KNOWLEDGE TO LEAD | ISSN 2765-0626 | Volume 4 | Issue 1 | Oct. 2023 by Education Association for Software Empowerment

ISSN 2765-0626 | Volume 4 | Issue 1 | Oct. 2023

KNOWLEDGE TO LEAD (ISSN 2765-0626) is a youth interdisciplinary and inclusive journal, oﬀering middle school and high school students a unique platform to publish their research manuscripts and research proposals across various research ﬁelds. This invaluable experience fosters their intellectual curiosity, broadens their perspectives on societal phenomena and global issues, and hones their creative problem-solving skills to address the diverse challenges of sustainable development. In Volume 4, Issue 1, we proudly feature manuscripts produced by participants of the 5th HOBY Korea Global Youth Academic Enrichment Program, award-winning manuscripts from the 7th International Youth Research Paper Competition, as well as manuscripts and research proposals selected for the 3rd HOBY Korea International Young Scholars Conference. HOBY Korea actively encourages and supports teenagers who engage in research activities, regardless of their skill level or the scale of their projects. We extend our heartfelt appreciation to all the authors who have contributed to this volume.

TABLE OF CONTENTS RESEARCH PAPERS – SOCIAL SCIENCES 6

Beyond materials access: a state-level analysis of the multifaceted relationship between digital divide levels and multivariable determinants of Internet use Ahn, Andrew

Technical Analysis and the Impact of News Sentiment on the Dow Jones Industrial Average Market: An Empirical Study Ahn, Hoseok

The Solar Energy Landscape and the Paris Agreement: China and the United States Cha, Yejoo

Chinese Elite Politics after 20th Party Congress: Emphasis on Xi Jinping’s leadership system Choi, Jayun

Navigating Inclusivity: Unveiling Challenges in Using Public Transportation Network for Visually Impaired Individuals in the Seoul Capital Area Hong, Seokhyeon & Seo, Yewon

Devising a Framework for Nudge Applying Behavioral Psychology In, Jenny & Kim, Minchei

Assessing the State of Mental Health Among Prisoners and the Accessibility of Mental Management Centers Across States in the United States Jung, Selice

105

Opposing Common Conception: Weak Positive Relationship Between Academic Performance and Exercise Kim, Ashley

124

Global Imports in the War on Ukraine: How Big of an Impact Has Russia’s Invasion Had on the World Economy? Kim, Dayeon

136

Insights on Korean Perceptions of Chinese Environmental Issues Based on a Big Data Analysis Kim, Donghyuk

151

Entwined Economies: Exploring Evolving US-China Relationships in a Globalized World — is it in the US’ interest to decouple from China economically? Kim, Junseo

164

The Association between Islamophobia in South Korea and the Perceived Distance of Muslims Lee, Haejun

172

Protection Trade Fosters Domestic Production and Real Gross Domestic Product Lee, Heejoon

180

From Stigma to Inclusion: Rethinking Special Education for Learning Disorders in South Korea Lee, Yoona

189

Impact of White Noise on Cognitive Performance: A systematic review Oh, Phoebe

198

Social Stigma on Electronically Monitored Offenders in South Korea Rhee, Sieeun

208

Predicting the Decline of Pronvincial Cities through Data Science Techniques Seo, Yeeun

219

Speak Big and Carry a Soft Stick: China as a Superpower of 21st Century Shin, Gun

225

Is Language an Indicator of Inclusion and/or Exclusion? A Historical Investigation Using Idioms of Catalan and Castilian Culture Shin, Irene Su Yeon

231

A Case Study on the Conflict of International Trade between U.S. and China: Focusing on the Advanced Technology Shin, Phil Gyu

240

Relationships between Different Types of Childhood Neglect and Personality Characteristics Sim, Yeji

247

Koreans’ Perception of China in Social Media (Using Social Network Analysis) Sohn, Olivia Chaeri

RESEARCH PAPERS – STEM 258

Medical Data Clustering Algorithm with Improved Weighted Calculation Cha, Igyeong

271

EGCG's Protective Role Against Brain Cell Death in 3D Human Glial Cell Model of Alzheimer's Disease Cho, Hyunseo

279

How Does the Frequency of the Touch Stimulation Affect Plant Growth? Chung, Sehwan

312

A Study on the Identification and Solution of Staphylococcus aureus and E. coli Resistance to Antibacterial Copper Ions in Soil Contaminated with Copper ion (Cu 2+) Chung, Seungah

328

How can Nanosensing be Used for Outer Space Health Monitoring? Chung, Yehwan

337

Technological Innovations Shaping the Future of Healthcare Ham, Jiseok

354

Understanding Photodetector Mechanisms in PET Scans for Tumor Localization Jung, Michelle

364

Securing the Future: The Necessity and Potential of Post-quantum Cryptographic System Jung, Seoeun

373

Interaction of Thigmomorphogenesis and Nutrient Application on the Production of Basil Kim, Aaron Junung

387

Nanotechnology and Space Exploration: How Can Carbon Nanotubes and Self-Healing Materials Contribute to Making Advancements in Space Exploration Technology? Kim, Jinheon

398

Novel selenium antibacterial compounds against super bacteria Kim, Ju Hyun

406

Development of Eco-friendly Fishing Nets with Ramie and Linen Fiber Coated with Natural Beeswax Kim, Yesel Priscilla

416

The Effect of Thigmomorphogenesis on the Growth Rate of Basils and Blue Sages Lee, Haryeong

428

Safety System for Aircraft Water Landing in Emergency Situations Lesbekova Amina & Murat Almas

447

Optimizing the shape of the blade for improved efficiency in Savonius-type wind turbine Nam, Dohyun & Bae, Yohan

459

Study on Enhancing the Accuracy and Sensitivity of Identifying Parasites Using an Object Detection Model Seo, Brendan

469

Applying Nano Drug Delivery System for Respiratory Diseases Song, Minkyung

478

The Investigation of Bacteria Species in Communal Cutlery Trays in High School Settings Yi, Chaekyoung

491

Contrastive Learning of visual representations for Plant Disease Recognition Yoon, Seung Wook

509

Identification of Exoplanet Candidates using CNN Models based on Light Curve You, Dongho & Kim, Hwan

526

Motion Abnormality Detector - Detecting Fall Injuries Prevalent in Vulnerable Populations Youn, Minhyuk & Lim, Wonjun &Yu, Choeun

TRESEARCH PROPOSALS 544

547

How much is enough sleep? Current status of sleep duration in South Korea after Covid 19. Chang, Won-Jun Exploring the Neural Underpinnings of Aesthetic Preferences in Design: A Multidisciplinary Analysis Choi, Yejune

555

Assessing the Environmental Impact of Electric Vehicle Batteries: Towards Sustainable Solutions and Future Outlooks Hwang, Yujin

563

Unveiling the Veil: Assessing the Efficacy of International Efforts in Addressing Human Rights Abuses in North Korea Kim, Yoonseo Hanah

RESEARCH POSTER 574

First Record of ‘Pyroplastics’ Found in the Jeju Island Sea, South Korea Kim, Eryn

RESEARCH PAPERS

- SOCIAL SCIENCES

Beyond materials access: a state-level analysis of the multifaceted relationship between digital divide levels and multivariable determinants of Internet use Author 1

Full Name

Ahn, Andrew

Washington University in St. Louis

(Last Name, First Name)

School Name

ABSTRACT: Although the world claims to be in an alleged digital era – and the US, the most dominant country of this era – the digital divide remains a significant yet overlooked problem, especially in the US. This study adopts a holistic approach to conduct a state-level analysis of the digital divide. This study explores all three levels of the divide and compares the results for top- and bottom-ranked states of Internet use, to illustrate the overall scheme of the digital divide in the US. This study analyzes data from two sources: the National Telecommunications and Information Administration (NTIA) and an online survey. While the former is a public social dataset, the latter is an empirical survey conducted in July through August 2023, from 50 randomly sampled respondents in the top- and bottom-ranked states. The results show that while the first- and second-level divides can be perceived positively, the third level remains a significant problem. In other words, the findings reveal that access and usage are insufficient to bridge the digital divide. These findings warrant future research on the third-level divide and remind policymakers to thoroughly consider the third level to bridge the digital divide in the US.

KEYWORDS: Digital Divide, ICT Access, ICT Use, State-Level Difference

1. Introduction Over the past few decades, access to information and communication technology (ICT) has become indispensable to society (Chakraborty & Bosman, 2005). However, demographics that lack access to ICT, known as the digital divide, are still overlooked. Digital divide refers to the gap between those with adequate access to ICT and those with poor or no access to ICT (Soomro et al., 2020). Importantly, the digital divide is a multidimensional concept often divided into three levels (Lythreatis et al., 2021). The first-level digital divide refers to the binary distinction between people with adequate access to ICT and those with poor or no access to ICT (Soomro et al., 2020). Previous studies show that access to digital devices and the Internet is unequally divided among many variables such as age, gender, ethnicity, level of education, and demographic factors (Mubarak et al., 2020; Ragnedda & Kreitem, 2018; Gladkova et al., 2020). As more people gain access to digital devices and the Internet, a secondlevel digital divide occurs, as having access to such technology does not guarantee that people will use it in the same way owing to different usage and skills. It encapsulates the differences in digital skills and usage as well as inequalities in technical means, autonomy, and patterns of use (DiMaggio et al., 2004). Previous studies explored the second-level digital divide by examining how access affects ICT use (Pearce & Rice, 2013). Other studies categorize Internet use into two categories, namely, taskoriented and entertainment use, to specify the second-level divide (Huang et al., 2017; Pearce & Rice, 2013; Robinson, 2009). Recently, researchers have suggested that having access to, use of, and skills in using ICT and digital devices do not directly translate into beneficial outcomes. Hence, the ‘third-level digital divide’ is defined as the shift from the use and skills of Internet use to benefits from using the Internet (Wei et al., 2011). Psychological variables such as self-efficacy, emotional costs, and anxiety are used to describe the third-level digital divide (Huang et al., 2017; Peral-Peral et al., 2019). Researchers examined the third-level digital divide by manipulating different variables and parameters. Huang et al. (2017) examine the impact of mental access on changes in ICT use by adopting surveys to evaluate the impact of technology-focused interventions aimed at providing more digital access to students. Students with low computer access focused on task-oriented use to avoid emotional costs, while students with higher computer access experienced lower emotional costs, allowing them to engage in entertainment-oriented Internet use. It shows relationships at the second level by addressing how psychological factors affect Internet use patterns. Here, I examine how these three levels of the digital divide manifest and relate to each other, specifically in the top- and bottom-ranked US states in terms of Internet use. Five top-ranked and five bottomranked states are selected based on the two published rankings. The three levels of digital divide included variables such as device type, Internet service type, online activity type, self-efficacy, and emotional costs. Additionally, as an integrated study, data, which were in various forms, were collected in two ways: public data from the National Telecommunications and Information Administration (NTIA) and empirical survey data collected via an online survey.

2. Methods Sample To select the US states for analysis, the state Internet and Broadband rankings published by BroadbandNow Research and Tufts University were considered. The two rankings were selected following the high credibility of the two institutions as well as the thorough methodology each source presented as to how they finalized their ranking. From these rankings, five top-ranked and bottomranked US states were selected based on the sum of the rankings from each source. Accordingly, New Jersey, Maryland, Delaware, New York, and Massachusetts were chosen as the top- ranking states, whereas West Virginia, Arkansas, Mississippi, Vermont, and New Mexico were chosen as the bottomranking states. All analyses regarding the NTIA data considered the five most recently measured

proportion values, as the target states have different populations.

Procedure Data collected from the NTIA, a supplement to the Current Population Study, were used as the main social data, including information on device use, types of Internet services, Internet use, online activities, and accessibility for each US state (Table 1). It is important to note that, while the dataset included many variables about the first- and second-level divides, it lacked variables about the third-level digital divide. Given that the third-level digital divide primarily relates to psychological and subjective concepts, it is appropriate to collect data from empirical investigations. Hence, an online survey was conducted to examine the relationship between the second- and third-level divides.

Table 1. Social Data Set Variables

Design For surveys to collect empirical data, an online survey platform (SurveyMonkey®), which included 61 questions, was used from July to August 2023. A randomly selected sample of 100 individuals comprised 50 individuals from the chosen bottom and top-ranked states. The first section of the survey was self-explanatory, collecting information on age, sex, ethnicity, and occupation. The second section asked how frequently and confidently they used the Internet. Internet use was sorted into task- and entertainment-oriented activities to consider how different types of

activities manifest differently in states with multiple choices, on a 7-point Likert scale. The last section collected data on third-level digital divide variables with 20 questions using a 7-point Likert scale designed based on previous studies (Table 2).

Table 2. List of the third-level divide variables on the online survey

3. Results and Discussion Social Data The analysis of social data from the NTIA revealed two key findings. The findings showed that the first-level digital divide has shown significant and positive developmental progress (Figure 1). The urbanization and universalization of ICT has made digital devices and Internet use more accessible for everybody. Over time, the findings show that a similar proportion of people in the top- and bottomranked states have access to ICT and the Internet. In 2015, there was a 6% gap in the number of

people with mobile data between the top- and bottom-ranked states. Unsurprisingly, in 2021, this gap narrows to approximately 2%.

Figure 1. Mobile Data Access in the top- and bottom-ranked States (2015 - 2021). The blue and red lines represent the top-ranked and bottom-ranked states respectively. This trend is common in most first-level divide variables, with all variables except laptop use at 6.86% and wired high-speed at 10.26%, with a gap of less than 4% in 2021. Therefore, the findings reveal that the first-level digital divide has narrowed significantly, as shown by the small disparities between the top- and bottom-ranked states. Second, the findings reveal that the second-level digital divide shows positive developmental progress. This suggests that, while the first-level digital divide is relatively bridged and shows positive progress, the second-level digital divide remains a major problem, especially for bottom-ranked states. Although the top- and bottom-ranked states for many second-level variables differed significantly, most variables showed a low disparity in 2021. In 2021, all variables had a top-to-bottom state difference lower than 5%, except for online activities of participating in video conferences, working remotely, and seeking jobs with a gap of 8.22%, 6.84%, and 5.76% respectively. Furthermore, the top-ranked states exceeded the bottom-ranked ones for all second-level variables in 2021, except social networking services, where the bottom-ranked states’ activities have been higher than those of the top-ranked ones since 2015. This demonstrates that despite the fact that the top states still have more access to and skills in using ICT and the Internet, the bridging of the first-level divide in the bottom states and the second-level divide in the bottom states are currently in a positive phase.

Survey Data

Table 3. Descriptive statistics for the frequency and confidence of performing online activities and third-level digital divide variables in bottom states. Note that Task Freq = Frequency of task-oriented online activities, Ent Freq = Frequency of entertainment-oriented online activities, Task Conf = Confidence of task-oriented online activities, Ent Conf = Confidence of entertainment-oriented online activities, Int Self = Self-efficacy of using the Internet, Dig Self = Self-efficacy of using digital devices, Tech Anx = Technological anxiety, Emo Cost = Emotional costs.

Table 4. Descriptive statistics for the frequency and confidence of performing online activities and third-level digital divide variables in top states. See Table 3 label for variable abbreviations. As shown in Tables 3 and 4, respondents in both the top- and bottom-ranked states reported moderately frequent use of both types of activities. However, entertainment-oriented activities exceeded taskoriented activities in both cases. Furthermore, the trends show that bottom-ranked states are more engaged in entertainment-oriented activities than the top-ranked ones, whereas the top-ranked ones are more engaged in task-oriented activities than the bottom-ranked ones. This is inconsistent with previous findings, which state that households with low access to ICT and the Internet – in this study’s case, bottom-ranked states – were more likely to engage in task-oriented activities owing to their low levels of confidence (Huang et al., 2017). Despite this inconsistency, the specific logic that led to such previous findings – that confidence and frequency are positively related – remain consistent in this study. To specify, the mean confidence level in performing task-oriented activities was higher for top-ranked states (M = 5.407) than for bottom-ranked ones (M = 5.194), aligning with the frequency of performing task-oriented activities being higher for the top states. In contrast, confidence in performing entertainment-oriented activities was higher for bottom-ranked states (M = 5.624) than for top-ranked ones (M = 5.573), consistent with the higher frequency of performing entertainment-oriented activities for the bottom states. Therefore, this substantiates the presence of a third-level digital divide and the important role psychological variables can play in bridging this divide. Self-efficacy in using the Internet was higher in the top-ranked states (M = 5.137) than in the bottomranked ones (M = 4.886). This result substantiates the findings, which state that top-ranked states have greater online activity use than bottom-ranked ones, as respondents are more confident in having the skills to access such online activities. Conversely, self-efficacy in using digital devices was higher in the bottom (M = 5.420) than in the top group (M = 5.379). Therefore, the bottom states are confident in their skills of using and navigating digital devices, pertaining to bridging the first-level digital divide. However, the bottom states still need to build confidence in their skills to use the Internet, as Internet self-efficacy for top states is higher, pertaining to the second-level digital divide. Moreover, technological anxiety, emotional costs, and privacy concerns of the top-ranked states (M = 2.721, 2.504, and 4.215, respectively) were lower than those of the bottom-ranked ones (M = 2.935, 2.774, and 4.533, respectively). All third-level divide variables are lower in the top states, thus suggesting that top states can use digital devices and perform online activities more frequently because they have lower psychological barriers.

Table 5. Pearson’s correlation analysis of average frequency and confidence levels for task-oriented and entertainment-oriented online activities in bottom states. See Table 3 label for variable abbreviations.

Table 6. Pearson’s correlation analysis of average frequency and confidence levels for task-oriented and entertainment-oriented online activities in top states. See Table 3 label for variable abbreviations. As shown in Tables 5 and 6, the frequency of task- and entertainment-oriented activities showed a strong positive correlation in the top- and bottom-ranked states. Likewise, confidence in both activities showed a strong positive correlation: rtaskconf-entconf(48) = .609, p < .001 in the bottom-ranked states and rtaskconf-entconf(48) = .597, p < .001 in the top-ranked ones. This reveals that frequent and confident users of task-oriented activities are also frequent and confident about entertainment activities (Figure 2). In the bottom states, the frequency and confidence for both activities were positively correlated. However, the correlation between frequency and confidence is stronger for entertainment-oriented activities. Therefore, while the frequency and confidence in performing both activities are similar, it is still evident that entertainment-oriented activities are more dependent on confidence. No strong correlations were found among the top states. Therefore, weak psychological barriers may hinder or prevent top states from accessing online activities.

Table 7. Pearson’s correlation analysis of all third-level digital divide variables in bottom states. See table 3 label for variable abbreviations.

Table 8. Pearson’s correlation analysis of all third-level digital divide variables in top states. See table 3 label for variable abbreviations. As shown in Tables 7 and 8, the confidence levels for both activities were positively correlated with both Internet and digital self-efficacy. These results reinforce the intuitive relationship between confidence levels and self-efficacy as can be assumed from the connotations of the two words. Internet and digital self-efficacy also displayed strong positive correlations in the top- and bottom-ranked states. Moreover, technological anxiety and emotional cost show a strong positive correlation: rint-dig(48) = .823, p < .001 in the bottom- and rint-dig(48) = .875, p < .001 the top-ranked states. Both results are intuitive, as can be assumed from the connotative meaning of each variable. Regarding respondents from the top states, Internet self-efficacy was negatively correlated with technological anxiety and emotional costs, rint-anx(48) = – .532, p < .001 and rint-emo(48) = – .513, p < .001, respectively. This indicates that Internet self-efficacy translates into technological anxiety and

emotional costs, meaning that top state users have a lower psychological burden. Similarly, regarding respondents from the bottom states, Internet self-efficacy was negatively correlated with technological anxiety and emotional cost, rint-anx(48) = – .314, p = .027 and rint-emo(48) = – .434, p = .002, respectively. Having a relatively weaker correlation indicates that despite the presence of self-efficacy, individuals from bottom-ranked states still experience psychological boundaries from fully engaging with the Internet. The bottom states participate less in all but one second-level variable, which is attributable to this third-level digital divide. Furthermore, regarding the bottom-ranked states, digital self-efficacy was negatively correlated with technological anxiety and emotional cost, rdig-anx(48) = – .323, p = .022, and rdig-emo(48) = – .375, p = .007, respectively, while the top-ranked states showed insignificant correlation. This implies top-state respondents use digital devices spontaneously, and high self-efficacy does not necessarily translate to low technological anxiety or emotional costs, as there are no psychological barriers. The negative correlation for bottom states demonstrates that although psychological boundaries still exist, respondents with high digital self-efficacy generally face low technological anxiety and emotional costs. The results identified the status quo of each digital divide level and examined the multifaceted relationships among all three levels. Figures 2 and 3 show all the correlations. This section reveals that, for the first level, while individuals in the top states have more access to digital devices and the Internet, the gap between the top- and bottom-ranked states is small. Similarly, for the second level, while the top-ranked states use online activities more often than the bottom-ranked ones, the gap between the two is small. Hence, it is evident that examining the third-level digital divide is essential for understanding its current mechanism of digital divide.

Figure 2. Summary chart of all significant correlations of all third-level digital divide variables for bottom states. See table 3 label for variable abbreviations.

Figure 3. Summary chart of all significant correlations of all third-level digital divide variables for top states. See table 3 label for variable abbreviations.

4. Conclusion To better comprehend the overall scheme and trend of the digital divide in the contemporary US, this study conducts an integrated research approach and state-level analysis. First, this study shows that the first- and second-level digital divides can be positively perceived, as the gap between the top- and bottom-ranked states is small. The top-ranked states exceed the bottom-ranked states for almost all the first- and second-level variables. Second, the empirical survey data evidently show that the third-level digital divide is an important influencing factor of the second-level divide. The correlation between confidence and frequency confirms this finding. Lastly, the results of the correlation analysis of the survey data indicate that the third-level digital divide remains an issue in the bottom-ranked states despite the low levels of the first- and second-level divides. Despite these important implications, this study has some limitations. First, although a concrete selection method was justified, there may have been limited representativeness. Second, this study’s sample size could be relatively insufficient for aggregating data, which may result in noisy and highly estimated results. Finally, the fact that respondents could access online surveys suggests that they already possess high confidence and self-efficacy levels. Hence, the survey data did not include the bottom ends of the population that lacked access to any form of ICT or the Internet. Despite these limitations, the results of this study provide positive and significant findings that provide insight into the overall scheme of the digital divide in the contemporary US.

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Robinson, L. (2009). A taste for the necessary: a Bourdieuian approach to digital inequality. Information Communication & Society, 12(4), 488–507. https://doi.org/10.1080/13691180902857678 Shevik, J. (2023). Best & worst states for broadband, 2023. BroadbandNow. https://broadbandnow.com/research/best-states-with-internet-coverage-and-speed Soomro, K.A., Kale, U., Curtis, R., Akcaoglu, M., & Bernstein, M., (2020). Digital divide among higher education faculty. International Journal of Educational Technology in Higher Education, 17 (1), 1–16. https://doi.org/10.1186/s41239-020-00191-5 Wei, K.-K., Teo, H.-H., Chan, H. C., & Tan, B. C. (2011d. Conceptualizing and testing a social cognitive model of the digital divide. Information Systems Research, 22(1), 170–187. https://doi.org/10.1287/isre.1090.0273

Technical Analysis and the Impact of News Sentiment on the Dow Jones Industrial Average Market: An Empirical Study

Author 1

Full Name

Ahn, Hoseok

Asia Pacific International School Seoul

(Last Name, First Name)

School Name

ABSTRACT: Prompted by flaws observed in the Efficient Market Hypothesis, this paper investigates the correlation between manifestations of information conveyed through news title sentiments and technical analysis activities. Consequently, the paper assesses the means and variances of the returns of five distinct technical analysis strategies, namely Stochastic Relative Strength Index (RSI), Bollinger-Band, Moving Average Convergence/Divergence (MACD), MACD Breakout, and Volatility Breakout. The performance evaluations are based on Dow Jones Industrial Average during 360 randomly selected thirty-day periods in 2016, utilizing sixty-four-day period data. Moreover, the study compares these strategies in different informational contexts, which are identified by sentiment analysis of Google News article titles. The study’s findings indicate that in neutral sentiments, the means of technical indicator algorithms do not significantly deviate from the benchmark strategy. However, under negative and positive sentiments, the findings indicate that technical analysis strategy means all exhibit significant deviations from the benchmark. Furthermore, this study demonstrates that variances of both the benchmark and MACD display significant heterogeneity across different sentiments. By analyzing a variety of technical indicator algorithms and their relationship with news sentiments, the study offers practical implications for investors within diverse market sentiments. The results of the findings highlight the significance of considering news sentiment when implementing technical analysis strategies.

KEYWORDS: Efficient Market Hypothesis, News Sentiment, Technical Analysis, Stochastic Relative Strength Index (RSI), Market Conditions

1. INTRODUCTION Since Eugene Fama’s seminal proposal in 1970, the Efficient Market Hypothesis (EMH) has garnered widespread acceptance in the field of finance as the fundamental principle that governs market behavior. The theory posits that unexpected information (1) governs price movements and (2) elicits immediate and rational responses from investors, a notion found favorably among many due to the perceived unpredictability of markets. (Malkiel, 1989) Technical indicator stood in opposition to the doctrine of the EMH as past price trends cannot apply to future price trends if only the unpredictability of information matters. As a result, technical indicator algorithms, which rely on historical data to identify mispriced stocks, were discredited, particularly pronounced in the Dow Jones Industrial Average (DJIA) market. This apparent theoretical conflict was eventually resolved when the EMH’s premise of immediate and rational stock prices was debunked. (Ozkan, 2021) (Tran and Leirvik, 2019) (Mnif et al., 2019) In the subsequent years, numerous studies have investigated the efficiency of markets, many revealing significant inefficiencies that contradicted the EMH. Prominently, Van Oort (2018) examined the 2016 DIJA market employing the Geographical Market Segmentations to identify “prolific” and “persistent” inefficiencies therein. They revealed that market efficiency changes over time and under different circumstances. These discoveries negate the presumption that investors cannot benefit from market timing strategies. If markets are inefficient, that is, the aggregate of investors fails to react to information instantly and correctly, stock prices undergo adjustment periods. According to Wong et al. (2003), during such periods, mispriced stocks lag to correctly represent information. Consequently, technical analysis strategies can exploit these adjustment periods and generate abnormal profits by identifying footprints in price movements, using historical data to trade at optimal prices. However, practical applications do not always attest to the predictability of technical analysis during adjustment periods. In fact, several studies have documented the relative underperformance of different technical analysis strategies across various markets. (Batten and Ellis 1996). Li et al. (2019), Alfonso and Ramirez (2020), Alusabaie et al. (2019), Lahmiri (2014), Rech et tal. (2006), Naik (2019), Ozturk et al. (2016), Oliveira et al. (2011) hypothesized that the performance of technical indicator algorithms varies due to the different affinities of stocks with various properties towards technical indicators. In this belief, Yao (1999) employed the non-linear method of neural networks as a model to forecast stock prices in the Kuala Lumpur Stock Exchange. Further, Alfonso and Ramirez (2020) developed a distinctive non-linear method to combine technical indicators, addressing the limitations of neural networks that lack sufficient generalization power in high dimensional markets. Similarly, machine learning studies have experimented with algorithms to deconstruct markets into combinations of variables and develop technical indicators accordingly, which include tech naïve Bayes (NB) (Alusabaie et al, 2019), fine-tuned naïve Bayes (FTNB) (Alusabaie et al., 2019), support vector machine (SVM) (Alusabaie et al, 2019) (Lahmiri, 2014), MetaCost wrapper (Alusabaie et al, 2019), cost-sensitive fine-tuned naïve Bayes (CSFTNB) (Alusabaie et al, 2019), and Technical Trading Indicator Optimization (TTIO) (Li et al, 2019). One noteworthy study is Lahmiri (2014), which modeled entropy in the international stock market to optimize technical indicator combinations using the SVM. More attempts at finding technical indicators in relation to the market include the experimentations of the Boruta feature selection (Naik, 2019), heuristic methods (Ozturk et al., 2016), tuning, and parameters (Oliveira et al, 2011). Additionally, few studies have focused on time horizons as determinants of technical indicator performances. Using fuzzy systems, Chourmouziadis (2015) proposed a short-term horizon to technical analysis trading. A study by Shynkevich et al. (2017) determined that the predictive performance of technical analysis peaks when the forecast horizon equals the time frame.

However, insufficient attention has been devoted to the impact of information on the efficacy of technical indicators. Studies have consistently adhered to the presupposition that technical indicator algorithms operate independently of information awareness, neglecting the possibility that prevailing market information could greatly influence the varied returns of technical indicator as posited by the EMH. In this paper, I examine how technical analysis strategies perform in relation to prevailing informational trends. To quantitatively represent information, I employ polarity scores of news title sentiments, which capture both investor interpretations of information and the factual market context. (Zhai et al., 2010) (Siering, 2012) (Wan et al., 2021) The constants derive from a sentimental analysis of news titles collected on Google News, which evenly provides news articles from various investment communities. (Mohan et al., 2019) Specifically, my focus is on the Dow Jones Industrial Average market during 2016, a period previously established as inefficient by Van Oort (2018). This precondition garentees the theoretical possibility for technical analysis to generate abnormal profit by its predictive ability over the randomness of the market. (Wong et al., 2003) My study offers practical implications for practitioners of technical analysis. It identifies general sentimental circumstances for which technical analysis outperforms and underperforms the Dow Jones Industrial Average market. This may help the practitioners enhance their profitability by avoiding return losses relative to the market. Furthermore, the study sets a direction for forthcoming technical analysis studies. By further examining how the contents of information determine the returns of technical indicators, future academics may develop technical analysis strategies that predominantly warrant consistent alpha generation. The subsequent sections of this study are organized as follows. Section 2 discusses the methodologies. Section 2.1 <Period Randomization> establishes the premise of market inefficiencies and outlines the criteria for data collection, while Section 2.2 <Stock Data Collection> explains how this study obtained stock price movement data. Section 2.3 <Technical Analysis Simulation> delineates the processes of technical analysis algorithms simulated in the study. Section 2.4 <News Article Title Collection> discusses ways in which this study obtains news article title data. Section 2.5 <Sentiment Analysis> details how this study converts news article titles into quantitative polarity scores, leading to section 2.6 <Data Analysis>. Section 3 primarily focuses on the results and significance of the study’s findings. Section 3.1 displays and evaluates the overall performances of trading strategies. Section 3.2 demonstrates the sentiment data of news article titles and defines negative, neutral, and positive sentiments accordingly. Section 3.3 evaluates the performance of technical trading strategies in relation to sentimental patterns. Finally, Section 4 presents the conclusion of this paper, summarizing the key findings and implications derived from the study.

2. METHODOLOGY This study aims to examine the effects of sentiments on the performance of technical indicator algorithms. To assess the technical analysis performance, five widely recognized strategies are selected: Stochastic Relative Strength Index (RSI), Bollinger-Band, Moving Average Convergence/Divergence (MACD), MACD Breakout, and Volatility Breakout (Breakout). These strategies are then applied to all stocks listed in the Dow Jones Industrial Average (DJIA) during 360 randomly chosen sixty-four-day periods, spanning from November 1st of 2015 to December 30th of 2016. These periods correspond to the thirty-day intervals starting January 1st of 2016, providing a representative sample of the stocks' performances. Given the algorithms’ objectives of generating buy and sell signals within a thirty-day time frame based on evaluating past trends, it was necessary to include a comprehensive sixty-four-day data set to accurately represent the employed data.

The data collected and represented in this study exhibit variations due to specific data requirements for the Bollinger-Band, Volatility Breakout, MACD, and MACD Breakout algorithms. These variations are considered during the analysis to ensure the accuracy of the technical analysis performances computed. This study’s selection of technical indicators derive from Pheng et al. (2022), which identified optimal models that produced statistically significantly different returns compared to the non-involvement in stock markets. This increases the likelihood that technical analysis performances follow their predictive movements moreso than the general market trend to ideally maximize profit margins. Through the application of natural language processing techniques, the study quantitatively assesses the sentimentality of these titles and assigns polarity scores accordingly. Each polarity score enables the classification of titles into distinct sentiment categories of “negative”, “neutral”, and “positive”. The division of sentiments relies on the distribution of sentiments observed in the 360 randomly selected sixty-four-day periods, following the succeeding directive: The lowest 120 stocks set the range for negative sentiments, the middle 120 stocks set the range for neutral sentiments, and the upper 120 stocks set the range for positive sentiments. Subsequently, each polarity score is paired with its corresponding technical analysis performance to establish a relationship between sentiment and performance. The study then proceeds to evaluate the variances and means of the trading strategies across different sentiment categories, whilst examining their statistical significance. This paper discusses the relationship between news title sentiments and the effectiveness of technical analysis strategies along with the specific procedures in more detail through subsections: <Period Randomization>, <Stock Data Collection>, <Technical Analysis Simulation>, <News Article Title Collection>, <Sentiment Analysis>, and <Data Analysis>.

2.1 Period Randomization To investigate the performance of technical analysis and sentiment patterns, this study focuses on thirty Dow Jones Industrial Average (DJIA) stocks and their corresponding Google News article titles from November 1st of 2015 to December 30th of 2016. The selection of this specific market and time period follows the approach employed by Van Oort (2018), which identifies extended durations of market inefficiency across the Dow Jones Industrial Average stocks in 2016. While the performances of stocks and sentiments during this year long period may not necessarily represent the same performances of other periods, they are crucial in establishing the premise of market inefficiency, which forms the foundation for exploring the potential utilization of implied informational patterns through technical indicator algorithms. Within the said period, the study randomly selects 360 sixty-four-day subperiods, with each subperiod dedicated to one of the thirty DJIA stocks. This approach ensures the availability of diverse market data and news titles that reflect information trends. The chosen quantity of subperiods is designed to meet the statistical requirements of the Central Limit Theorem and normality, even with the presence of abnormally distributed data points. The thirty-day parametrization of each subperiod allows for the study of short-term trading performances that include multiple buying and selling activities. This emphasis on short-term horizons aligns with the trading practices commonly observed among technical analysis practitioners Chourmouziadis (2015) and Taylor et al. (1992). The randomization processes are implemented via a random module in Python, ensuring unbiased selection of variables.

2.2 Stock Data Collection Once the randomization of subintervals for analysis is complete, the study proceeds to collect price movement data for the selected DJIA stocks. This data collection includes the highest, lowest, closing, and opening prices of the stocks on a daily basis, all of which pertains to the trading mechanisms of the benchmark and different technical analysis strategies, as outlined in Section 2.4. To collect the price

data, the study employs Pandas DataReader, a data analysis tool from Panda used to facilitate data extraction from Yahoo Finance. As an online stock data API platform, Yahoo Finance presents comprehensive historical price data for all 30 DJIA stocks. No alternative platform was considered as the documentation of stock pricing remains consistent across platforms.

2.3 Technical Analysis Simulation Although the benchmark and technical analysis strategies all exhibit distinct methods in arranging trading cues, they share the fundamental algorithmic framework of buying stocks at buy signals and divesting stocks at sell signals. Hence, it is possible to simulate the application of various technical analysis strategies under a unified procedure. (Brock et al., 1992) The study undertakes the processing of all technical analysis calculations by implementing four sets of commands: 1. Start thirty-day trading intervals from January 1st of 2016 to November 18th of 2016 with a money value of $1,000,000. 2. For every business day, add the factor of the number of stocks owned and the recorded day's closing price plus the remaining money value and append this value as an asset. If no stock is held, append the remaining money value. 3. When a trading strategy generates a buy response, divide the money value by the recorded day's closing price to calculate the number of stocks bought to the nearest whole number. Then, properly update the amount of money by subtracting the product of the number of stocks purchased and their closing prices. 4. When a trading strategy cues a sell signal, multiply the number of purchased stocks by the closing price. Add the resulting number to the amount of money value. Further, fix the number of purchased stocks to zero. * As an exception to Procedure 3, when the Breakout strategy generates a buy signal, it will divide the money value by the sum of the recorded day's opening price and Volatility Score to calculate the number of stocks bought to the nearest whole number. It will subtract the product of the number of stocks purchased and the sum of the recorded day's opening price and Volatility Score from the previous day's money value to update the money value.

The aforementioned procedure provides an overarching algorithm for technical analysis simulations that predicate on signal generations. Below, this paper details the signal generation mechanisms of the Stochastic Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD), Bollinger-Band, and Breakout in addition to the benchmark. All of the below technical indicators are selected based on Pheng et al. (2022), which identified the optimal models that reject the null hypothesis of equality of the mean returns between buy signals and sell signals.

2.3.1 Relative Strength Index The stochastic RSI Relative Strength Index (RSI) is a technical indicator that measures the speed, velocity, and momentum of price movements in a market. (Brzeszczynski and Boulis, 2019) RSI employs a specific formula to generate buy and sell signals:

ܴܵ‫ = ܫ‬100 െ 100/(1 + ܴܵ) * In the formula, RS refers to Relative Strength. It is derived by dividing the average gain by the average loss over a 14-day period. Both average gain and loss are expressed as positive numbers. The study implements a 14-day period as its parameter, which aligns with the prevailing preference among RSI traders.

The paper follows three different RSI rules as indicated: 1. A buy signal is triggered when RSI crosses the centerline (RSI=50) from below, while sell signal is generated when RSI crosses the centerline from above. (Brzeszczynski and Boulis, 2019) 2. RSI algorithm identifies two zones (oversold and overbought zones) utilizing its RSI values. When RSI value falls below 30 (RSI<30), stocks are considered oversold. Conversely, when RSI rises above 70 (RSI>70), stocks are considered overbought. (Brzeszczynski and Boulis, 2019) 3. A buy signal is produced when RSI value fallen to the oversold zone rises back above 30, and a sell signal is obtained when RSI rises above then falls below 70. (Brzeszczynski and Boulis, 2019)

2.3.2 Bollinger-Band Bollinger-Band is a trading strategy that assesses volatility of securities, encompassing both price and volatility characteristics by indicating a relative definition of high and low prices of the market. The paper follows two set rules: 1. Entry and Exit signals of the stock purchase is generated by comparing price movements to their corresponding upper and lower Bollinger-Bands. (Lento, 2009) 2. The upper and lower Bollinger-Band is expressed by the equations below: ܷ‫ = ݀݊ܽܤ ݎ݈݈݁݃݊݅݋ܤ ݎ݁݌݌‬20 ݀ܽ‫ ܣܯܵ ݕ‬+ 2 ‫( כ‬20 ݀ܽ‫)݊݋݅ݐܽ݅ݒ݁݀ ݀ݎܽ݀݊ܽݐݏ ݁ܿ݅ݎ݌ ݕ‬ ‫ = ݀݊ܽܤ ݎ݈݈݁݃݊݅݋ܤ ݎ݁ݓ݋ܮ‬20 ݀ܽ‫ ܣܯܵ ݕ‬െ 2 ‫( כ‬20 ݀ܽ‫)݊݋݅ݐܽ݅ݒ݁݀ ݀ݎܽ݀݊ܽݐݏ ݁ܿ݅ݎ݌ ݕ‬. * In the equations above, the 20-day SMA represents a simple moving average value computed from the twenty most recent price data points. The implementation of a 20-day parameter aligns with the prevalent Bollinger-Band practices. (Lento, 2009)

The paper follows three different Bollinger-Band rules as follows: 1. The Bollinger-Band algorithm generates a sell signal when the equity price falls below the lower Bollinger-Band and triggers buy signals when the same metric reaches above the upper band. 2. Volatility level must be acknowledged when considering Bollinger Bands: Low volatility is suggested when upper and lower bands lie close together and market volatility increases as bands expand. 3. When volatility levels are high and Bollinger bands are far apart, a sell signal is obtained. Buy signal is produced as the difference between upper and lower bands decreases.

2.3.3 Moving Average Convergence/Divergence The Moving Average Convergence/Divergence (MACD) indicates the relationship between exponential moving averages (EMA) of security prices by comparing the movement of the MACD line and the Signal line to derive trading signals. (Yeung et al., 2023) The MACD line is computed as below:

‫ = ܦܥܣܯ‬12 ܲ݁‫ ܣܯܧ ݀݋݅ݎ‬െ 26 ܲ݁‫ܣܯܧ ݀݋݅ݎ‬ * The 12-Period EMA signifies the exponential moving average for twelve recent price data, and the 26-Period EMA is an exponential moving average for twenty-six recent price data. * The study selects 12-Period EMA and 26-Period EMA for its exponential moving average settings to reflect the conventional MACD practice. (Yeung et al., 2023)

The Signal line is computed as below:

݈ܵ݅݃݊ܽ = 9 ܲ݁‫ܣܯܧ ܦܥܣܯ ݀݋݅ݎ‬ * In this equation, the 9-Period EMA represents a nine-day exponential moving average for a MACD line. * The choice of a nine-day parameter aligns with the general practices associated with MACD. (Fang, 2014)

The study indicates two MACD rules: 1. MACD value is positive when 12-period EMA is above the 26-period EMA, and negative when 12period EMA is below the 26-period EMA. 2. MACD trading algorithm elicits a buy signal when the MACD line surpasses the signal line and a sell response when the MACD line falls below the signal line.

2.3.4 Breakout Volatility Breakout (Breakout) is a technical analysis strategy that relies on the volatility of a previous price point to trade to reflect the momentum of the market. By calculating the Volatility Score, this paper focuses on quantifying the daily returns of the price to measure the stock volatility. (Fang, 2014) The Volatility Score is calculated as follows:

ܸ‫ ݐݏ݄݄݁݃݅_ܲ| = ݁ݎ݋ܿܵ_ݕݐ݈݅݅ݐ݈ܽ݋‬െ ܲ_݈‫ כ |ݐݏ݁ݓ݋‬0.5 * P_highest represents the highest stock price observed during the preceding business day. * P_lowest represents the lowest stock price observed during the preceding business day.

Two Volatility Breakout rules are inferred in this paper: 1. Volatility Score implies how volatility of stocks impact future price movements of the market. 2. Breakout algorithm produces a buy signal when a price value rises by the Volatility Score from the opening price. A sell signal is triggered at the end of each day that produces the buy signal when the price value drops below the breakout range.

2.3.5 MACD Breakout The MACD Breakout strategy is a trading strategy that combines MACD and Breakout strategies, specifically developed for this study. The trading mechanism of MACD Breakout strategy is outlined as below: MACD Breakout first traces the MACD line and the Signal line according to the equation introduced in Section 2.3.3. It signals buy cues when the MACD line crosses above the Signal line. If this method does not detect a buy signal, MACD Breakout operates the Breakout strategy outlined in Section 2.3.4. MACD Breakout generates sell signals according to Volatility Breakout rules outlined in Section 2.3.4.

2.3.6 Benchmark The benchmark strategy, often referred to as the buy-and-hold strategy, is an investment technique in which investors purchase stocks and hold onto them for an extended period, regardless of short term price fluctuations. This strategy is based on the belief that over time, the stock market tends to exhibit an upward trend, leading to an increase in the value of investments purchased and held by investors. Unlike technical indicator algorithms, the benchmark strategy primarily focuses on long term investment growth and does not generate buy and sell signals.

3. EMPIRICAL RESULTS 3.1 Technical Analysis Performance The study evaluates the rates of returns for benchmark and technical analysis strategies to analyze their respective profitability. The rates of returns measure the net change in investment assets as percentages of the initial costs. To derive this metric, the study divides resulting investment outcomes by initial investment capital for each of the trading strategies. The results are summarized in Figure 1 and Table 1.

Figure 1. Benchmark and technical analysis rate of return scatter plot

Table 1. Benchmark and technical analysis average rate of return table Trading strategy

Average rate of return

Benchmark

101.69

RSI

100.22

Bollinger-Band

100.00

MACD

100.80

MACD Breakout

100.88

Breakout

101.00

Figure 1 illustrates the rate of returns for both benchmark and technical indicators during the studies designated test periods. The graph reveals that two of the trading strategies–Bollinger-band and RSI– exhibited rates of returns closely centered around 100%. This suggests that their algorithms failed to identify substantial price movements for entry in many of the reading intervals. On the contrary, MACD, MACD Breakout, and Volatility Breakout generated a diverse range of returns, scattered across various points. This trend implies that at least one of the following is true: (1) the DJIA stock price movements were diverse enough to generate a wide range of return values, and (2) the strategies had low thresholds for buy signals. Infrequently, MACD, MACD Breakout, and Breakout have been shown to generate rates of returns exceeding 110%. Benchmark strategy displayed a similar pattern, generating slightly higher rates of returns above 110% compared to other technical analysis strategies. Returns ranging from 100% to 110% are fairly evenly distributed among the mentioned strategies, indicating a diverse range of return rates. Returns below 100% were more sparsely distributed for the benchmark than for other strategies. Moreover, the benchmark strategy experienced significantly more deeply negative rates of returns than MACD, MACD Breakout, and Breakout strategies. The return rates below 100% did not converge towards 100% as closely as those observed in other technical indicators. This suggests that MACD, MACD Breakout, and Breakout may offer more stability than the benchmark strategy in underperforming markets. Table 1 presents the average rate of returns for the benchmark and the five technical analysis strategies. The table shows that all strategies achieved average rates of return exceeding 100%. This trend suggests that the DJIA stock market proved to be profitable for these strategies in 2016. Furthermore, the table demonstrates that, on average, the benchmark strategy outperformed all technical analysis algorithms used in this study. Combining this finding with the implication that benchmark underperformance generally carries more risk than underperformance of other technical analysis strategies, it can be asserted that the high-risk, high-return principle held true for DJIA stock trading in 2016. The comparative overperformance of the benchmark over technical analysis strategies can be attributed to the widely accepted knowledge that the benchmark tends to outperform technical analysis in bullish markets. (Cohen et al., 2015) In 2016, the Dow Jones Industrial Average experienced a drastic increase from 17,148.94 to 19,762.60, demonstrating a growth of 15.24%. (Dow Jones Industrial Average (^DJI) Stock Price, Quote, History & News) Under the assumption that bullish markets support benchmarks over technical analysis, such growth may account for a significant portion of the observed trend. Another factor that could explain the relative underperformance of technical analysis strategies is that the market inefficiencies in adjustment periods in the 2016 DJIA market mentioned in Van Oort (2018) were not long enough for daily technical algorithms to effectively detect.

3.1.1 <Technical Analysis Performance Mean and Variance Data Analysis> To check whether a pair of dataset with different mean exists, this study performs the One-way Analysis of Variance (ANOVA) test. The test yields a p-value of 0.03, signifying that the mean rate of return for at least one strategy differs significantly from another strategy with a 95% confidence level. Furthermore, this study uses Levene’s test to identify which datasets exhibit different means when compared to the benchmark strategy. Levene’s test, a statistical tool to check the homogeneity of variance, can determine whether Welch’s t-test or Student’s t-test should be employed to analyze the disparity in mean between two datasets. The result of Levene’s test on the benchmark and the five technical analysis algorithms indicate a pvalue of 0.00, which falls below the critical threshold value of 0.05 required to reject the null hypothesis that at least one pair of datasets possesses equal variance at a 95% confidence level. This p-value demonstrates that the variances of datasets statistically and significantly differ from the benchmark. Accordingly, Welch’s t-test, which requires a nonhomogeneous variance, is appropriate to determine

whether technical analysis strategies statistically significantly differ from the benchmark strategy.

Table 2. Results of Welch’s t-test on the Five Technical Analysis Strategies Compared to the Benchmark Technical Analysis Strategy

T-statistic

p-value

RSI

3.20

0.00

Bollinger-Band

3.65

0.00

MACD

1.79

0.07

MACD Breakout

1.30

0.20

Breakout

2.34

0.02

Table 2. summarizes the results of Welch’s t-test conducted on each technical analysis strategy. The pvalue for MACD and MACD Breakout are respectively 0.07 and 0.20, both over 0.05. The p-value of greater than 0.05 shows that the differences in means are statistically insignificant and hence the null hypothesis that the two datasets have unequal means cannot be rejected. Therefore, at a 95% confidence level, it is not possible to conclude that neither MACD Breakout nor MACD has a significant difference in mean compared to the benchmark. On the contrary, RSI, Bollinger-Band, and Breakout yield p-values of 0.00, 0.00, and 0.02, respectively, all below the 0.05 threshold. The corresponding t-statistics surpass the critical value of 1.96, providing substantial evidence to reject the null hypothesis and conclude that the mean difference is statistically significant. These findings validate that RSI, Bollinger-Band, and Breakout perform differently from the benchmark at a 95% confidence level. A plausible explanation for the resemblance between MACD and MACD Breakout and the benchmark is that the two technical analysis algorithms have low thresholds for buy signals and high thresholds for sell signals. This approach ensures that MACD and MACD Breakout hold stocks for long durations, aligning their respective price movements with those of benchmark. On the other hand, RSI and Bollinger-Bands both set extremely high thresholds for buy signals, leading to minimal engagement in the market, which contrasts with how the benchmark synchronizes to market price movements. The experiment results that highlight significant differences between the rate of returns for Breakout and the benchmark shed light on how the technical analysis algorithm liquidates all of its holdings at the end of business days.

3.2 Sentiment Analysis The goal of this study is to compare the variability of technical analysis performance based on different sentiments. As such, the study first outlines the qualifications for different sentiment categories and arranges the six trading strategies’ rates of returns accordingly. During the process of sentiment analysis, news headlines are quantitatively expressed into polarity scores between -1 to 1. For example, a title that reads “[Stock] expects [an] uptrend as its dividends double from the previous year” converts into a polarity score of 0.371, denoting a moderately neutral sentiment.

Figure 2. Distribution of 30-day Sentiment

This study establishes three distinct sentiment categories: negative, neutral, and positive. Negative sentiments encompass the lower one-third of all sentiments from the comprehensive 30-day sentiment data collected from this study. Neutral sentiments comprise the middle one-third of the sentiments within the same dataset. Similarly, positive sentiments represent the upper one-third of the sentiment distribution. This categorization is based on the quantity of data points, which may lead to criticism that the distribution captures overall sentiment trends rather than sentiments that are inherently negative, neutral, and positive. However, this study deems such an approach to be proper and necessary to account for the heavy concentration of 30-day sentiments around zero. Figure 2 illustrates the pronounced centralization of the 30-day sentiments’ propensity near a single point.

Based on the collected 30-day polarity scores, this study defines negative sentiments as polarity scores ranging from -1 to 0.0262, neutral sentiments as polarity scores ranging from 0.0262 to 0.0638, and positive sentiments as polarity scores ranging from 0.0638 to 1. Figure 3. Trading Strategy Performance for Each Sentiment

Table 3. Variances of Each Trading Strategies by Sentiments Sentiment

Benchmark

RSI

BollingerBand

MACD

MACD Breakout

Breakout

Negative

13.20

0.66

0.07

7.67

12.50

5.47

Neutral

26.45

0.72

0.07

16.58

21.17

7.98

Positive

22.72

1.08

0.02

12.92

18.60

6.49

Table 4. Average Rates of Returns for Each Trading Strategies by Sentiments Sentiment

Benchmark

RSI

BollingerBand

MACD

MACD Breakout

Breakout

Negative

100.74

100.01

100.04

100.10

99.71

100.10

Neutral

100.91

100.04

99.99

100.37

100.43

100.22

Positive

101.25

99.94

100.00

100.27

100.23

99.79

3.3 <Technical Analysis Rate of Return in Relation to Sentiments> The trading strategy results presented in Figure 3 highlights a direct relationship between sentiments and the benchmark performance; the more positive the sentiments were, the higher the performance it demonstrated. However, findings in Table 3 suggest that this observed trend is not consistent. The variances of the benchmark strategy under negative, neutral, and positive sentiments are measured at 13.20, 26.45, and 22.72, respectively. Comparing these three different values, one might conclude that positive sentiments elicit more reliable growth than negative and neutral sentiments. However, it is important to note that even among positive sentiments, there is still a significant level of variability indicated by the difference in variance. In terms of reliability, both RSI and Bollinger-Band performances demonstrate consistent and stable change. The RSI variances under negative, neutral, and positive sentiments are 0.66, 0.72, and 1.08, respectively. Even less, the Bollinger-Band variances respectively measure 0.07, 0.07, and 0.02. While the returns of RSI and Bollinger-Band generally exhibit stability, they do not guarantee abnormal returns. Figure 3 indicates that both technical analysis strategies generated average rates of returns near 100 under all sentiments. Still, the algorithms exhibit patterns in response to sentiments. For RSI, rates of returns under neutral sentiments generally show an upward fluctuation, while those under positive sentiments tend to fluctuate downwards. This results in RSI’s profitability being arranged in a descending order as neutral, negative, and positive. The profitability of rates of returns for BollingerBand, far less versatile to indicate any fluctuation, ranges from negative to positive to neutral. These findings suggest that the sentiment trends observed in both technical analysis strategies deviate from that of the benchmark. This underlines the importance of considering distinctive mechanisms of different technical analysis strategies in responding to price movements generated by incoming information trends. Contrary to the benchmark strategy, MACD, MACD Breakout, and Breakout generate lower but more stable returns. According to Table 4, the rates of returns for negative, neutral, and positive sentiments are as follows: MACD (100.10, 100.37, 100.27), MACD Breakout (99.71, 100.43, 100.23), and Breakout (100.10, 100.22, 99.79). The corresponding variances for these strategies are as follows: MACD (7.67, 16.58, 12.92), MACD Breakout (12.50, 21.17, 18.60), and Breakout (5.47, 7.98, 6.41). Further, they exhibit sentiment to rate of return trends different from that of the benchmark. For instance, MACD and MACD Breakout generated the greatest average return under neutral sentiments and the lowest average return under negative sentiments. Moreover, the average rate of returns for Breakout demonstrated strong performance under neutral sentiments but weak performance under positive sentiments. It is also noteworthy that both MACD Breakout and Breakout experience discernable declines when the sentiment reaches under 100%. Overall, four out of six trading strategies generate the most stable rates of returns under negative sentiments. Furthermore, neutral sentiments result in the highest return volatility for five out of six trading strategies. These two recurring patterns indicate that sentiments associated with information

influx greatly influence market behavior, subsequently impacting price movements and the corresponding technical analysis performances.

3.3.1 Technical Analysis Rate of Return in Relation to Sentiments Data Analysis This study employs Levene’s tests to assess the similarity of variance among trading strategy performances for each sentiment and trading strategy. The former evaluation examines the extent to which the five technical analysis performances vary over different sentiments. The latter underscores how the average rate of returns for each trading strategy differs based on sentiment patterns. Additionally, this study employs One-way ANOVA tests to determine whether the differences between the mean rates of returns for technical analysis strategies and the benchmark are statistically significant, considering each sentiment and trading strategy. If a positive response is obtained, a subsequent t-test is conducted to assess the significance of the mean difference between the benchmark and each technical analysis strategy.

Table 5. Results of Levene’s Test on Trading Performance Variance for Each Strategy by Sentiments Sentiment

F-statistic

p-value

Negative

70.07

0.00

Neutral

69.21

0.00

Positive

104.56

0.00

Table 5 presents the results of Levene’s test on trading performance for each sentiment, as categorized by sentiment. The p-values for all sentiments are below 0.05, rejecting the null hypothesis that one or more technical analysis strategy performance data share the same variance as the benchmark performance data at a 95% confidence level.

Table 6. Results of Levene’s Test on Trading Performance Variance for Each Sentiment by Trading Strategies Technical Analysis Strategy

F-statistic

p-value

Benchmark

5.18

0.01

RSI

0.00

1.00

Bollinger-Band

1.30

0.27

MACD

2.97

0.05

MACD Breakout

1.81

0.17

Breakout

0.71

0.50

Table 6 shows the results of Levene’s test on trading performance for each sentiment, categorized by trading strategies. It demonstrates that the variances for RSI, Bollinger-Band, MACD Breakout, and Breakout exceed the p-value of 0.05. This suggests that the behaviors of the said technical analysis strategies do not significantly differ across sentiments. Conversely, the variance for MACD does not exceed the p-value of 0.05. On this note, it could be concluded that the variances of MACD exhibit statistically significant differences at a 95% confidence interval.

Table 7. Results of One-way ANOVA test on trading performance means for each sentiment by sentiments Sentiment

F-statistic

p-value

Negative

2.22

0.05

Neutral

1.53

0.18

Positive

2.61

0.00

Table 7 demonstrates the results of the One-way ANOVA test on the mean values of technical analysis performance for each sentiment. Negative sentiments yield a respective p-value of 0.18, which is greater than 0.05. The results indicate that the mean rate of returns for technical analysis strategies did not significantly differ from the benchmark. Conversely, negative and positive sentiments produced a pvalues of 0.00 and 0.05, respectively, indicating a statistically significant difference between the performance of technical analysis strategies and the benchmark.

Table 8. Results of One-way ANOVA test on trading performance mean for each sentiment by trading strategies Technical Analysis Strategy

F-statistic

p-value

Benchmark

0.50

0.61

RSI

0.49

0.61

Bollinger-Band

1.84

0.16

MACD

0.22

0.80

MACD Breakout

1.07

0.34

Breakout

1.32

0.27

Table 8 summarizes the results of the One-way ANOVA test on trading performances for each sentiment based on a division of trading strategies. The p-values for all trading strategies are above 0.05, suggesting that the mean rate of return for each trading strategy does not statistically significantly differ across sentiments.

Table 9. Results of Welch’s t-test on trading performance means for each sentiment by for positive sentiments Technical Analysis Strategy

T-statistic

p-value

RSI

3.67

0.00

Bollinger-Band

3.59

0.00

MACD

2.25

0.03

MACD Breakout

2.18

0.03

Breakout

3.71

0.00

Elaborating on the conclusions drawn from the One-way ANOVA test documented in Table 7, this study employs t-tests to identify specific technical analysis strategies that generated statistically significant differences in means during positive sentiments. Since the rate of return variances for positive sentiments are essentially different across trading strategies, the t-tests operate in the form of a Welch’s t-test. The results in Table 9 reveal that all technical analysis strategies bear accountability for the overall p-value of 0.00 for positive sentiments, with none of them exceeding 0.05. This ultimately proves that the mean rate of return for all trading strategies significantly differs under the pretext of positive sentiments.

4. CONCLUSION This study analyzes the behaviors of technical analysis activities by categorizing market contexts based on its sentiment division. It observes the thirty-day rates of returns for the benchmark strategy as well as the five technical analysis strategies–Stochastic Relative Strength Index (RSI), Bollinger-Band, Moving Average Convergence/Divergence (MACD), MACD Breakout, and Volatility Breakout (Breakout). These analyses were conducted on all 30 DJIA stocks in the year 2016. The study then employs various statistical tests to assess the means and variances of the strategies’ performances in relation to market sentiments. Based on the empirical evidence, this study derives several conclusions. This study provides insights into the relationship between technical indicator algorithms and market sentiments, suggesting that technical analysis strategies exhibit varying performances based on the prevailing market sentiments. The contrast was reflected in their variances, which refers to the differences in their performances. It establishes that the mean returns of technical analysis do not significantly deviate from the benchmark under neutral sentiments, but vary significantly under negative and positive sentiments. Additionally, the study concludes that the benchmark and MACD strategies demonstrate contrasting behaviors in response to prevailing information trends, which is reflected in their variances. While this study contributes to facilitating the understanding of technical analysis and market sentiments, it also acknowledges that relying solely on quantitative metrics like price and volume data may not always be sufficient in predicting market trends accurately. Thus, further research could focus on integrating the information with technical indicator algorithms to enhance its capability to predict market trends more accurately and generate reliable alpha. This could be achieved by analyzing how qualitative and quantitative metrics govern technical analysis activities and identifying ways to deconstruct information to make it more useful in predicting market trends. For example, changes in government policy or corporate earnings reports can impact market behavior, but by incorporating both quantitative and qualitative analysis, investors can gain a more comprehensive

understanding of the market and make more informed investment decisions. Additionally, exploring how market inefficiency relates to the effectiveness of informational supplements in technical indicator algorithms could help identify the market contexts in which such supplements are most effective in invigorating alpha generation. Consequently, further research could explore how to deconstruct information to make it more useful in predicting market trends, ultimately leading to better investment decisions and outcomes for investors. In conclusion, this study delves into the essence of the Efficient Market Hypothesis and technical indicator algorithms to understand how information trends may supplement the profitability of technical analysis. The findings and conclusions of this study offer new perspectives that could guide future research and improve the reliability of alpha generation.

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The Solar Energy Landscape and the Paris Agreement: China and the United States Author 1

Full Name

: Cha, Yejoo

(Last Name, First Name)

School Name

: Korean International Christian School

ABSTRACT: This paper lays out the national efforts that the United States and China have taken to mitigate the effects of climate change, more specifically, in the solar power sector and with the Paris Agreement. One of the most significant and urgent global issues as of now is climate change. The two nations that this paper analyzes are the most dominant leaders of both climate change alleviation and exacerbation. Therefore, how each country tackles renewable energy development and international cooperation is vital knowledge that is needed to enhance global sustainability. This study uses secondary literature, government documents, and reports to give the reader a good understanding of the US’ and China’s solar energy progress since 2017 and the Paris Agreement implementation since 2015. China has struggled with the problem of subsidy gaps and has turned to grid parity while the US has decided to show more dominance in CSP technology rather than PV. Over the years, both countries have shown hesitance in participating in the Paris Agreement, but recent evidence shows that they are active and cooperative. This literature review of the existing secondary literature, government documents, energy agency reviews, news articles, and organization briefs will serve to guide future research needed to form guidelines for other countries in developing renewable energy and supporting international climate agreements.

KEYWORDS: carbon emission, renewable energy, solar energy, photovoltaics, China, United States, Paris Agreement, climate change

1. INTRODUCTION Climate change is a severe global issue that is partly driven by the carbon emissions that societies release into the air. Of these communities, China and the United States are the greatest carbon emission emitting bodies in the world. A research paper on photovoltaics presents that in 2019 China’s percentage of global heat-trapping gas emissions tallied up to about 27 percent with the US as runner-up accounting for 13 percent [1]. Therefore the continued environmental efforts made by these two countries take on a big role in the global combat against climate change. One of the strategies that nations have implemented in order to reduce their carbon emissions is decreasing the national reliance on nonrenewable energy sources. This paper takes a deeper look at the renewable energy development process of solar energy of the two major market leaders, China and the United States. As this topic is too complex to identify a causal mechanism, we will simply be describing the two different cases. For the same reason, only one type of renewable energy, solar energy, will be analyzed. When addressing climate change there are a myriad of factors that countries have to consider. Even within the renewable energy factor, there are different forms of energy that have their own advantages and disadvantages. In order to keep this paper as concise and specific as possible, we will focus on the variable of solar energy. Solar energy is a completely renewable energy source that can be harvested for a long, stable period. Unlike other renewables which have a limit to how much they can offer, the sun can be utilized without concern [2]. Technology in this energy sector can be divided into (1)concentrating solar power technologies and (2)solar photovoltaic(PV) cells. Concentrating solar power technology is the means of gathering sunlight while solar photovoltaic cells function to convert sunlight to electricity [3]. Aside from renewable energy development, international involvement is another important component that a country must consider in relation to the climate crisis. The Paris Agreement is a prominent international treaty and one that will be analyzed in this paper to show the efforts that the US and China have made to mitigate the impacts of climate change. While the section on solar power describes each nation’s solar energy landscape individually, the section on international involvement is constructed with more comparative language. The two nations, China and the United States have fluctuated in their solar industrial success as well as their global treaty participation but, both countries have demonstrated effective performance in the climate change combat through solar energy development and involvement in the Paris Agreement.

2. CHINA China is a global leader in the solar power market being first place in the world in solar energy generation [4]. In 2017, the solar power capacity was 130.06 gigawatts(GW) which then rose to 205GW in 2019 becoming a nation with nearly three times the capacity of other countries [5]. Additionally, China firms make up 80% of the world’s top 10 solar cells and modules suppliers [6]. The nation saw a bit of a drop in power generation during the beginning of 2020 due to COVID-19 [7] but soon recovered with a solar energy generation capacity of 392.61GW in 2022 [8]. These statistics demonstrate the rapid development that China went through to eventually take its current dominant position. However, this speedy progression did not come without its problems. Just as the installed capacity of solar energy has increased, the government-provided subsidies have also increased greatly [9]. This created a subsidy gap that made it harder to support other solar energy projects [10]. In 2017, the cumulative financial gap was 45.5 billion Chinese yuan [11] which expanded to over 60 billion yuan in 2018 [12]. At this point in time, governments decided to focus on reducing the severity of this subsidy gap. One of the notable efforts was the “531” policy. Apart from reducing the subsidy, this policy aimed

to improve the supply-demand mismatch situation, and allow for the development of advanced solar technology and PV generation projects [13]. At first, the reaction to the notice of the policy regulations was not optimistic as there had been set expectations for a subsidies reduction policy but they ended up not being aligned with the “531” policy [14]. The subsidy reduction came earlier and required a bigger reduction than the predictions so the policy impacts on the solar energy industry were harmful [15]. Despite the hesitation, the “531” policy was able to bring the subsidy from 0.36 CNY/kWh(kilowatt hour) to 0.32 CNY/kWh [16]. In addition to this, national quotas were lowered, prices in relation to PV energy fell, and the country’s original goal of reaching grid parity was achieved early in a few parts of China [17]. Later in 2019, an improved policy called “Notice of the National Development and Reform Commission on Relevant Issues Concerning Improving the On-grid Tariff Mechanism for Photovoltaic Power Generation” was established to further narrow the subsidy gap [18]. A central part of China’s perspective on its solar industry development is grid parity. A study defines grid parity as the cost of electricity obtained from PV energy generation and the conventional energy power generation reaching equilibrium [19]. Grid parity has proved to bring a lot of benefits. Some of these benefits are the promotion of solar energy technology progress, lowering of solar power cost, reducing PV energy policy cost, improving China’s solar energy market competitiveness, and encouraging rapid energy transition [20]. After having looked at multiple pieces of secondary literature, grid parity appears to have been a crucial aim in the past and for the future. Accordingly, efforts to bring other regions of China to grid parity may be prioritized and put into action. Aside from grid parity, there was another significant aspect that was proposed in 2017 [21]. In July, a system called the “Green Electricity Certificate”(GEC) was established by the China Renewable Energy Engineering Institute [22]. This mechanism is a way for businesses as well as individuals to purchase renewable energy and derive the environmental benefits that come with energy generation [23]. The GEC system in China is also able to accommodate energy attribute certificates, issue greenhouse gas offsets [24], supply economic incentives, bring down renewable energy costs, and enhance project profit [25]. In the solar energy industry, photovoltaic projects that receive a Feed-in-Tariff and solar plants that are connected to large-scale grids can receive GECs [26]. The revenues from the GECs that are sold can then be used by the industry to offset a portion of the solar power generation costs [27]. As of now, the GEC is the only certificate system that China has in place although new systems may be designed and implemented to prevent overconsumption of renewable energy [28]. In the same year of 2017, the GEC system was able to issue 8 million GECs in wind and solar electricity [29]. China has been consistently active in the solar energy industry by not only enhancing its market value but also implementing impactful projects. Having been operating since 2017, the PV power project for the 2022 Olympic Winter Games’ welcome corridor in Beijing is a fit example to show consistent maintenance of technology. It has a total installed capacity of 500MW(megawatts) and supplies 635 million kWh of electricity every year [30]. The project also promotes PV agriculture and forestry as it shows urban and rural area development [31]. In February 2022, during the Beijing Winter Olympics, all 26 venues were powered by green electricity [32]. To provide this power, China also constructed several PV energy projects along with other energy source projects in different regions including Beijing and Zhangjiakou to transmit green energy [33]. This project served so much more than the actual Olympics. For example, a significant rise in the share of clean energy consumption by Beijing and nearby regions was observed [34]. Additionally, through this project, China practiced real-life implementation of large-scale transmission, grid connection, and clean energy uptake [35]. The country was able to represent great prowess in clean energy technology and environmental initiative. The global position of China in the solar energy sector is still sustained in 2023. China is home to the world’s largest hybrid solar-hydro power plant which began operation in June [36]. Located in the eastern Tibetan Plateau, the plant has an installed capacity of 1GW of solar panels [37]. The plant

generates 2 billion kWh of electricity every year and is set to supply green energy to 100 million households [38]. The continuously developing nature of the solar energy industry in China demonstrates that despite its issue with the subsidy gap, the nation continues to move forward with active innovation and environmental interest.

3. THE UNITED STATES The United States is runner-up after China for solar electricity generation and despite the sizable gap with China [39], it still holds a major position in the solar energy industry. America’s solar energy development has progressed at extreme rates. In 2017, the PV capacity was 52GW and PV generation was 67.4 TWh(terawatt hours) [40]. These numbers in 2021 grew to a capacity level of 118.5GW and PV generation reached 146.2TWh [41]. As the solar energy sector in the US progressed, the costs of solar power also decreased at a quick pace. The achieved cost target in 2017 was 0.06 USD kWh and it was accomplished three years ahead of schedule [42]. This surprising achievement caused the Department of Energy to set new 2030 utility solar energy targets at 0.03/kWh [43]. Although most of the time lowering energy costs are seen as a goal and a means of making an energy source competitive, in 2018, a problem with solar cell imports had to be addressed. The US solar power industry depends a lot on solar cell and panel imports [44]. This increasing reliance caused domestic producers to suffer and propose solutions to the government [45]. Hearing these complaints, the government set out a press release informing the decision to implement safeguard tariffs on PV cell imports [46] according to Section 201 of the Trade Act of 1974 [47]. The tariffs were designed to stay applicable for four years [48]. They would start in 2018 and decrease from 30% in the first year by 5% each year after that with every year having a 2.5GW(gigawatt) exemption [49]. Due to the heavy reliance on PV cell and panel imports, a rise in prices was predicted [50] but either due to its short-term nature or lack of macro impact, renewable energy consumption levels as well as electricity access levels have no significant change [51]. This policy was the most direct form of trade action that impacted the renewable energy sector [52]. In line with what was previously mentioned, the US’ solar PV technology has made impressive progress over the past few years [53]. Near the end of 2017, 590 PV projects on a utility scale were reported to be in commercial operation and 146 of these were successfully operated in the same year [54]. Based on this data it is clear that the PV technology progress and practice the US has performed is proficient. However, while China takes first place in most renewable power technology industries, the United States is ahead in concentrating solar power technologies(CSP) [55]. CSP like PV technology is a type of solar power technology except it has the capacity for heat energy storage which can later be converted into electricity [56]. CSP plants that include the thermal storage capacity function can continue to generate electricity on days without direct sunlight [57]. The CSP data in comparison to the PV data tells us that CSP technology is less developed and explored. The CSP capacity in 2017 was 1.8GW and generation levels were at 3.6 TWh [58]. It can also be observed that CSP progress has been relatively slow as the data in 2021 shows 1.5GW for capacity and 3.2TWh for generation [59]. The CSP plants in the United States have mostly been started in the year of 2014 or before [60]. There are no recorded CSP plants that have been started since 2017 [61]. Nonetheless, this fact should not be seen as a pause in technological progression as other factors to the lack of new CSP plants may exist. While there is no notable development in CSP statistics and rather a small decline, the United States is still a global leader in CSP plant building and operation with over 26 projects implemented worldwide [62]. Hopeful projections have also been made estimating that CSP plants comprising a total capacity of 118GW could be implemented in 2030 and in 2050, this capacity may rise to 1504GW [63].

4. PARIS AGREEMENT The Paris Agreement is an international treaty that is known as the first successful agreement to legally bind all nations together to mitigate the effects of climate change [64]. This treaty was formed under the leadership and active contribution of China and the United States [65] at the Paris Climate Summit in 2015 [66]. The product of the summit created by 195 countries consisted of a 2 degrees Celsius limit on global warming and the overarching goal to bring down temperatures to 1.5 degrees Celsius [67]. Both the nation of China and the United States jointly signed the agreement on April 22, 2016, in an effort to put the agreement into action as fast as possible [68]. Despite having acted as a model to the rest of the world, the US’ participation in the Paris Agreement did not last for long. As Donald Trump became president in 2017, the decision to withdraw from the Paris Agreement was implemented [69]. Not only did this act of “stepping out” received strong backlash from both the US and foreign bodies but the decision also proved to be unbeneficial and in contrast a hindrance to the US’ environmental performance [70]. Trump’s skepticism of global warming and tendency to support fossil fuel industries put the country in a position where achievement of environmental goals seemed improbable, the guarantee for developed countries to be provided with climate aid was not sustained and other countries like China could exert global dominance [71]. Meanwhile, China has shown to be comparatively more active in global cooperation. Before the Paris talks, China was very wary of foreign cooperation and unwilling to meet the expectations that the world had in order to combat climate change [72]. Consequently, China was seen as an obstacle slowing down global progress with the climate crisis [73]. It was only until the years 2014 and 2015 that China started to receive recognition for its influential efforts as shown in the formation of the Paris Agreement [74]. At the UN office of Geneva in 2017, President Xi Jinping further emphasized the importance with which China held the Paris Agreement by highlighting the continuous maintenance of the aims within the agreement, international cooperation, and China’s intention to fulfill its climate responsibility [75]. China demonstrated long-term progression under the Paris Agreement at the Climate Ambition Summit in 2020 through the president’s affirmation of ongoing climate mitigation with policies and governmental measures [76]. Once considered a global adversity in the climate movement, China has now found its place among other international leaders at the front of the lines. The world’s former singular leader in climate change, the United States began to recover its past intensity in global warming mitigation with the Biden administration in 2021 [77]. Upon coming into office, President Joe Biden brought the US back into the Paris Agreement and steadied the focus back on multilateral relations [78]. In 2021 at the COP26, Biden announced the new perspective with which the US would face the climate crisis. The UN Climate Change Conference that took place in Glasgow gathered a total of 120 world leaders and more than 40,000 participants to enhance the application of the Paris Agreement [79]. In his speech, Biden encouraged perseverance with the 1.5 degrees Celsius limitation and explained the actions in greenhouse gas emissions, renewable energy, and energy market occupations that the US was planning to take [80]. With the US’ intention to become a universal example along with China’s increasing dominance, the two nations show implications to do their part in fighting climate change as the world’s largest emitters.

5. CONCLUSION In conclusion, the United States and China, as much as they are largely dependent on nonrenewable resources and account for a great portion of global carbon emissions, show continuous effort and progress in climate change mitigation. China despite its problem with subsidies, solar energy technological development, and economic mechanisms has been implemented consistently. Unlike before, China has taken lengths to strengthen its multilateral relations corresponding to solar power

progression and climate change. Not only has it made itself an active international partner but it also has grown to be a vital leader in the climate crisis. In contrast, the United States has always shown itself as the major power leading climate change cooperation however in some cases the government was unwilling to participate in international agreements or withdrew as can be seen with the Paris Agreement. This instability in prioritizing international collaboration and well-being may be a reason for the US’ comparatively slow development in solar energy. Further research must be performed in order to understand the factors behind China’s rapid success in not only the solar energy market but the entire renewable energy industry. Future studies must also analyze why the US’ efforts are not as efficient in progressing their development. These gaps must be answered so that other countries may use the US’ or China’s strategies to enhance their renewable energy security and diversity. Another crucial area that must be addressed is China’s recent announcement on its intention to strive toward its climate mitigation targets at its own pace without foreign interference [81]. This act can be seen as turning away from the international goals that the Paris Agreement has set [82] and therefore could mean the repetition of China’s past individualistic, isolated character. Such a situation would slow down the world’s progress in lowering global temperatures and raise the difficulty in establishing stable partnerships with China. As most of the research used to describe China’s willingness to join international environmental efforts was taken from government remarks, there is a need to examine whether these announcements or aims on climate change are followed up with action and whether that action is sufficient.

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Chinese Elite Politics after 20th Party Congress: Emphasis on Xi Jinping’s leadership system Author 1

Full Name

Choi, Jayun

Cheongshim International Academy

(Last Name, First Name)

School Name

: : : :

ABSTRACT: Since assuming office as the fifth-generation leader in 2013, President Xi Jinping has garnered significant attention from global media and academicians, who have widely speculated on his potential to emerge as a formidable leader and consolidate the authority of the Central Communist Party of China. It is anticipated that President Xi Jinping, who has solidified his authority through a series of power consolidation measures, will deviate from these norms and embark on a trajectory of prolonged tenure, which ceased to exist subsequent to the era of Mao Zedong. Numerous assessments and arguments arise pertaining to the establishment of a system like to the Mao Zedong era by President Xi Jinping. The essay endeavors to delineate the attributes of the Xi Jinping administration through an examination of the process of consolidating President Xi Jinping's authority and to draw a comparison between the subject under examination and Mao Zedong, the sole individual in the annals of contemporary China who successfully built and implemented a system of autocratic governance. Presently, there exists an examination of the Xi Jinping era in isolation, as well as a comparative analysis vis-à-vis the preceding Hu Jintao era. Nevertheless, the topic of centralized control by a single individual during the Mao Zedong era has not been extensively examined in existing publications. Hence, the present discourse endeavors to elucidate the distinct attributes and parallels by means of juxtaposing the processes of power consolidation throughout the Mao Zedong era and the tenure of Xi Jinping. The purpose of this analysis is to compare the policy implementation methods of two regimes, specifically focusing on the birth policies enacted by Mao Zedong and Xi Jinping as these policies have significant implications for demographic, social, economic, and political dimensions of Chinese governance. Through this analysis, this study provides a distinct perspective by examining the expanded collective leadership structure under Xi Jinping's term following the 19th Party Congress, in comparison to the authoritarian rule of Mao Zedong.

KEYWORDS: Xi Jinping; Elite Political System; Centralized leadership system; Birth Rate; ChinaSouth Korea relation; 20th Party congress

INTRODUCTIONG Xi Jinping, the esteemed individual who assumed the position of general secretary during the esteemed 18th Congress of the esteemed Communist Party of China in 2012, remarkably consolidated his esteemed authority at an accelerated pace that surpassed the esteemed expectations of the populace. The frequency with which his numerous official positions are cited is a notable illustration of this phenomenon. In January 2017, it was noted that Xi Jinping occupied a comprehensive range of 12 distinct positions. In addition to the positions stipulated by the Constitution and the Party Constitution, such as the General Secretary of the Communist Party, the Central Military Commission, and the State President, various leadership groups and committees are encompassed within the organizational structure. In contrast to his predecessors, Jiang Zemin and Hu Jintao, Xi Jinping's leadership ideology was explicitly named and implemented at the onset of his second term, deviating from the customary practice of introducing such ideology after the second term in power. This departure from the convention indicates a heightened level of consolidation within Xi Jinping's regime. The consolidation of power under Xi Jinping is further evidenced by the absence of a clear path to the next leader after Xi Jinping in the composition of the 19th Party Congress Standing Committee, notwithstanding the transparency with which Hu Jintao and Xi Jinping were appointed general secretary. Therefore, in 2014, Xi Jinping's third year in power, some scholars and media cautiously stated that collaborative leadership, which had been maintained for the past 20 years, was collapsing and that Xi Jinping's oneman rule was emerging. Yet, many academics continue to dispute the validity of this claim.G G However, the notion that Xi Jinping's one-man rule is forming poses concerns considering there is currently a need for legislation outlining what one-man control entails. The transition from collective leadership to a one-man rule significantly affects China's elite politics. Hence, to engage in a comprehensive discourse on this matter, it is imperative to begin by elucidating the one-man rule's precise definitions and connotations. Only subsequent analysis will assess whether the dynamics of elite politics under the Xi Jinping administration are indeed transitioning towards a system characterized by concentrated power in the hands of a single individual. G G This research paper explores the potential similarities between Xi Jinping and Mao Zedong, which have been brought to attention due to Xi Jinping's efforts in consolidating the system following the 19th Party Congress. During the Mao Zedong era, a notable concentration of power existed in the hands of an individual known as Mao Zedong. This concentration of power was further solidified by the emergence of Xi Jinping, which deviated from the practices observed under previous key leaders after the 19th Party Congress. In light of the ongoing discourse surrounding Xi Jinping's second term system, it becomes imperative to undertake a comprehensive analysis of the political framework established by Xi Jinping subsequent to the 19th Party Congress. This study endeavors to undertake a comparative analysis of the governance systems implemented by Mao Zedong and Xi Jinping, explicitly emphasizing the highly debated childbirth policy in contemporary China. G G This study will examine the elite political systems Xi Jinping, and Mao Zedong implemented. This inquiry aims to gain a comprehensive understanding of the one-man rule system implemented by Mao Zedong, as well as the first and second collective leadership systems introduced by Xi Jinping. Subsequently, three distinct criteria that differentiate these two esteemed systems will be examined. A comprehensive comparison and analysis of the two systems will be conducted in light of the three criteria mentioned above. An examination will scrutinize the disparities in childbirth policies implemented by the two respective systems. The paper aims to ascertain whether the disparities in the political governance framework, as outlined earlier, are distinctly manifested in the policy measures implemented. In light of the investigation above, the paper shall now provide a concise overview of the research findings. The findings of this study will substantiate the notion that the dynamics of elite politics observed during the tenure of Xi Jinping exhibit a more remarkable resemblance to the era of collective leadership witnessed in the post-Jiang Zemin period, as opposed to the autocratic governance model characterized by Mao Zedong's singular rule.G

RESEARCH METHOD Two distinct methodologies can be employed to elucidate the concept of one-man rule within the realm of elite politics. The comparative socialist approach is one of the theoretical frameworks employed to analyze socioeconomic systems. The present methodology entails the identification of the distinctive attributes inherent in an individual's body of work through synthesizing the salient features exhibited by the totalitarian regime led by Joseph Stalin in the Soviet Union. Numerous scholarly investigations have been undertaken to examine the subject, and it is widely acknowledged within academic discourse that totalitarianism serves as a prevailing framework to characterize Stalin's autocratic rule. China during the era of Mao Zedong can indeed be categorized as a form of totalitarian regime. However, there is a bound to understanding the features of authoritarian one-man rule as it attributes to the macrolevel nature of the concept in question, which encompasses the realm of elite politics and the broader political system as a whole. G G The alternative method under consideration is the historical approach. The present discourse aims to elucidate a particular modality of governance known as a one-man rule, which has surfaced as a distinctive variant within the broader spectrum of elite politics in the contemporary Chinese political landscape. Upon retrospective analysis of China's historical trajectory, three predominant forms of elite politics have emerged and persisted throughout the nation's past. The initial consideration pertains to Mao Zedong's one-man rule, characterized by his authoritative rule. This particular form of political governance can be classified as an exemplar of elite politics prevalent during the Mao era, from 1949 to 1976. The second principle pertains to the senior directive of the revolutionary elders, with a particular focus on Deng Xiaoping. The third phase of the post-Deng era encompasses the leadership tenures of Jiang Zemin, Hu Jintao, and Xi Jinping. One area of focus for comprehensive analysis lies in examining Mao's one-man rule, which presents an opportunity to gain insights into the distinctive features of such a form of governance.G G The present study aims to employ an alternative methodology. In order to achieve this objective, a comprehensive analysis will be conducted to examine the specific attributes associated with the phenomenon of autocratic governance during the Mao Zedong era. As evidenced by prior research, Mao's tenure as chief leader allowed him to wield his authority with considerable autonomy and discretion in various domains, including policymaking, personnel appointments, selection of successors, and mobilization of military forces. In the given scenario, the individual in question demonstrated the capacity to convene significant gatherings aimed at deliberating upon and potentially modifying the ideological stance or course of action adopted by the Communist Party. The individual in question can exercise discretion in selecting or revoking the appointment of their designated successor. Mao Zedong served as the paramount leader of a political regime characterized by an unparalleled level of dominance that remained unchallenged by any opposing forces. Henceforth, through a comprehensive examination of Mao's autocratic governance, one can gain insights into the essence of one-man rule within elite politics. G G The present study employs qualitative synthesis and policy analysis as the chosen methodologies for data acquisition. The primary aim of this policy analysis is to offer a more comprehensive comprehension of the nature and progression of China's birth policy, specifically focusing on the perspective of an elite political system. The policy documents employed in this study comprise subsequent iterations that have undergone analysis and publicly accessible versions that do not require explicit permission for their utilization in research endeavors. In pursuit of its stated objectives, this study examined the keywords employed within the pertinent policy discourse. The identified keywords include: "19th Party Congress," "fertility rate," "Xi Jinping," "economic instability," "collective leadership system," "birth policy," and "elite politics." Thus, this study has compiled a comprehensive corpus of over 70 secondary sources on relevant subject matters, alongside a curated selection of 5 policies explicitly addressing the domain of childbirth and the data collection period encompassed the historical period spanning from the Mao Zedong era to Xi Jinping's second term. The primary focus of the study was on data gathered between 2017 and 2022, with particular emphasis on the post-19th Party

Congress period. Following the conclusion of this phase of data collection, an extensive analysis was undertaken to examine the prominent political patterns in China. This examination involved meticulous scrutiny of the political framework that encompasses the period from Mao Zedong's era to the initial term of Xi Jinping. In pursuit of obtaining impartial information, a comprehensive examination was undertaken to scrutinize the diverse methodologies employed by scholars from various nations in analyzing political trends.G G G

THE TRENDS IN ELITE POLITOCS IN CHINA G 1. The one-man rule of Mao Zedong's eraG The political landscape during the Mao Zedong era is distinguished by the prominent feature of Mao Zedong's autocratic governance, which is often referred to as one-man rule. During his reign, Mao Zedong effectively wielded autonomous control over various aspects of governance, including policymaking, personnel appointments, succession planning, and military mobilization. Nevertheless, Mao's tenure as a leader was characterized by a complex and multifaceted nature, and it would be inaccurate to categorize his rule solely as that of a dictator. During the period spanning from the establishment of the People's Republic of China in 1949 to the initiation of the Great Leap Forward Movement in 1958, Mao Zedong effectively wielded his political power by engaging in consultative processes with his comrades in order to deliberate and make decisions on significant matters. Mao, however, can be characterized as a dictator who held power from 1958 until his demise in 1976. Mao Zedong's dominant position in the political landscape remained unaltered; however, there was a discernible shift in how he wielded his authority. Specifically, Mao transitioned from employing a consultative approach to governance to adopting a more autocratic leadership style. G G Initially, the prominent Chinese leader Mao Zedong effectively consolidated political power by leveraging his charismatic authority. Upon the establishment of the People's Republic of China in October 1949, Mao Zedong assumed the positions of chairman of the Communist Party, government, and military. This consolidation of power solidified his status as the nation's preeminent revolutionary leader and founding father. Following the demise of Joseph Stalin in 1953, the international landscape underwent a significant shift as the absence of a prominent socialist figure capable of exerting a restraining influence on Mao Zedong's authority became apparent. G G The consolidation of Mao Zedong's authority can be attributed to the recognition bestowed upon him by fellow political leaders and the general populace, who acknowledged his significant contributions to the revolutionary cause and the subsequent establishment of the state. Mao Zedong, the Chinese Communist leader, established a dominant position within the party and society by effectively harnessing charismatic legitimacy. Furthermore, procedural legitimacy was also a viable option. The Communist Party held an expanded meeting of the Politburo on March 20, 1943, which confirmed the provision that the chairman would have the ultimate say on matters to be discussed during the clerk's meeting. In turn, the esteemed secretary general, Mao Zedong, was vested with the ultimate authority to make official decisions. G G The exercise of Mao Zedong's power has been conducted in a manner characterized by arbitrariness. There are claims that Mao Zedong referred to himself as a combination of Marx, the renowned philosopher and economist, and the emperor. The emergence of this phenomenon became prominent with the initiation of the Great Leap Forward Movement in 1958. Since approximately 1958, Mao reportedly remained in the provinces instead of attending the Politburo meeting in Beijing, issuing directives to the Politburo, and receiving reports on the meeting's outcomes. Mao, during the year 1958, allocated a significant portion of his time, ranging from approximately one-third to one-half of a year, away from the city of Beijing. There is mention of an informal entity known as the Central Working Party purportedly assuming the role typically fulfilled by official entities like the Central Committee. A series of 27 central operational conferences occurred between 1958 and 2003. Notably, the Mao

period from 1958 to 1976 constituted a significant majority of these conferences, amounting to approximately 77.8 percent of the overall count. On average, these conferences occurred 1.2 times per year.G G Consequently, the Communist Party's National Congress (Party Conference), the organization with the most power stipulated by the Party Constitution, and the Central Committee have become nominal entities. The 9th Party Congress, which took place in 1969, was held approximately 13 years subsequent to the convening of the 8th Party Congress in 1956. The Central Committee convened 12 times, with an average frequency of once per year, during the eighth period of the Communist Party from 1956 to 1968. However, the frequency of Central Committee meetings decreased significantly during the subsequent ninth period (1969-1972), with only two meetings held on average, equivalent to 0.5 times per year. Similarly, during the tenth period (1973-1977), the Central Committee convened three times, with an average frequency of 0.4 times yearly.G G The justification for Mao Zedong's singular leadership within the Communist Party was predicated upon implementing what has come to be known as the 'one-two-term system .'The establishment of the system in question was formally ratified during the proceedings of the eighth Communist Party Congress in the year 1956. Mao Zedong voluntarily relinquished his position for a second term and assumed responsibility solely for critical policies. Consequently, a division of labor system materialized, wherein other leaders assumed frontline roles and responsibility for the ruling party's day-to-day operations and government agencies. In the cohort of inaugural leaders, Liu Xiaoqi assumed the pivotal role of overseeing the political bureau of the Communist Party.G G On the other hand, Deng Xiaoping assumed the responsibility of leading the Communist Party's secretariat. Zhou Enlai, a prominent figure, was entrusted with the task of heading the government. Lastly, Chen Yun was entrusted with the crucial responsibility of overseeing the economy. The operational oversight of the People's Liberation Army (PLA) during the specified period was primarily attributed to the influential leadership of Mao Zedong. Mao's direct guidance was facilitated through the platform of the Pyeongdehui, a critical political organ within the Chinese Communist Party. Subsequently, following the Lushan Society incident in 1959, the responsibility of overseeing the PLA was assumed by Lin Biao, who continued to provide strategic direction to the armed forces. Multiple transformations occurred during the epoch under Mao's governance, characterized by a political paradigm wherein authority was centralized around the persona of Mao Zedong. G G The Xi Jinping era, which commenced in 2012 and continues to the present day, has exhibited discernible variations in elite politics compared to the preceding Jiang Zemin/Hu Jintao period. In essence, various phenomena have been observed, including the concentration of power within the central and general secretaries of the Communist Party, the reinforcement of control mechanisms within the party, the promotion of personal adulation, and the reinforcement of the leadership group. The subsequent consequence of this development was the gradual erosion of the collective leadership structure.G

G 2. Collective Leadership system of Xi Jinping era The collective leadership system can be categorized into two distinct types. The initial category is commonly referred to as the decentralized type. This category encompasses the initial tenure of power (1992-1997) in the context of Jiang Zemin and the complete duration (2002-2012) in the context of Hu Jintao. The second type under consideration is commonly referred to as the centralized type. The subsequent phase of Jiang Zemin's tenure, spanning from 1997 to 2002, as well as the entirety of the Xi Jinping era, can be categorized within this classification. The criterion utilized to differentiate between decentralized and ruling types lies in the extent of power concentration. In simpler terms, the criterion for dividing collective guidance lies in the extent of power concentration on individual supreme leaders.

This is primarily seen in the actual political process as a power dynamic between the Communist Party's general secretary and the Standing Committee of the Political Bureau.G G The phenomenon of collective leadership observed during the period of Xi Jinping's governance serves as a notable exemplification of a particular form of ruling. The Xi Jinping Power has been firmly established by Xi Jinping. During the establishment of the Jaffa forces, Xi Jinping exhibited distinct characteristics that set him apart from his predecessors. He successfully dismantled the existing factional system, which included the Gang of Four, Princeling, and Shanghai Bang. He assembled the necessary support forces to bolster the power base by employing competent individuals directly or indirectly related to him. This was a strategy that accounted for both justification and practicability. It appeared to adhere to the Communist Party's no faction tenet by expressing no preference for any one faction over another in terms of rationale. This made it feasible to optimize human resource utilization by adopting a selection process that prioritized individuals with demonstrated skills, irrespective of their affiliations or factions.G G Furthermore, Xi Jinping, the current General Secretary of the Communist Party of China, has implemented a significant initiative by establishing a prominent leadership group within the party's framework. This strategic move by Jinping aims to consolidate and strengthen the party's governance structure, thereby enhancing its ability to govern and lead the nation effectively. The military demonstrated a remarkable capacity for comprehensive and systematic guidance. To promote comprehensive reform, he established numerous leadership groups, assuming responsibility for himself as a leader or manager and adding Jaffa forces to crucial posts. This was the antithesis of Mao Zedong's style of government. The prominent Chinese leader Mao Zedong implemented a political framework known as the one-two-term system, which aimed to streamline governance and prioritize macro-level and long-term strategic endeavors over day-to-day operational tasks. However, the one-two-term system ultimately fell short, leading to anarchy in elite politics. Using this as an insight, Xi Jinping instituted a new leadership system in which he directly oversaw vital areas.G G

G COMPARISON OF MAO ZEDONG AND XI JINPING’S ELITE POLITICAL SYSTEM 1. Power source and power concentration The primary criterion utilized in the differentiation of China's elite politics pertains to identifying power sources and assessing power concentration. The initial criterion pertains to the foundational basis upon which the exercise of power by the most prominent political elite is established, as well as the degree of concentration of power within said political elites. In the context of the one-man rule of Mao and Deng Xiaoping, it is observed that revolutionary elders primarily wielded political power. These individuals, who held significant influence, could exert their authority based on their charismatic appeal. This appeal was primarily derived from the reputation and personal networks these esteemed leaders and founding fathers established. The power source utilized by the individuals in question can be described as personal authority. Hence, the official position held by individuals did not constitute a crucial factor in exerting power. G G On the other hand, under collective leadership system, Jiang Zemin, Hu Jintao, and Xi Jinping were able to ascend to the position of supreme leaders by winning the positions of Communist Party general secretary, state president, and president of the Central Military Commission as required by the Constitution. The primary determinants of power were derived from individuals' official positions, which granted them a certain level of authority within the institutional framework. Hence, in the event of their removal from their respective official positions, individuals experience a significant decline in their overall influence and authority.G G

The one-man rule was a privileged political system during the Mao Zedong era with an intense concentration of authority. Similar to the emperor of the traditional era, Mao Zedong possessed the ability to exert authority arbitrarily through the consolidation of policy-making, personnel, and military control. This was achieved by disregarding numerous regulations set forth by the Communist Party and state agencies. Indeed, during Mao Zedong's leadership, a notable allocation of powers was bestowed upon the Communist Party and other political elites responsible for overseeing state agencies. Liu Xiaochi, for instance, could exercise certain powers in daily affairs. In contrast, Deng Xiaoping was in charge of the Central Politburo, Zhou Enlai was in charge of the State Council, Chen Yun was in charge of the economy, and Feng Dehuai and Lin Biao were in charge of the military. However, he was not authorized to make significant policy or personnel decisions and had to follow Mao's directives. G G Collective leadership is characterized by a relatively dispersed power distribution across three key dimensions. The distribution of significant powers within the Communist Party is primarily concentrated among crucial positions such as the General Secretary, the Standing Committee of the Political Bureau, and the Political Bureau. Individuals' exercise of authority is contingent upon official regulations and informal norms. Consequently, individuals were required to adhere to these regulations and norms when exercising their authority. Second, power is shared between state organizations like the National People's Army, the State Council, and the Communist Party. With the diligent implementation of the reform and opening policy, various branches of the government, including the parliament and the Communist Party, acquired distinct spheres of authority, enabling their respective leaders to wield their power effectively. The authority to manage and administer the economy is vested in the prime minister of the State Council. At the same time, the responsibility for legislation and supervision lies with the chairman of the National People's Congress. Even the general secretary-general cannot infringe upon such authority. Third, there is a distribution of authority among diverse factions.G G The Communist Party ostensibly prohibits the formation of factions as per its guiding principles; however, in the realm of practical politics, the existence of factions is an undeniable reality. The individuals under consideration encompass various political orientations, namely reformists and conservatives. Additionally, they can be further categorized based on their affiliations with specific groups such as Shanghai clique, Beijing clique, Gusubang (糿薵閇), Gang of Four, Princeling, Tsinghua clique, and Beidavang (菄耵閇). The latter two groups are specifically classified based on the respective universities with which their members are associated. The most well-known were Jiang Zemin's Shanghai Bang, the Princeling Party, and Hu Jintao's Gongcheong Danpa. The balance of power in this situation was preserved by guaranteeing a specific position to each faction when forming the leadership of the ruling party, the government, and the power organization. For instance, the Communist Party general secretary and the prime minister of the State Council cannot be monopolized by a single faction.G

G 2. Utilization of power G The second modality of power manifestation entails the utilization of power in a distinct manner, constituting an alternative approach to exerting influence. The inquiry pertains to how the political elite wields their power, explicitly examining whether it is done arbitrarily or through a collectively institutionalized approach, thereby disregarding privately prescribed procedures and processes. During the Mao era, a distinctive characteristic of governance was the predominance of one-man rule. Mao Zedong exercised significant autonomy in determining crucial policy directions and personnel matters, often without seeking input or consultation from other individuals or entities. Mao also did not adhere to the Communist Party's and the state's regulations or procedures. Mao frequently refuted resolutions by the Central Committee of the Communist Party and the Politburo. In this regard, Mao can be characterized as a figure akin to a supreme ruler who held authority within the Communist Party. G G G

During the post-Deng Xiaoping era, there has been a notable shift in the approach to exercising power. As general secretaries, Jiang Zemin, Hu Jintao, and Xi Jinping hold significant positions within the Chinese political system. However, their authority is not absolute for crucial policy and personnel decisions. In order to arrive at a collective decision, the concerned parties must convene a meeting of the Politburo Standing Committee and the Politburo, allowing a thorough deliberation of pertinent matters before reaching a consensus. There are instances in collective leadership system in which the general secretary circumvents the political bureau through various leadership groups and decides on significant matters.G G Nonetheless, even in this instance, nothing that has not been decided by the Politburo or the Politburo Standing Committee can be announced under the banner of communist central. Moreover, when exercising its authority, it must adhere to the Communist Party's and the state's regulations and procedures. In this regard, the individuals in question hold leadership positions within the Communist Party.G

G 3. Dynamics of power relationsG The third power relationship consists of the paramount leader, the party president or general secretary, and other members of the Politburo Standing Committee. In the early days of the Communist Party, the Central Secretariat of the Communist Party and the Standing Committee of the Political Bureau shared a cooperative rapport. Hence, during the convening of either the secretariat meeting or the Politburo Standing Committee meeting, the participants engaged in comprehensive deliberations, ensuring a balanced exchange of viewpoints, and ultimately arrived at collective decisions. The establishment of China in 1949 marked a significant turning point in the dynamics of international relations, as the notion of equal relations between nations underwent a notable transformation. Under the leadership of Mao Zedong, a prominent figure in the political landscape, a consolidation of power occurred across various domains, such as politics, economy, and military. This transformed the dynamics between Mao Zedong and his colleagues, leading to a hierarchical relationship where the latter assumed subordinate roles.G G Cooperative relations of the Communist Party general secretary and other members of the Standing Committee of the Political Bureau was reinstated under the collective leadership of the post-Deng Xiaoping period. The Communist Party protocol also helped to clarify their distinct responsibilities and positions. The operational guidelines governing the Politburo, Politburo Standing Committee, and Secretariat, established in 1987 and 2002, exhibit a representative nature. This states that the general secretary has the authority to direct the Central Secretariat on behalf of the Communist Party, preside over various meetings of the Politburo and the Politburo Standing Committee, and issue decisions. From this, the paper may conclude that the posts and responsibilities of the party president and general secretary throughout the Mao Zedong reform era are wholly distinct. In other words, the general secretary never exercised the final decision; instead, the party chairman did. Thus, the relationship between the general secretary of the reform period and other members of the Standing Committee of the Political Bureau is articulated as primus inter pairs among the same individuals.

G THE CHILDBIRTH POLICY IN CHINA: AN ANALYSIS FROM A POLITICAL SYSTEM PERSPECTIVE 1. The phase of pregnancy advocacy G From 1949 to mid-1953, the People's Republic of China, with an initial population of 540 million, undertook a series of policies to encourage childbirth. This strategic approach was adopted to effectively tackle labor shortages and bolster productivity, ultimately laying a solid foundation for the establishment and progress of a socialist state. During this era, the widespread adoption of Mao Zedong's theory of acquisition and the concept of multilateral welfare within the context of traditional agricultural society led to a substantial increase in population. Since the advent of the year 1950, the

government has undertaken a series of initiatives and policies with the explicit objective of fostering childbirth rates. One such measure, the Measures on Abortion Restriction of Women's Executives, has been implemented as part of this overarching strategy. During the aforementioned historical era, Mao Tse-tung ardently propagated the ideology of self-sufficiency, which emphasized using manual labor as a primary driver of production. The aforementioned ideology was extensively pervasive throughout the historical period, commonly referred to as the Great Leap Forward. The observation of a strong dependence on manual labor in the production process implies a potential association between the size of a population, the abundance of labor resources, and the pace of economic development. G G The political system characterized by Mao's sole leadership can be further elucidated by examining the underlying rationale behind the policy promoting childbirth. This rationale is deeply rooted in productivity considerations and Mao's acquisition theory. The substantiation of the policy's efficacy in promoting childbirth is evidenced by the recorded total fertility rate in China from 1950 to 1955, which stood at 6.11. G

G 2.GThe phase of birth controlG In the mid-1950s, the Chinese government recognized the interrelationship between population growth and economic development, leading them to consider the potential adoption of birth restrictions. With the exception of minority areas, the Chinese government issued a decree in the National Agricultural Development Guidelines from 1956 to 1967 to restrict childbearing in heavily populated areas. They also encouraged the custom of postponed marriage. The decision was found to have been influenced by the notable impact of the unexpectedly robust population growth ascertained during the inaugural census conducted in 1953. In response, the Chinese Government Administration and the Ministry of Health implemented population control measures, such as the pervasive dissemination of propaganda and educational campaigns on contraception and artificial abortion. Mao Zedong promoted the need for human restraint during a meeting of the Supreme Council when discussing the achievement of planned expansion. In parallel, Chinese economist Ma In-chu presented an innovative population theory that tackles concerns of population dynamics. However, the implementation of the Great Leap Forward Movement resulted in a significant increase in the population. This resulted from improperly taking into consideration demographic changes during this period. The natural growth rate and total fertility rate experienced a notable upsurge during the period spanning from 1962 to 1965, surpassing all previously recorded rates observed since the inception of New China. In addition, with the onset of the Cultural Revolution, the enforcement of the birth control policy was revoked, resulting in an escalation of poverty in rural regions due to the absence of population regulations and the concurrent population explosion.G

G 3. The implementation phase of the two-child policy implementation G China has persistently reconfigured its population policy through the exclusive implementation of the two-child policy. Since 2007, numerous research institutes have undertaken studies to reevaluate and reconfigure the existing birth control policy. On January 6, 2010, the National Population Planning Birth Committee announced the release of the 12th Five-Year Plan for National Population Development. This plan introduced a significant policy change known as the single two-child policy, which allowed couples to have a second child. The 18th Third Plenary Session, which took place on November 15, 2013, was a pivotal event that resulted in a momentous decision to discontinue the onechild policy. This long-standing measure had been implemented for a period exceeding thirty years. The official implementation of the two-child policy took effect, replacing the previous policy.G G In the course of implementing the single two-child policy, several distinct issues have emerged. Firstly, numerous authoritative figures have vehemently opposed implementing the single two-child policy. The implementation of the single-child policy was hypothesized to potentially result in a subsequent phase of population growth, thereby potentially triggering a resurgence in women's fertility rates.

China's pre-established objectives for population growth were significantly impacted by the consecutive occurrence of two elevated periods, characterized by a surge in birth rates among women surpassing replacement levels and a deceleration in the pace of zero population growth. With so much available labor, this is not the most significant time to enforce the two-child ban, and it stands to reason that doing so will only exacerbate current labor shortages. The proposed resolution to address the issue of aging entails implementing an enhanced retirement welfare system that is not contingent upon the childbirth policy. The diverse policies regarding limiting offspring to two children across the various provinces within the nation have resulted in potential inconsistencies and conflicts among said provinces. The variations in the implications of the two-child policy were observed among the different provinces, specifically within their respective policy frameworks. Beijing, Tianjin, Guangxi, Shandong, Inner Mongolia, Gansu, Nanjing, Chongqing, and Hubei used the concept of single-lanai, whereas Zhejiang and Hebei used the concept of single-lanai. The terms single child and Erhai were used interchangeably but with distinct meanings; for example, single Erhai meant two children of a single couple, and having a second child meant that the original pair did not already have many children. Nonetheless, the singletwo-child policy does not apply to families with more than two children, as the term single-lanai meant something other than single-two children, even if one of the couples is a single-born kid. The divergent interpretations of the definition across different regions have engendered discordant viewpoints between local governing bodies, thereby presenting a multitude of challenges in effectively implementing policies pertaining exclusively to the regulation of two children.G G The implementation of the two-child policy in China, while a significant step towards addressing the nation's low birth rate, has yet to prove to be a comprehensive solution to the underlying issue. China, the most populous nation globally, faces a significant challenge regarding its fertility rate, which ranks 150th worldwide. This predicament has led to growing concerns regarding the country's declining birth rate. In recent decades, there has been a persistent decline in the number of newborns, leading to low birth rates. There was a decline in the number of newborns over three years. Specifically, newborns decreased by 630,000 from 17.86 million in 2016 to 17.23 million in 2017. Subsequently, in 2018, the number of newborns further declined to 15.23 million, representing a decrease of 2 million compared to the previous year. G G

4. The implementation of the Three-Child Policy The three-child birth policy's significance and associated support measures have been amplified due to several notable advantages. These advantages include improving the population structure, implementing a proactive national strategy to tackle population aging, and preserving the benefits derived from human resources.G G In light of the implementation of the two-child policy, a notable segment of households has indicated a keen interest in augmenting their family size. However, they have chosen to abstain from doing so owing to three predominant factors. The factors under consideration encompass the significant financial responsibilities that arise from the decision to have more children, the lack of sufficient childcare services, and the difficulties women encounter in effectively balancing their familial obligations with their professional aspirations. Therefore, a holistic methodology was employed, encompassing supplementary measures of assistance and the execution of policies to assess the ramifications of a three-child framework. As mentioned earlier, the statement acknowledges the imperative to collectively address the interconnected aspects of marriage, childbirth, parenting, and education. The Ministry of Human Resources and Social Security conducted a comprehensive examination of regulations concerning maternity leave and maternity insurance. The examination considered various factors, including working hours, breaks, and vacations for workers. In addition, the ministry has developed targeted law enforcement measures to ensure the protection and preservation of the rights and interests of women within the workforce.G G

Moreover, it mandated the promotion of maternal and fetal well-being, the implementation of comprehensive measures to prevent the birth of children with disabilities, and the establishment of standard protocols for human-assisted reproductive technologies. The government has expanded the three-child policy to include people with disabilities to ensure that healthy birthing occurs and advance the general population's well-being. The intervention consisted of the distribution of relevant information, the improvement of guidance on preventing childbirth for individuals with disabilities, the strengthening of premarital health practices, the encouragement of comprehensive medical evaluations for the birth of healthy children, the intensification of thorough prenatal and postnatal examinations and diagnoses, and the facilitation of interdisciplinary cooperation. Moreover, a functional mechanism was implemented to facilitate government-led assistance and foster active participation from social organizations. Through an open bidding methodology, the task of delivering birth control services to specific families was entrusted to eligible social organizations. The services provided encompassed various aspects of care, including assistance with daily living activities, emotional support, and guidance in legal matters. This included facilitating the relocation of legal representatives to nursing homes and overseeing the management of medical and nursing affairs. The birth control policy in different regions of China, encompassing provinces, direct cities, and autonomous regions, experienced modifications in alignment with the directive issued by the central government. The length of maternity leave has effectively been extended nationwide, and regulations to provide males with paternity leave have been implemented. Variations in specific indicators were observed concerning the level of regional development. Panzhihua City, situated in the province of Sichuan, offers a monthly childcare subsidy of 500 yuan to households giving birth to their second or third child. In Beijing, households with more minor children are favored when applying for public housing rentals and include 16 supplementary reproductive technology procedures within the scope of coverage provided by medical insurance settlements. G

A COMPARATIVE ANALYSIS OF THE BIRTH POLICIES ENACTED BY MAO ZEDONG AND XI JINPING Ideological factors played a crucial role in shaping the government of Mao Zedong. During the earlier period, Mao Zedong assumed the role of the delegate from Hunan Changsha in the inaugural assembly of the Communist Party of China. The establishment of the Communist Party of China was helped via the assistance provided by the Soviet Union. Subsequently, the Communist Party expanded its influence by utilizing its original collaborative endeavor. Following the dissolution of the cooperative alliance, the organization has become embroiled in an extended legal conflict spanning two decades. During the series of events, a significant ideological disagreement emerged among the leaders, finally leading to the ascension of Mao Zedong to power during the quasi-conference in January 1935. Subsequently, Mao enacted a well-defined policy framework to safeguard the Communist Party from the onslaughts initiated by the Kuomintang.G G In 1936, Mao instigated a party reorganization during the second cooperation campaign, subsequently taking the party's leadership role in 1938, reaching the utmost level of authority both nominally and effectively. At the 7th Party Congress convened in April 1945, the Communist Party of China officially embraced Mao Zedong's collection of policies, concepts, and ideas as the party's guiding ideology, alongside Marx-Leninism, under the label of the 艉眤塃萷蒋.G G The termination of the joint enterprise in 1946 precipitated the commencement of the civil war. On October 10, 1947, Mao Zedong promulgated the Ssangsip Order to tackle the aberrant conduct displayed by party members by implementing stringent party discipline. The core components encompass the Three Great Rules and the Eight Great Principles (趏耵謗褙). The Communist Party of China enhanced its organizational unity through the implementation of action instructions and the regular provision of ideological education. Consequently, the Kuomintang-led Republic of China was required to undertake a forced evacuation to the island of Taiwan. At the same time, the People's

Republic of China emerged as the governing power over the mainland. Mao's efforts to achieve national unification garnered substantial support from both the elite segments of society and the general populace, thereby conferring legitimacy upon the Communist Party's government.G G G Before the creation of the People's Republic of China, Mao's leadership had already attained absolute and unchallenged authority. The integration of Mao Zedong Thought into the highest levels of the Communist Party's leadership in 1945 granted Mao an indisputable mandate within the party, thus consolidating his position. In order to offer more elucidation, after the founding of the People's Republic of China, Mao implemented a governance system characterized by his exclusive authority. Mao, a renowned revolutionary leader, aimed to attain economic progress by prioritizing building a state grounded in socialist philosophy. The examples above encompass several historical events and movements in China, such as land reform, the Three-Party and Five-Party Movement, the Anti-Rightist Struggle, the People's Communication, the Great Leap Forward Movement, and the Cultural Revolution. Mao Zedong implemented a policy posture from 1949 to mid-1953 to promote population increase. The endeavor above was undertaken to construct the fundamental structure for a socialist state.G G Mao's objective was to enhance the workforce and productivity by implementing proactive strategies to encourage childbearing. The Chinese government implemented policies to incentivize births during the specified historical period. These policies-imposed limitations on contraception and abortion, intending to ensure a sufficient labor force and foster economic productivity. Hence, at the inaugural national census conducted in 1953, the population of China had surged to an astonishing 600 million, signifying a tremendous growth of more than 100 million within five years. The exponential growth of the population, primarily attributed to a yearly fertility rate of 37%, has resulted in many challenges. These include diminished productivity stemming from an overabundance of workers and scarcity of food and housing within urban regions.G G The Chinese government has enacted particular steps to address issues related to contraception and artificial abortion. However, a fundamental reform of the population policy stance has not been conducted. During the mid-1950s, several intellectuals articulated their perspectives regarding the population, which later garnered recognition as a significant societal concern. One notable figure in this discourse was Ma In-chu, who espoused the implementation of population control strategies grounded in Malthusian theory. The article titled New People offers a comprehensive analysis of the approaches utilized by the government to promote well-informed decision-making in the development of policies. This involves the methodical collection of precise data through periodic censuses, the dissemination of information on contraception to contest prevailing fertility-focused ideologies, and the enforcement of strict regulations against induced abortions, all while advocating for managed population growth by promoting the widespread adoption of contraception. Nevertheless, his claim gets classified as Malthusian with the anti-rightist movement that followed and got repressed.G G Mao Zedong, a significant influence in that historical period, voiced his disagreement with Manchu's demographic theory by proposing the acquisition theory. The observer observed that addressing the issue of food scarcity and poverty necessitated a fundamental transformation in the socioeconomic structure. The underlying factors contributing to these challenges can be mainly linked to capitalists' coercive and exploitative activities rather than being entirely ascribed to overpopulation and excessive resource use. From a Marxist materialist perspective, a large population can lead to the effective allocation of labor, hence enhancing productivity and fostering economic progress to address the population issue. The philosophy of Mao Zedong during the historical era, referred to as the Great Leap Forward Movement, placed significant emphasis on prioritizing concentrated labor instead of capital and technology.G G Nevertheless, utilizing the takeover hypothesis served as a political mechanism to quell dissent. Moreover, a set of policies advocated by Mainchoo were implemented from the late 1950s to the early

1970s. In the given environment, Mao Zedong's policy on encouraging births was primarily driven by a desire to centralize control and consolidate power under his leadership. This strategy had the potential to yield positive outcomes, given the current social circumstances characterized by limited female participation across several domains of society. G G On the other hand, the case of Xi Jinping exhibits both commonalities and divergences. The ideological cornerstone introduced by Xi Jinping during the 19th Party Congress is a fundamental notion that underpins many institutional transformations, exemplifying the reinforced collective leadership framework that has been previously deliberated. One noteworthy political advantage Xi Jinping possesses is his significant departure from Chinese predecessors, including Jiang Zemin and Hu Jintao. The exceptional quality of this trait has enabled Xi Jinping to successfully articulate his viewpoint on the progress of socialism with Chinese characteristics in the contemporary era and throughout his term in office. The persistent significance of ideological authority, a significant characteristic attributed to the supreme leader in China, remains consistent throughout the leadership of Mao Zedong and the successive leaders that followed Deng Xiaoping. As highlighted in the political report of the 19th Party Congress, the advent of the socialist ideology known as Xi Jinping Thought in the present era is predicated upon the Chinese Communist Party's recognition of the intricacies posed by the prevailing domestic and international circumstances in China. The current challenges comprise an increasing wealth imbalance, environmental deterioration, and the desire to attain great power status.G G The primary objective is to construct a depiction of societal dynamics within a specified timeframe, namely 2020. The primary goal within the foreseeable future is to attain the fundamental modernization of socialism by the year 2035. The overarching goal is to develop a comprehensive and durable framework for socialist modernization by 2050. Xi Jinping implemented a revision to the existing onechild policy during his five-year term to achieve a specific objective. This alteration enabled couples to bear two offspring as opposed to the prior restriction of one.G G Furthermore, the significance of the 19th Party Congress and the ideology of Xi Jinping was underscored in order to enhance the optimization of the population composition, augment the workforce, tackle the issues arising from population aging, achieve the objectives of a robust and influential economy, and foster familial well-being and societal cohesion. In this particular setting, it becomes evident that, according to Mao Zedong, Xi Jinping endeavors to augment and fortify the ideological and political facets. However, he is formulating policies promoting realistic approaches to achieving economic advancement. The ideological framework of Xi Jinping is primarily rooted in political motivations; however, it has resulted in significant transformations in the administration of public services. These reforms aim to adequately respond to the requirements of a population development strategy in the contemporary setting. This discovery validates that the strategy under investigation diverges by emphasizing enhancing the quality of life for individuals within a particular societal framework.G

CONCLUSION This study aims to enhance the current scholarly literature by doing a comparative examination of the systems adopted by Xi Jinping and Mao Zedong. The analysis of these two systems, which has garnered significant scholarly interest recently, aims to ascertain and authenticate their shared characteristics and disparities. This remark is of particular significance as it underscores the opposing attributes of Xi Jinping's second-term system and Mao Zedong's sole leadership system within China's notable political trajectory. Furthermore, compared to other studies, the justification for doing research can be supported by its ability to illustrate the implementation of childbirth policies within different systems. This study additionally examines the existing conditions and political rationales that underlie the birthing policies implemented by Xi Jinping and Mao Zedong, placing particular attention on the political context.

During the Mao era, the political landscape was characterized by a system of governance in which Mao Zedong held absolute authority, effectively establishing a one-person rule within the realm of elite politics. Mao Zedong effectively consolidated power by leveraging his charismatic authority, establishing a monopoly over the decision-making processes within the Chinese Communist Party. This ascendancy allowed Mao to exercise his discretionary jurisdiction, often without adhering to established norms or procedures. The individual in question possessed a notable degree of charismatic legitimacy, which contributed to his status as a revered figure in the capacity of a revolutionary leader and founding father. The development above emerged as a pivotal foundation for both the political elite and the general populace to embrace Mao's singular authority. Furthermore, it is noteworthy that Mao successfully solidified his position of authority by employing the Politburo meeting in 1943 and the Communist Party's 7th Party Congress in 1945. These pivotal events allowed Mao to obtain what can be referred to as the last policy decision and establish a sense of procedural legitimacy within the party. During Mao's tenure as the sole leader, there was a notable concentration of power in his hands, with policymaking, personnel decisions, and military control centralized around Mao as an individual. Liu Xiaoqi, the second-in-command individual who eventually succeeded Mao Zedong, encountered significant challenges in attempting to establish a power-sharing dynamic with Mao. Mao Zedong, a prominent figure in Chinese history, assumed a position of significant authority within the Communist Party and the state, akin to that of an emperor. The individual in question tended to exert his control autocratic, disregarding established institutions and regulatory frameworks. Mao's comprehension of democratic centralism and collective leadership was limited. The formalization of the one-two-term system during the eighth Communist Party Congress in 1956 justified Mao's exercise of dictatorial power. He had yet to attend a Politburo meeting since 1958, disregarding official bodies such as the Party Congress and the Central Committee. Instead, he used more beneficial informal groups like gatherings of local party secretaries and craft meetings to carry out his agenda. Despite widespread opposition, this allowed him to push forward with the Great Leap Forward Movement and the Cultural Revolution. Subsequently, a state-sanctioned alliance materialized between Mao Zedong and his contemporaneous political counterparts. Following the establishment of China, the equal comradeship that had existed during the revolution was replaced by a military alliance. One observed outcome was the direct consequence of the regular practice of Mao's daily worship. This particular position allowed Mao to carry out purges of leaders who espoused divergent ideologies during the Great Leap Forward Movement and the Cultural Revolution. Based on Mao's one-person rule, elite politics under Xi Jinping cannot be described as one-man rule. First, unlike Mao, Xi Jinping derives his power from institutional rather than personal authority. To rephrase, he rose to prominence after being appointed to high-ranking government positions, such as general secretary of the Communist Party. He knows the boundaries of institutional authority, which is why he is so fixated on his position despite being mockingly referred to as a title collector by international media.76 In this regard, the fact that he occupies numerous positions instead of just one shows that his power could be more stable rather than robust. Furthermore, Xi Jinping cannot act autonomously in all areas of power, including personnel decisions, military leadership, and policymaking. Instead, he must convene a meeting of the Political Bureau's Standing Committee or a meeting of the Political Bureau before using such authority, and he must do so per the established procedures. This is supported by the fact that during the Xi Jinping era, political bureau meetings and meetings of other government-government groups were regularly convened, and significant issues were discussed and decided through this process.

Lastly, the relationship between Xi Jinping and other members of the Politburo Standing Committee is not the same as military relations. The relationship between them remains one of equality, and each individual has one vote when deliberating on matters of significance. Within their spheres of influence, they are free to act independently. For instance, the general secretary has exclusive authority in military and foreign affairs, party affairs, and reform guidance, the prime minister of the State Council has economic management and administration, and the National People's Congress chairman has exclusive authority in legislation and oversight. Although Xi Jinping has obtained a core status similar to Jiang Zemin's, this has not fundamentally altered their equal-to-mainstream relationship. Xi Jinping, however, has secured the authority of the final policy coordinator and executive facilitator by achieving the rank of core, in addition to the general secretary's initial authority to choose agendas, preside over meetings, and disseminate essential papers. Moreover, the differentiation between Xi Jinping's and Mao Zedong's political systems can be further elucidated by analyzing their respective birth policies. The political report of the 19th Party Congress emphasizes the emergence of Xi Jinping Thought as a socialist ideology in the new age. In pursuing this purpose, Xi Jinping revised the existing one-child policy during his tenure, allowing couples to bear two children instead of one. The policy above modification has been implemented for five years. Moreover, the 19th Party Congress emphasized the importance of Xi Jinping's ideology in enhancing the demographic structure, expanding the labor force, addressing the challenges of population aging, promoting sustainable economic growth, and nurturing family welfare and social unity. In this context, it is apparent that Xi Jinping, similar to Mao Zedong, seeks to enhance and strengthen the intellectual and political dimension. Nevertheless, Xi Jinping is devising policies based on pragmatic principles, primarily emphasizing promoting economic progress. Fundamentally, Xi Jinping's ideology is grounded in political considerations. Nonetheless, substantial reforms have been enacted in the service management system to efficiently meet the demands of a population development plan in the present-day era. Within this particular setting, it can be verified that the government led by Xi Jinping deviated from the system created by Mao, opting instead to consolidate Xi Jinping's preexisting framework and enact policies aimed at strengthening the structure of collective leadership. As demonstrated in this research, China's economic situation since Mao Zedong has been influenced by its population's high potential. Nevertheless, instances arose where birth control programs were enacted in response to the adverse consequences stemming from an unchecked expansion of the population. The primary drivers of China's economic growth were the expansion and trade of the domestic market. These factors were exemplified by the implementation of the new urbanization promotion in 2013. Additionally, the reform of income distribution played a crucial role as a fundamental reform pathway for the 5th generation leadership. Moreover, the recent rapid decline in the birth rate has rendered the future of the Chinese economy uncertain, suggesting that President Xi Jinping has strengthened internal control via the 20th National Convention with the justification that overcoming the crisis through strong leadership is the solution. Nonetheless, the present study is constrained in its ability to fully comprehend the historical transformations in China's birth policy due to its predominant focus on political factors, disregarding the sociocultural ramifications within the discourse and formulation of policies among the Chinese population. Yet, this study offers a unique viewpoint as it investigates the augmented collective leadership structure under Xi Jinping's tenure after the 19th Party Congress, in contrast to Mao Zedong's authoritarian rule. Moreover, it conducts a novel inquiry to determine the discrepancies in the childbearing policy. Even so, it is crucial to recognize the intrinsic constraints of scientific inquiry. Henceforth, it is imperative for forthcoming research endeavors to endeavor to furnish a more allencompassing explanation of the disparities between the frameworks instituted by Mao Zedong and Xi Jinping, with a specific focus on their intellectual foundations. Furthermore, it is imperative to prioritize research initiatives that explore the demographic discourse of birth policies and comprehensively analyze their sociocultural implications.

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Navigating Inclusivity: Unveiling Challenges in Using Public Transportation Network for Visually Impaired Individuals in the Seoul Capital Area Author 1

Author 2

Hong, Seokhyeon

School Name

Hankuk Academy of Foreign Studies

Full Name

Seo, Yewon

Hankuk Academy of Foreign Studies

Full Name (Last Name, First Name)

(Last Name, First Name)

School Name

ABSTRACT: This article reports on the design of bus terminals in the Seoul Capital Area, South Korea, for the visually impaired (including those who are blind and those who have low vision). Interviews with five individuals revealed a need for more usability for bus terminals and stations than other transportation facilities. This study mainly uses thematic analysis of qualitative data between 5 individuals to explore the most critical deficiencies causing the visually impaired to be disconnected from public transport.

KEYWORDS: The Visually Impaired, public transport, bus terminals, Seoul Capital Region, Seoul City, Gyeonggi Province, Incheon City

INTRODUCTION With at most 2 dollars, South Korea's public transportation system can take anyone, everywhere, within the boundaries of Incheon City, Seoul City, and Gyeonggi Province(hereafter called the Seoul Capital Region). The transfer policy is where if one changes to another public transportation vehicle within thirty minutes, no fees are charged, connecting all of the myriads of lines of buses and metropolitan railways. The fee of a mere 2 dollars is what it takes to enter the public transportation network, creating a symbiosis. However, although the transportation system could take anyone anywhere, individuals with low vision or blindness (hereafter called visually impaired) are disconnected from this symbiotic experience. There must be compensation if there is a will to allow access to all the infrastructure for the visually impaired. To achieve this objective, the study reported in this article investigated the frustrations of traveling using public transport for the visually impaired. The population of the visually impaired The population of the visually impaired is a significant portion of the population in South Korea. Province

Total

Male

Female

South Korea

250,767

148,909

101,858

Seoul City

40,991

24,622

16,369

Busan City

17,740

10,485

7,255

Daegu City

11,788

6,980

4,808

Incheon City

13,800

8,286

5,514

Gwangju City

7,146

4,207

2,939

Daejeon City

6,905

4,104

2,801

Ulsan City

4,790

2,834

1,956

Sejong City

1,240

775

465

Gyeonggi-do

54,916

33,597

21,319

Gangwon-do

9,396

5,401

3,995

Chungcheongbuk-do

8,793

5,221

3,572

Chungcheongnam-do

12,146

7,252

4,894

Jeollabuk-do

11,058

6,450

4,608

Jeollanam-do

13,412

7,481

5,931

Gyeongsangbuk-do

15,612

8,829

6,783

Gyeongsangnam-do

16,937

10,058

6,879

Jeju Island

4,097

2,327

1,770

The Korean Statistical Information Service (hereafter called KOSIS) reports that in Korea total, there is 250,767 registered population that are visually impaired (highlighted in blue)(ͼ΀΄ͺ΄͑傕伨瓝俬眔瑠, n.d.). For the purposes of this study, 40,991 population of visually impaired in Seoul City, 54,916 population of visually impaired in the Gyeonggi Province, and 13,800 population of Incheon City(all highlighted in yellow); a combined 109,707 would be the number of people in the region set as the limit. On August 21, 2023, KOSIS Reported that Seoul City has a population of 9,338,274, 13,794,753 For Gyeonggi Province, and 2,959,571 for Incheon City. Combined, the three amounts to 26,092,598 people. It can be calculated that 0.42% of the Seoul Capital Region’s population is legally registered as visually impaired. To be legally registered by the Korean Government as a visually impaired person, the person must be one of the following. £ A person who has a bad eye vision (referring to the corrected vision measured according to the recognized vision table) of 0.02 or less ¤ a person with good eyesight less than 0.2 or less ¥ a person whose vision in both eyes remains below 10 degrees from their respective gaze point ¦ a person who has lost more than a half of his sight § a person with double vision within 20 degrees of the central vision of both eyes.͙͑͹ΥΥΡͫ͠͠摄槠昄伩櫍梈檠思注倨, n.d.) Two main types of regularly scheduled public transportation are widespread in the Gyeonggi province, Incheon City and Seoul City. Buses and the metropolitan rail cover most of the transportation needs since an estimated 7,300,000 users use the system 18,450,000 times daily (Ministry of Land, Infrastructure and Transport). It can now be calculated that 27.98% of the population in the Seoul Capital Region migrates through public transportation every day. 27.98% of the visually impaired population is 30,696. Every day, 30,696 people in the Seoul Capital Region experience difficulties in a situation where public transportation should be used.

LITERATURE REVIEW Related studies have been conducted in England(Low et al., 2020), and Italy(Campisi et al., 2021). Urban mobility and accessibility have garnered significant attention in recent years as essential components of creating inclusive and equitable cities. For individuals with visual impairments, public transport, and walkability are crucial for enabling independence and participation in out-of-home activities. Despite governmental efforts to promote accessible transportation for all, the unique needs of visually impaired people (VIP) remain inadequately addressed, often resulting in challenging journeys. This literature review critically examines two distinct research papers that delve into the journey experiences of VIP using public transport and the walkability of urban environments from their perspective. The first study focuses on evaluating the journey experience of VIP using public transport in London. Through semi-structured interviews, the researchers uncovered several key concerns. One major issue is the limited access to information, making navigation difficult for visually impaired individuals. Inconsistencies in infrastructure further exacerbate the challenges faced by VIP, hindering their ability to travel independently. The lack of available staff assistance compounds these issues, emphasizing the need for more accessible and supportive transport systems. Notably, the provision of concessionary travel positively impacts the well-being of VIP, encouraging them to embark on more journeys. The findings underscore the necessity of tailored policies that cater to the specific needs of different disabilities, rather than adopting a generalized approach. Ultimately, the study concludes that the journey experience significantly influences an individual's sense of independence and societal inclusion. The second study introduces a research endeavor aimed at assessing the walkability of urban

environments from the perspective of visually impaired individuals. Employing the Commented Paths Method (CPM), the study offers a qualitative analysis rooted in the practical experiences of visually impaired individuals navigating specific paths. The researchers employ multiple-choice questions and a Likert scale to evaluate various physical characteristics and infrastructural elements along these paths, considering factors such as slope surface and sidewalk width. The study extends its focus to encompass interferences encountered during movement, including the need to stop and assistance from others, as well as emotional responses like anxiety and tiredness. The research methodology generates disaggregated and global Walkability Indices, enabling the creation of thematic maps that highlight critical aspects of each path segment. By conducting a case study in Enna, Italy, the results reveal a notable emphasis on infrastructural issues compared to perceived interferences. This aligns with the local context and contributes to the study's validity. Importantly, the research advances the discourse on inclusive public policies by incorporating the subjective viewpoints of visually impaired individuals, which proves pivotal in enhancing walkability for all city dwellers. These two research papers collectively illuminate the challenges faced by visually impaired individuals in urban environments. The first study underscores the significance of tailored policies to meet the diverse needs of VIP when it comes to public transport accessibility. The second study, employing an innovative method, highlights the importance of infrastructural considerations for walkability. Both papers share a common theme of inclusivity, emphasizing the necessity of adopting a user-centric approach to enhance urban mobility and accessibility for all individuals, regardless of their visual impairments. As cities continue to evolve, addressing the concerns raised by these studies can contribute to the creation of more accessible and equitable urban spaces.

METHOD Since the study's main objective is to evaluate what changes are needed to connect the visually impaired and public transport, a thematic analysis was carried out. Interviews were performed to accumulate qualitative data to discover the blind spots between public transport use and the visually impaired, the recurring frustrations among the visually impaired, and the current status of public transport amongst the visually impaired.

Participants To qualify as an interviewee for this study, the participants had to qualify in the following three criteria. Be visually impaired in a legal sense, be a member of the Seoul Capital Region population for more than three years (to strengthen the study's validity), and have tried using the public transportation system. Data was collected from participants until redundant information occurred. Based on the principle of data saturation, it was determined to collect sufficient data on the sixth interview. Later, one of the participants was found to have been visually impaired for only three months and had not finished training, thus giving more extreme responses. The participant’s response was excluded, resulting in 5 interviewees in this study. As calculated earlier, 0.42% of the population in the Seoul Capital Region is legally visually impaired. To conduct an interview, because there is a lack of information on individual contacts for the visually impaired population, NGOs and government facilities specifically for the visually impaired were found. Each place was called and explained the paper’s purpose and the author’s status, eventually being able to contact the Yong-in department of the Korean Union of the Blind. There, an in-depth interview was requested with several people, and got permission five days after the initial call. Ten interview questions were created to gather qualitative data to determine the recurring difficulties. The interviews were conducted back to back, one interviewee after another, to remove the possibility of each interviewee influencing one another. Each interview question was tailored with enough open

answers that if there were a reoccurring answer, it would indicate a significant problem with using the public transportation network.

Interview In-depth interviews were done to understand the barriers to utilizing the existing public transport infrastructure. They were used in person because visually, the interviewer not being present cannot be changed through visual mediums such as online meetings since tactile interaction is a significant proportion of communication between the visually impaired and the interviewer. The etiquette for interacting with the visually impaired, including the practice of holding hands during initial introductions, was reviewed. Three types of questions were asked, one type in difficulties in accessing public transport, one type in problems as a pedestrian, and the last type in potential dangers of traveling in isolation. Ɣ Ɣ Ɣ Ɣ Ɣ Ɣ Ɣ Ɣ Ɣ Ɣ

Could you share some of the difficulties you've come across when using public transportation as someone with a visual impairment? Have you ever found it challenging to get accurate information about bus or train routes, schedules, and stops? What specific problems have you faced with the physical features of the transportation system, such as signs, paths, or seating? Can you tell about a recent situation where you didn't feel safe or comfortable while traveling on public transport due to your visual impairment? From your point of view, how crucial is it to have staff assistance available when you're using public transportation? Have you had any experiences, either positive or negative, with policies that offer discounts or benefits for visually impaired individuals using public transport? Can you describe instances where you've felt isolated or uncertain when traveling alone on public transport? When it comes to walking to and from public transport stops or stations, what kinds of challenges have you encountered as a pedestrian with a visual impairment? In your opinion, what could public transport authorities do to better address the needs of people with visual impairments? If you were to suggest ways to enhance accessibility for visually impaired individuals using public transportation and create a more inclusive experience, what advice would you offer?

JUSTIFICATION The transcript data was thematically analyzed for the data analysis. Each of the five transcripts was read multiple times to gain familiarity and validify the overlapping parts. The rereading showed a theme for the overlapping parts. Keywords were identified when things overlapping showed a common pattern. Then, the transcript data was categorized so that each response for each category was in a separate column in a table. Then, for each category artificial intelligence query with InfraNodus(InfraNodus.Com by Nodus Labs, n.d.-b) was done to separate the keywords to enhance the accuracy and offset human error. The two data were cross-examined to isolate keywords that clearly contained meaning. The resulting codes are represented in the following table. Most codes received more than one example interview quote, normally six, however, some of them were overlapping and it was considered unnecessary to include all of the quotes in the table.

Code

Description

Example Interview Quote

…and the cars were gradually parked on top of the Braille block, but you cannot park a car there. Tactile paving for It is the entry and exit route that we, the blind, go back and Braille block visually impaired forth along the braille block like this, but the car is put on top of it, so it is blocked so that we cannot go in and out. The most important thing for navigation is sound. If I can make a bell called the zone itself that says which Vocal or telephonic Communication zone I will board, and when I press it, it tells the direction communication Busan, Daejeon, Daegu. We will not have to look for a bus stop to catch the bus anyway. right? First, we have to ask passers-by and go with a guide Direction Guidance or route if there is a guide, or if we are walking alone, we have to go in that direction with a white cane and walk the same way. If I have to stop at Seodang station, for example, I should The audibility of be able to listen to the notification of which station is next. Audibility notifications However, all the train traveling noise drowns out the notification’s sound. At least, because the railroad is operated by the state, now People in mandatory because that's why National Service Conscripts are military service who deployed there. So, for this kind of thing, even for private National Service was deemed inapt and bus terminals in Korea, the government has to do it so that Conscript was put to civil the National Service Conscript can be deployed there as services. well. When a signal sounds on the bus, and the signal that the disabled person is trying to board is put on the bus, then the Sound Auditory or noise driver puts it on the bus and knows that the disabled person is trying to board us here. They should wait, then.

OVERALL RESPONSES The transcripts of the interviews show that it is deemed nearly impossible to use the bus transit as five of the six codes are related to the difficulty in using buses. The one participant that has been visually impaired for only three months even quoted that it will never be possible regardless of navigation due to high stairs and bus drivers not waiting for the visually impaired. Individuals with a longer time being visually impaired seemed to have an easier time navigating in general. There was no quantitative analysis for this statement. However, the qualitative data showed that the longer the time of being visually impaired, especially in severe cases where there is a complete loss of vision, the easier people navigate through the stations. Participants all generally mentioned the need for human guidance. It was evident that it was a dependency that cannot be replaced easily. Most of the participant's problems could be addressed by using this single solution, however, it was also evident that all of them acknowledged the fact that there are not enough human resources to field one guide per person.

This paper investigates the keywords “Braille Block,” “Communication,” “Audibility,” “National Service Conscript,” and “Sound.” An analysis of the transcripts revealed that the communication between the status of the buses and the status of the user was the most severely problematic.

DATA ANALYSIS Theme: “Using the bus” This theme represents the difficulties the participants experienced in the process of interacting with the bus transit system. Considering the context of the usages, the participant all pointed towards one great theme in using the public bus transit system. The major theme of “Getting on the Bus” Inquiry: “At least, because the railroad is operated by the state, now because that's why National Service Conscripts are deployed there. So, for this kind of thing, even for private bus terminals in Korea, the government has to do it so that the National Service Conscript can be deployed there as well.” “When a signal sounds on the bus, and the signal that the disabled person is trying to board is put on the bus, then the driver puts it on the bus and knows that the disabled person is trying to board us here. They should wait, then.” “The main problem in catching a bus is that there is no way to tell which bus is the one I’m supposed to ride when there are multiple buses” The quotes above show that there is a major problem with getting on the bus. There is a problem in each step of getting on a bus, identifying which bus is which, navigating to the bus door, and climbing the stairs to ride the actual bus. Participants A, B, C, and E all mentioned the difficulty of navigating to the bus door. All of them mentioned the fact that buses don’t necessarily stop at the designated spot, so they have to guess where the bus stops every time. Participant C mentioned that when multiple buses arrive, sometimes the buses even stack on each other on different road lanes, where navigating to the bus without notice can lead to a human casualty. Participants B and C both mentioned that with enough time, it will probably be possible to navigate, but the buses never wait that long. It can be concluded that the bus transit system is very negatively usable, and needs improvement in the process of actually getting on the bus more than anything else.

Theme: “Using metropolitan railway” This theme represents the difficulties the participants experienced in the process of interacting with the metropolitan railway system. It could be concluded that the metropolitan railway system is fairly usable, but there were evident complaints mainly about the audibility of information. There was also a problem with over-relying on human guidance and difficulty in navigating in isolation. Inquiry: “At least, because the railroad is operated by the state, now because that's why National Service Conscripts are deployed there. So, for this kind of thing, even for private bus terminals in Korea, the government has to do it so that the National Service Conscript can be deployed there as well.” “When you request guidance from the information desk, a guide navigates me until I catch a taxi to my destination”

“If I have to stop at Seodang station, for example, I should be able to listen to the notification of which station is next. However, all the train traveling noise drowns out the notification’s sound.” The results show that when comparing metropolitan railways to bus terminals or stations, metropolitan railway stations are perceived as much better and usable on most occasions. The importance of human guidance was also greatly emphasized each time. Participant B even changed her mind about metropolitan railway stations when she was informed that National Service Conscripts were present to help anybody in need of guidance. Participant A described in length his regular usage of the subway system in Seoul, marking it as very usable with human guidance. This gave evidence that it is possible to reliably use the metropolitan railway system enough to become a regular user.

Theme: “Navigating public spaces” Bus stations, Subway stations, and Bus terminals are all public spaces that the visually impaired must interact with in order to access the public transportation system. Although the fact that the way of accessing is walking creates basic accessibility, there were great problems in the actual design of the places. Inquiry: “…and the cars were gradually parked on top of the Braille block, but you cannot park a car there. It is the entry and exit route that we, the blind, go back and forth along the braille block like this, but the car is put on top of it, so it is blocked so that we cannot go in and out.” “The most important thing for navigation is sound. If I can make a bell called the zone itself that says which zone I will board, and when I press it, it tells the direction Busan, Daejeon, Daegu.” “The main way of navigating is remembering a specific imperfection that I can remember to know where I am. Every time a make a new familiar location I use this strategy. This makes Glass walls frustrating to us because of a lack of imperfections” Participants D and A mentioned that the Braille blocks were put in the wrong order in addition to them being often covered by vehicles. The second quote indicates a lack of information to navigate like nonvisually impaired individuals. When asked supplementary questions about how they navigate without the aid of suggested services, they responded universally by asking passers-by for navigation. However, Participant A mentioned that because they are visually impaired, passers-by act like they never heard anything and ignore them.

IMPLICATIONS This study’s data and inquiries show that train stations, public spaces, and bus stations are accessible currently. The value of this study is that it confirms and pinpoints exactly what problems need to be addressed. Any interested parties such as government agencies, private companies, and software developers seeking to address the issue of public transit usability can use the results of this study to guide the creation process. For example, a software developer could develop an app that calls out which bus is the one they have to catch for the lightly visually impaired and guide them to the door.

LLIMITATIONS The study was limited to the city of Yong-in in the Gyeonggi Province, as the individuals interviewed and the surveyed population was found in the visually impaired association, Yong-in department. Admittedly, this limits the study's scope, as Yong-in City is only a part of the metropolitan area. However, since Yong-in has its own metropolitan railway that is connected to the web of the Seoul city metropolitan railway system and has numerous bus lanes that are similar in usage to all the other parts of the area, it would share all the same frustrations like falsely placed Braille blocks for the visually impaired, lacking guidance for the visually impaired, and the lack of precision on where the buses stop.

CONCLUSION In wrapping up, this research delves into the intricate array of challenges that visually impaired individuals encounter while utilizing public transportation, with a specific focus on the bus terminals within the Seoul Capital Area, South Korea. Through profound conversations held with five participants who are either blind or have low vision, a deep and nuanced exploration of the deficiencies inherent in the current design of bus terminals has been skillfully undertaken. The outcomes of this study illuminate an urgent need for heightened usability and accessibility within these transportation facilities, given their central role in the daily lives of visually impaired individuals. The thematic analysis of the qualitative data has artfully revealed that bus terminals and stations present a distinctive set of usability challenges that extend beyond those faced in other transportation venues. The participants' firsthand experiences have eloquently exposed issues concerning navigation complexities, the availability of accessible information, and the overall terminal environment. By distilling this data, it has become evident that these design gaps substantially hinder visually impaired individuals from seamlessly integrating into the public transportation network, ultimately curtailing their autonomy and active engagement in various aspects of life. This research makes a meaningful contribution to the broader discourse on fostering inclusive urban environments by pinpointing the inadequacies within the existing design of bus terminals. It underscores the paramount importance of proactively addressing these shortcomings, not solely for the immediate benefit of the visually impaired community but also for the broader fabric of society. The study accentuates how a well-conceived and inclusive public transportation system forms a foundational bedrock for nurturing equal opportunities and social cohesion among individuals, irrespective of their visual capabilities.

Work Cited Campisi, T., Ignaccolo, M., Inturri, G., Tesoriere, G., & Torrisi, V. (2021). Evaluation of walkability and mobility requirements of visually impaired people in urban spaces. Research in Transportation Business and Management, 40, 100592. https://doi.org/10.1016/j.rtbm.2020.100592

ΙΥΥΡͫ͠͠摄槠昄伩櫍梈檠思注倨. (n.d.). https://bokji.or.kr/sub/sub06_01.php InfraNodus.Com by Nodus Labs. (n.d.-a). InfraNodus: Generate Insight with AI and Network Thinking. https://infranodus.com/ InfraNodus.Com by Nodus Labs. (n.d.-b). InfraNodus: Generate Insight with AI and Network Thinking. https://infranodus.com/

ͼ΀΄ͺ΄͑傕伨瓝俬眔瑠. (n.d.). https://kosis.kr/search/search.do Low, W., Cao, M., De Vos, J., & Hickman, R. (2020). The journey experience of visually impaired people on public transport in London. Transport Policy, 97, 137–148. https://doi.org/10.1016/j.tranpol.2020.07.018 Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2017). Saturation in qualitative research: exploring its conceptualization and operationalization. Quality & Quantity, 52(4), 1893–1907. https://doi.org/10.1007/s11135-017-0574-8 Svendsen, K. J. (1994). The Use of Light Rail or Light Rapid Transit Systems by Individuals with Severe Visual Impairments. Journal of Visual Impairment & Blindness, 88(1), 69–74. https://doi.org/10.1177/0145482x9408800109 傕瓈偸瓝您͙͑ͣͣ͑͟͡͡͝ͲΡΣΚΝ͚͑ͣͤ͑͟偸瓝熜堄͑嚘檜瑘͑兘彀͑嘨氹偸瓝͑檜槑昌琄͑悬摅͑碀尐͑敀囬傴͑ ͨͤ͡ 峴͑ 嶭檜͑ ͩͥͦ͢͝ 峴侜檀͑ 嘨氹偸瓝橬͑ 檜槑͑͟ 嘨碄弤傕͑ 欽潭愴峔硹͑͟ https://www.korea.kr/briefing/pressReleaseView.do?newsId=156386894 徽歄激͙͑͟Ο͟Ε͚͑͟͟櫍梈檠͑盠檀轼侜伽注槸͑ͯ͑櫍梈檠͑盠檀轼侜伽注槸͑佄榼͑ͯ͑櫍梈檠檀͑佄呸͑強͑ 堙宅͑ 堙͑ ͯ͑ 櫍梈檠檀͑ 佄呸͑ ͙怠幠͚͑ έ͑ 潦兘斔槜͑ 搅禄徽孡欽怜͑͟ https://easylaw.go.kr/CSP/CnpClsMain.laf?popMenu=ov&csmSeq=1003&ccfNo=1&cciNo=1&cnpC lsNo=1&search_put=

Devising a Framework for Nudge Applying Behavioral Psychology Author 1

Author 2

In, Jenny

School Name

Hankuk Academy of Foreign Studies

Full Name

Kim, Minchei

Hankuk Academy of Foreign Studies

Full Name (Last Name, First Name)

(Last Name, First Name)

School Name

ABSTRACT: Behavior design is a way of shaping a desired behavior by changing the system or the placement of objects, without directly demanding specific actions upon people. Although it is prevalent in everyday life, there is a great lack of a generalized theory. This study proposes Judgment Circuit Theory as a frame for behavior design. It was devised by generalizing behavioral design cases in the fields of behavioral psychology, behavioral economics, and TRIZ. Judgment Circuit Theory is classified into two main categories: Value Judgment and Stability Judgment. Furthermore, it includes eight sub-categories: Praise and Punishment, Affection, Mind Circuit, Human Environment, Feedback and Realization, Attention-Getting, Message, and Environment. To test the efficacy of Judgment Circuit Theory, two experiments on each main category were conducted in the self-laundry room of the dormitory. Many students often forget to take their laundry immediately, causing other students’ inconvenience. The results demonstrated that both Value Judgment and Stability Judgment effectively shortened the time it took to pick up the laundry, and the latter was more effective in this particular situation.

KEYWORDS: Behavioral psychology, Behavioral economics, Behavior design, Judgment circuit theory

პ ,1752'8&7,21 Designing human behavior is inducing positive behaviors by changing the system or arrangement of objects, without forcing or directly telling people to do specific actions. It may sound like brainwashing or manipulating, but it happens every day and every time. Almost everyone would have experienced it. If you have asked yourself “why did I act like this?”, behavior design can be the answer to the question. For example, most people buy a sanitizer that says it can kill 99% of virus, rather than the one that says it leaves only 1% of virus. Some toilets have a picture of a fly on it to make people unconsciously aim it, and small cheap candies are always right next to the counter to make people easily buy it. Every factor that makes individuals want to take action is a work of behavior design. However, there was no generalized law for behavior designing. Each case had a suitable method, and there were only small parts of generalization of it. Fortunately, most methods introduced by the books were repeated since behavioral psychology is not such an old discipline. We decided to analyze the cases and create a generalized method. This report will provide specific steps and examples of making and conducting the behavior designing theory. We studied behavior design and gathered specific cases of behavioral economics, Nudge, TRIZ, and psychology. Then, with common aspects among the cases, we generalized examples and grouped similar methods to make a theory. We found two main categories and eight sub-categories, and we named the whole method as Judgement Circuit Theory. We also applied it to a real problem: selflaundry service. To solve it, we planned two experiments that include two primary standards of Judgement Circuit Theory: value judgment and stability judgment.

ჟ 7+(25< 0$.,1* 1. Studying Existing Theories (1) Behavioral Economics Behavioral economics, in simple terms, is the study of rational and irrational humans. Among the subfields, system designing is closely related to the Nudge, which induces positive results by changing the system or arrangement of objects without forcing or directly telling people to do specific actions. In Nudge, it is essential to let people do whatever they want and avoid the designed system easily. Choice architects, people who design the system, should only try to block their choice or cost them a lot if they change their actions. Economics’ premise is that people are rational; however, behavioral economics provides many examples that prove people also have irrational aspects. One of the key theories about it is loss aversion. According to it, people feel that the loss is about twice as significant as the gain, though they both are the same price, which does not make sense if people are only rational. Broken windows theory is also known as an important theory. It is made from the experiment: The researchers placed two used cars on a clean and comparatively dirty street, respectively. A day later, almost every part of the car on the dirty street was stolen, but nothing happened to the car on the clean street. This shows how important the environment is and how irrational people are. Based on this theory, system design has been developed over recent history and applied to daily life. Well-known example from Nudge is that attaching a fly sticker to the toilet helps people use it cleaner as people tend to aim the fly, as mentioned above. Also, setting a default option induces people to keep the option; food arrangement affects the consumption of particular food for a maximum of 25%, and people use much fewer unnecessary towels when they are told that the ‘others’ are also practicing it.

(2) Psychology Psychology is a study of the human mind. It focuses on feelings, thoughts, behaviors, consciousness, unconsciousness, and more. There are a lot of famous psychological ideas such as Piaget theory of development, defense mechanism, hierarchy of needs, and the Hawthorne effect. Also, lots of schools that have unique viewpoints are present. They include thoughts like biological, cognitive, social, behavioral, psychoanalytic ones. (3) TRIZ and Game Theory TRIZ is a method to solve the problem by defining the contradiction and using the shift of the thinking and patterned solution. Contradiction is a situation where we cannot select between two aspects because it has completely different characteristics. An example of the contradiction can be “a gentle torture.” It can be divided into two: technical contradiction and physical contradiction. Technical contradiction is a case where one element’s characteristic worsens when we want to improve the other element. An example is “The iron has to be hot and not hot (to keep the clothes from burning).” Physical contradiction, the other one, is that one element has to have two different physical quantities simultaneously. For example, “The iron must be in contact with the clothes to iron them, and not with the clothes to avoid burning them.” The method to solve this contradiction using TRIZ is using 40 invention principles. The 40 principles of the invention are Segmentation, Extraction, Local quality, Asymmetry, Consolidation, Composite material, and more. The first case of technical contradiction, "The iron has to be hot and not hot,” can be solved using the method of Russia’s ancient TRIZ. We can find four principal inventions in the contradiction matrix 22, 33, 35, and 02 - and select the best appropriate method, 35. By transforming the properties of matter, we can invent steam iron. In the second case of physical contradiction, “The iron must be in contact with the clothes to iron them, and not with the clothes to avoid burning them,” we can solve this using a Korean practical TRIZ. Using this, we can make the boundary area visible in the schematic chart and find the physical contradiction, solving it by inventing the spring iron. TRIZ mind map develops the TRIZ’s problem-solving process using the mind map. The case it used can be “Prevention of suicide.” This is a non-technical case, and we use the ‘element-interaction technique’ to solve this. There are two factors in this technique, which are element and interaction. Element is about two primary ingredients that are needed for problem-solving. Element 1 should be selected as something that can affect Element 2. Interaction is a relationship that occurs between the two elements. TRIZ mind map can be used to visualize and solve the problem.

Figure 1 75,= PLQG PDS

Game theory studies mathematical models of strategic interaction among rational decision-makers. It is a mathematical approach of ‘all people make the best choice.’ A person or a certain company does some actions; it affects the reality as it is in a game. Then, in that situation, this theory studies the best choice people make in the mathematical aspect. Game is the action that the players do to gain the best rewards.

The elements of the game are actors, strategy, and payoff. Actors are participants, strategy is actions that the participants can do, and the payoff is rewards that the participants get by their strategy’s combination.

2. Generalizing Examples The next step of making a theory is classifying behavioral design cases and generalizing the examples. In behavioral economics, there were cases: an award and punishment, setting the environment, using things easily if one got it quickly or suddenly, letting people own it, making it a game, using others, making innocent people disadvantaged due to one’s wrong action, and letting one have others do not. In psychology, there is a correlation between touch and affection; the environment affects people’s psychological behavior, the repetition of studying effect, and childhood affection deficiency. TRIZ included the following examples: segmentation, local quality, consolidation, preliminary counteraction, preliminary action, preliminary compensation, reverse, inversion, and feedback copying homogeneity. We generalized all the specific cases into eight sub-categories: Praise and Punishment, Affection, Mind Circuit, Human Environment, Feedback and Realization, Attention Getting, Message, and Environment. Then, we generalized sub-categories into two main categories: Value Judgment and Stability Judgment.

3. Judgement Circuit Theory Most of all, Judgment Circuit means the circuit of perception for the alteration of action, which makes people change their behavior. As shown in Figure 2 with a case of Praise and Punishment, it begins with people having default behavior. If a researcher provides a condition that offers benefits for the desired behavior, people will judge if it is really a benefit. When people fulfill that condition by doing the desired behavior, they will get the reward that boosts the desired behavior again. By repeating this process, people eventually get new behavior.

Figure 3 -XGJHPHQW Circuit

Figure 2 -XGJPHQW &LUFXLW 7KHRU\

In Judgment Circuit Theory, there are two main categories that are colored purple in Figure 3. The eight sub-categories are colored blue, and the specific cases of each sub-category are colored red to yellow. The two main categories are divided by sorting the motivation of action. Value Judgment judges which option is more beneficial, and the motivation for behavioral change is an advantage. People choose new actions when they can get a benefit, but if not, they keep their original behavior. Praise and Punishment and Affection are classified as Value Judgment. Stability Judgment is about how people can feel stability. Common sense, moral custom, and social mood can be the things that people have to fit in to feel stability. People change their actions to feel stability in a crowd with the same behaviors, and there were lots of examples in Psychology. Human Environment, Feedback and Realization, Attention Getting, Message, and Environment are grouped into Stability Judgment. Praise and Punishment would be the most familiar one. It means giving praise, or reward, for encouraged action and punishment for discouraged action. Experiencing small successes or offering benefits right after actions are included. For a simple example, to make kids sleep earlier, we can praise the one who does. Then, kids will go to bed early to get it. It shows that Praise and Punishment have the most external motivation for designing behavior, and it is the most obvious option in Value Judgment. Affection creates affection for a particular thing so that people can think they have an advantage or benefit. It includes making people own something, letting them make their own things, and giving special things. For example, most people prefer DIY products over factory-made products. Their attitude about the object or situation can be changed by making bondage with a particular object. Moving on to Stability Judgment, Environment is the ultimate option for it. It can be considered as the background of surroundings for an action, which can differ from nation to nation or era of society. It includes controlling encountering numbers, changing order and shape, using the default option, simplifying the option for faster decision, and taking out of sight. The candies near the counter is an example of changing order. It is the most internal way of altering behavior. Message, the next one, might be confused with Environment, as they are both backgrounds for changing behaviors. Message is more specific and direct. It includes every case of giving people indirect messages. Giving the metaphor, using collective unconscious, framing of words, and giving pressure visually or emotionally are all included. The different phrases for hand sanitizer advertisement is an example for it. Attention Getting sets an awkward factor and makes people check it again. It makes people feel alienated and want to solve it. For example, suddenly stopping talking makes the content more memorable. Similarly, if the speaker wants the audience to focus more on his speech, stopping while talking about the important sentence can change the audience's behavior. Feedback and Realization designs the behavior by making people realize the situation by feedback and modify the actions. It includes giving feedback, using a mirror, and re-asking a question. An example is a little box asking “Are you sure?” when a system detected bad words. The last category of Stability Judgment, Human Environment is a provided environment made among humans. Making an appointment and making a group with the same goal can be examples. Gathering friends with the same goal would be one way to make a healthier morning routine. Using human environments shows a high rate of implementation. People stimulate each other, which becomes an excellent motivation for designing behavior. Finally, Mind Circuit is the middle of the two judgments. It usually uses both of them. For example, stimulating game psychology not only gives motivation but also makes people unstable-minded so they can change their behavior instantly. Inducing behavior from small separated behavior is a crucial case.

Judgment Circuit Theory helps analyze and model many cases of behavioral psychology, especially when we need to compare the effectiveness of specific cases. For example, when the government should advertise trash recycling, they can say "You can have an environmental advantage with recycling!” or “You should recycle your trash to fit in this society!”. In this situation, suggesting benefits will be more effective than just warning them to be an ethical citizen. The Judgment Circuit Theory can be used to design the best situation.

რ Application 1. Pre-survey

Figure 4 ([SHULPHQW VLWXDWLRQ

To apply Judgment Circuit Theory, we listed in-school problems, such as annoying noise, energy waste, lining problems in the school cafeteria, a lost-and-found system, a parcel system, recycling, rubbish on the ground, elevator usage, and violent word use. Among many problems, we chose one about the self-laundry service. The dormitory provides self-laundry service on the weekend. However, students must remember to pick up their laundry, but they usually forget about it. It interrupts other students’ opportunities to do the laundry. Also, the dormitory had to make frequent announcements for students to pick up their laundry, which bothered other students. To solve this problem using Judgment Circuit Theory, we planned the experiment.

At first, a pre-survey was conducted. How many times students experienced the delay and how uncomfortable they felt are asked. The first question is related to the Value Judgment, and the second one is related to the stability Judgment. In the survey, 29.2% of students answered they had experienced a delay three times. 16.9% answered five times, and 13.8% answered once. Students who have experienced delay four times were 10.8%, and those who experienced delay two times were 9.2% of the whole. Other students answered that they experienced delays every time when using the service or other similar responses. In the second question, 33.8% of students said they feel very uncomfortable when they experience a delay. 29.2% of students answered that they feel uncomfortable, and 18.5% said they do not mind. Students who feel comfortable or very comfortable were 18.5% of the whole.

Figure 6 3UH-survey question 2

Figure 5 3UH-survey question 1

2. Experiment There were two experiments, each on Value Judgment and Stability Judgment. We wanted to determine which judgment was more effective in this situation. In both cases, we requested students to write the time when they put in the laundry and when they pick it up on the list attached to the washing machine. Each experiment also required them to write one different thing. In the first experiment about Value Judgment, we made them write their name to let students know who was the next or previous student and who delayed the system. Since they were conscious about their reputation and social relationships, they would try their best to be on time, not to be defined as a selfish person. Therefore, Praise and Punishment was the main factor, and the praise was good social status while the punishment was the opposite. Students who picked up the laundry on time fulfilled the expected conditions. As a reward, they received a good reputation. The second experiment was about Stability Judgment. We required students to write the expected time for laundry, so that they could feel guilty about their delay and get it on time to solve this uneasy feeling. We also attached visual messages that reminded students about bringing back the laundry to give them pressure to pick it up. Therefore, Message and Feedback and Realization were the main factors.

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In the Value Judgment experiment, a list that required a name, a putting time and pick-up time, a pen and a clock were needed. We informed students to fill out the form when they did the laundry. After students put their clothes in the washer, they must write their name and time. Then, students would come down and pick up their laundry when it was over. They had to write the time when they got their clothes. The Stability Judgment experiment proceeded with a poster for visual aids, a list that requires expected time, putting time, and pick-up time. We designed posters in a way that we have learned from Nudge. Similar to the first experiment, students had to write the expected time on the washer and putting time. When their laundry was done, they had to pick up and write pick up time.

Figure 9 ([SHULPHQW VLWXDWLRQ

3. Post-survey The last step was post-survey. We asked which method they preferred to the students who participated in the experiment by making them check if they had written the list during the experiment period. 41% of students preferred Value Judgment while 28% preferred Stability Judgment. 31% did not care.

Figure 10 3RVW-survey question

4. Results Before analyzing the experiments, we figured out that the self-laundry system takes 30-50 minutes, so we set 40 minutes as the time to finish the laundry. Each delayed time was calculated in the following way: (Time taken) - (40 minutes). The average time for picking up the laundry was calculated in the following way: (Time taken) / (Number of the students). Also, we found that it took about 101.85 minutes to pick up the laundry without any condition. Throughout the Value Judgment experiment, we expected students to care about their social fame by writing their name on the list on the washer. We found that the time taken to pick up the laundry became about 63.05 minutes, and about 38 minutes were reduced. One student said, “This experiment was helpful. Thinking other students might see me writing the time, it made me pick up on time. With the Stability Judgment experiment, we expected students to feel pressured by writing and realizing the delay, and the time taken had been reduced to 55.91 minutes. It was more significant than Value Judgment experiment.

Figure 11 7LPH taken WR SLFN XS WKH ODXQGU\

,9 ',6&866,21 We generalized examples and skills of behavioral economics, psychology, TRIZ, and Game Theory to devise Judgement Circuit Theory. We first divided the generalized categories into two groups: value, which is about personal benefit, and stability, which is about recognition in relations. Based on this circuit, we designed two experiments. In both experiments, we had students write putting time and pickup time. However, for the Value Judgment experiment, they had to write their name in addition to these so that they could consider their reputation and try to protect it by picking up their laundry on time. For the Stability Judgment experiment, they had to write the expected time for laundry instead of their name, which gave them mental pressure to shorten the delay time. These two experiments shortened the time taken to pick up the laundry by 38 and 46 minutes, respectively. Also, the Stability Judgment was more helpful in making students pick up their laundry on time. However, in our post-survey, students preferred how the Value Judgment works. This can be interpreted in many ways: students who focused on their emotions may have preferred value judgment with less guilt, or students who focused on making others take the laundry early may have preferred value judgment related to others' reputation. This research has meaning in that it tried to generalize the methods of behavior design. Since we were only able to test the theory in one case, it is necessary to apply this theory in more diverse situations and develop it in a more effective way.

REFERENCES Ayres, Ian. Carrots and Sticks: The New Science of High-Powered Incentives. Bantam, 2010. DK. The Psychology Book. DK Publishing, 2015. Go, Seokgyun. Pyeonuijeom e Gan Meongcheonghan Gyeongje Hakja. Chaekdeul Ui Jeongwon, 2019. Thaler, Richard H., and Se-yǂn Pak. Ttokttokhan Saramdǎl Ǎi Mǂngch’ǂnghan Sǂnt’aek: Kyǂlchǂngjǂk 1%, Saso Hajiman Ch’imyǂngjǂk Hǂchǂm Ǎl Kongnyak Hara = Misbehaving: The Making of Behavioral Economics. Ridǂsǎ Buk, 2016. Thaler, Richard H., and Seyeon Bak. Haengdong Gyeongjehak. Ungjin Jisik Hauseu, 2021. I., Wanbae. Sam Ui Mugi Ga Doeneun SSEULMO Inneun Gyeongjehak. Buk Teurigeo, 2019. Kahneman, Daniel, and Ch’ang-sin Yi. Saenggak E Kwanhan Saenggak: Uri Ǎi Haengdong Ǎl Chibae Hanǎn Saenggak Ǎi Pallan. Kimyǂngsa, 2018. R., Thaler, Richard. H & Sunstein, Cass. Nudge: Improving Decisions about Health, Wealth, and Happiness. Penguin Books, 2009. Lewis, Bradley. Moving beyond Prozac, DSM, and the New Psychiatry: The Birth of Postpsychiatry. University of Michigan Press, 2010. Ikegaya, Yuji, and Suji Seo. Sesang Eseo Gajang Jaemi Inneun 63 Gaji Simni Silheom. Saram Gwa Namu Sai, 2018. Naito, Yosihito, et al. Sesang Eseo Gajang Jaemi Inneun 88 Gaji Simni Silheom. Saram Gwa Namu Sai, 2020. Kang, Hyǂn-sik. Hanbǂn Ilgǎmyǂn Chǂltaero Itchi an Nǎn Simnihak Kongbu: Haeksim Kaenyǂmǂ 160-Kaero Salp’yǂbonǎn Simnihak Ǎi Modǎn Kǂt. Meit’ǎ Puksǎ, 2019. VandenBos, Gary R. Apa Dictionary of Psychology. American Psychological Association, 2015. Oh, KyeongCheol. 7UL] 0LQG 0DSࣟ $ 7UHH 7KDW 2SHQV <RXU 0LQG. BM SeongAnDang, 2AD. Watanabe, Dakahiro, and Mijeong Gi. Dohae Geim Iron. AK Trivia Book, 2014.

Assessing the State of Mental Health Among Prisoners and the Accessibility of Mental Management Centers Across States in the United States Author 1

Full Name

Jung, Selice

HPrep Academy

(Last Name, First Name)

School Name

ABSTRACT: In the era of mass incarceration, the health implications of prison environments are profound. The high rates of incarceration coupled with confined conditions in prisons create substantial challenges for prisoners’ mental health. Mental health disorders are significantly higher in the prison population than in the general population, with nearly half of all inmates in state prisons suffering from a mental illness. Carceral settings like overcrowding, family disconnection, solitary confinement, and lack of healthcare access contribute to the alarmingly high rates of mental health disorders among prisoners. Specifically, based on previous research, the lack of healthcare access in prisons is framed as one of the key factors in poor mental health among prisoners. Consequently, understanding the relationship between the two variables is essential in supporting the mental well-being of prisoners. To investigate the relationship between the accessibility of mental management centers and the mental health of prisoners, state-level data are collected from national reports and online databases to be analyzed using geographic information systems (GIS). The results suggest a slightly negative correlation between the density of mental management centers and rates of mental health disorders and suicide among prisoners. These findings provide room for further inquiry in related fields and raise suggestions on interventions to promote the mental health of prisoners through enhanced access to mental healthcare services.

KEYWORDS: mental health; mental management centers; healthcare access; prisoners; bivariate analysis; comparative analysis

Introduction For over two decades, the United States consistently maintained its position as the country with the highest incarceration rate worldwide, with an overwhelming population of nearly two million inmates. This trend began in the 1970s with rising crime rates that instilled fear and unease among the public, thereby adding momentum to the desire of politicians to push for stricter crime policies with increasingly punitive measures. Specifically, President Lyndon B. Johnson was an early advocate for the “War on Crime” to combat the rising crime rates by stricter law enforcement. This approach was followed by the “War on Drugs” under President Nixon and Reagan with aggressive law enforcement and penalties for drug offenses. Furthermore, the implementation of mandatory minimum sentences, truth in sentencing laws, and the “Three Strikes (and You’re Out)” law only aggravated the situation of mass incarceration. Consequently, over 1 in 100 individuals in the United States are currently incarcerated in either prisons or jails, as reported by the Prison Policy Initiative. Along with mass incarceration followed an elevated prevalence of mental illnesses, making prisons and jails the largest mental health providers in the United States (Connors, 2022). Over the years, concerns about the precarious well-being of prisoners, particularly their mental health, have intensified due to strikingly high rates of prisoners with mental illnesses not receiving proper medical attention. The prevalence of mental health disorders in prisons has been substantially higher than that of the general population. Prisons have a mental illness rate about four to seven times higher than the noninstitutionalized population. Over half of all state prisoners have a mental illness, while about 1 in 5 U.S. adults have one (“Incarceration Nation,” 2014; “Mental Health,” 2021). Regarding serious mental illnesses (SMIs), while 1 in 4 prisoners suffer from a serious mental illness, the rate falls to 1 in 20 among the general population (“Incarceration Nation,” 2014). Based on the statistics, the mental illness rate in state prisoners is more than double that of the general population, and the rate for serious mental illnesses in state prisoners is nearly five times that of the noninstitutionalized population. The high prevalence of mental health disorders among prisoners has already been well documented, but less is known about why this phenomenon occurs. Based on previous research, some factors that contribute to such a trend are overcrowding, family disconnection, solitary confinement, and lack of healthcare access. Despite such a large proportion of prisoners having mental illnesses, healthcare is often limited, especially in prison infirmaries. Simply requesting to see a doctor may take several days, and paying a fee for the treatment is often unaffordable for prisoners. As such, many prisoners with mental health illnesses are left untreated, putting them at a higher risk of suicide, recidivism, and worsened mental health both during and after incarceration. To address the needs of prisoners with mental health problems, state-level data on mental health disorder rates and suicide rates will be used to find a correlation between the density of mental management centers and mental health. The main source of data is from the Bureau of Justice Statistics (BJS) and Integrated Public Use Microdata Series (IPUMS) on prisoner health outcomes and the location of mental management centers across the 50 states. Four analyses are run with the data: 1) assessing and mapping the suicide rate in prisoners across states, 2) assessing and mapping the accessibility of mental management centers for prisoners across states, 3) investigating the correlation between suicide rates and availability of mental management centers, and 4) suggesting future policy implications to address the lack of mental health support for prisoners and enhance the mental health of prisoners. All analyses are visually presented with choropleth maps and scatterplots. Findings show that there is a negative correlation between the density of mental management centers and mental health among prisoners. The strength of the correlation varies among states. Some states show a strong negative correlation, while some do not follow the expected trend. These results ultimately inform questions on adequate healthcare provisioning for prisoners’ mental health, which will be further explored by suggesting policy measures on extending mental healthcare provision for prisoners.

Literature Review Impacts of Incarceration on Mental Health Outcomes of Prisoners For decades, multiple findings have demonstrated how incarceration has taken a toll on the health of prisoners. The incarcerated experience not only exacerbates existing health conditions but also places individuals at a heightened risk of developing new ones. To begin with, measurable indicators of poor mental health in prisoners have been well documented in the extant literature. Morgan et al. (2022) found that in Washington, suicide rates are profoundly higher in those who have been through the incarcerated experience. While formerly incarcerated individuals were found to have a suicide rate of 36.3 per 100,000, those who have never been incarcerated had a rate of 17.2 per 100,000; suicide rates for formerly incarcerated individuals were over twice those for non-incarcerated individuals. Furthermore, prisoners in Washington were 12.7 times more likely to die during the first two weeks after release due to drug overdose, cardiovascular disease, homicide, and suicide (Binswanger et al., 2007). Such high suicide rates can be attributed to the unusual prevalence of mental illnesses among inmates (Goss et al., 2002). Indeed, Torrey et al. (2010) found that jails and prisons in the United States hold more mental health patients than hospitals. Such high rates of mental health disorders in prisons can be attributed to conditions like overcrowding, family disconnection, and solitary confinement. Existing mental health conditions can be exacerbated by the lack of healthcare provision in prisons due to the poor quality of healthcare, the exclusion of prisoners from insurance policies, and restrictive access. The first factor of consideration is overcrowding, a pervasive issue in many of the prisons in the United States. As of 2019, the Prison Policy Initiative (PPI) revealed that state prisons in 20 states out of 50 were operating over their capacity (over 100%), and state prisons in 9 states were operating at over 90% of their capacity (Widra, 2020). With so many state prisons operating at nearly their maximum capacity or over, overcrowding is a rising concern in prisons due to the adverse impacts it has on the health of prisoners. Indeed, excessive overcrowding in prisons was deemed unconstitutional in 2011 after the U.S. Supreme Court ruled that California’s prison system, which housed more than twice its capacity, violated the Eighth Amendment to the Constitution in Brown v. Plata due to overcrowding leading to inadequate mental health care (Newman and Scott, 2012). Specifically, overcrowding leads to less access to healthcare and poor health outcomes among prisoners, in turn generating more suicide deaths (Huey and Mcnulty, 2005). Adding on, family disconnection in prisons leaves prisoners at high risk for depression; a nationally representative study revealed that inmates whose home was more than 50 miles from the prison were more likely to develop depression (Edgemon et al., 2018). Depression, in fact, is the most prevalent mental illness in prisons with nearly 1 in 3 state prisoners diagnosed with a major depressive disorder (Maruschak et al., 2021). Third, solitary confinement (restrictive housing) has been found to significantly alter prisoners’ mental health. With about 1 in 16 inmates in solitary confinement, preventing the severe mental alterations of inmates has become more alarming than ever (Casella, 2023). Solitary confinement generally refers to the physical isolation of individuals in cells with minimal to no interactions with others (“Solitary confinement”). After interviewing solitary-confined inmates in Walpole, Massachusetts, Grassian (2016) found that inmates in solitary confinement had strikingly consistent and specific psychiatric symptoms. Such include perceptual distortion, illusions, and hallucinations in a third of the prisoners, panic attacks and overt paranoia in over half, and loss of impulse control in nearly half of the prisoners (Grassian, 2016). Inmates described their experience as “I seem to see movements, real fast motions in front of me … I dwell on it for hours,” and “I cut my wrists many times in isolation…” (Grassian, 2016). Prisoners in solitary confinement report a variety of mental health disorders, many of them later developing into severe mental functionality impairments.

Finally, the lack of healthcare access in prisons leaves ill prisoners without appropriate care and treatment. Wilper et al. (2009) carried out a nationwide survey to investigate disease prevalence and access to healthcare in inmates and found that 1 in 5 inmates (20.1%) in state prisons with persistent medical problems received no medical examination since incarceration. In terms of medication, 28.9% of inmates in state prisons who were taking prescription medication for some reason when they entered prison stopped taking the medication following incarceration, and 24.3% of inmates with active medical problems routinely requiring medication stopped the medication after incarceration. For mental health issues, on the contrary, inmates received more medical attention. While only 1 in 3 (29.6%) inmates with a mental health diagnosis were taking psychiatric medication at the time of arrest, more than 2 in 3 (68.6%) inmates who had been treated with a psychiatric medication in the past took medication during incarceration. Even though certain health issues are better treated than others, prisoners generally receive improper health care, leaving them untreated. Making matters worse is the inmate exclusion in insurance policies. Public insurance plans like Medicare and Medicaid do not cover medical fees for inmates while they may still be enrolled. Furthermore, inmates are not permitted to use the marketplace to purchase private insurance plans either (“Health Coverage”). With prisoners being denied access to various medical health coverage options, their only option is to seek healthcare in prisons. In Estelle v. Gamble (1976), the Supreme Court of the United States ruled that the deprivation of healthcare to prisoners was cruel and unusual punishment, thus violating the Eighth Amendment to the United States Constitution (Paris, 2008). Estelle essentially established a de facto right to healthcare for all prisoners. However, even after 40 years of the ruling of Estelle, not all prisoners receive appropriate health care based on their needs. Due to the absence of a manual with specific guidelines on what is deemed “appropriate care,” all prisons provide differing quality of health care (Gardner, 2022). Many states provide inadequate healthcare to prisoners, mainly through restrictive access and financial strains. Restrictive access refers to the barriers that prisoners face when they are seeking medical attention. As Wang (2023) mentioned, inmates must go through a correctional officer to determine whether there is a medical necessity, and only after it is considered to be a necessity can inmates see a physician. However, as a prisoner in Louisiana mentioned, “If the guard felt like there was nothing wrong with you, you wouldn’t even see the nurse” (Wennerstrom et al., 2021). Prisoners rarely get to receive any medical attention until conditions are severe and they are on the verge of death: “You have to be almost dead before they ever really work on you in prison” (Wennerstrom et al., 2021). A more substantial factor is the financial strain placed on prisoners due to many states (40) charging a copayment (copays) for medical care services (Avila, 2022). The copayments’ original intentions are to compensate the states for the high cost of medical care for prisoners who have pre-existing health conditions and prevent prisoners from seeking medical care when not needed (Sawyer, 2017; Ollove, 2015). However, the high fees are only deterring prisoners from obtaining necessary medical attention. Medical copays cost around $2 to $5, but some states like Texas charge up to $13.55 per visit. In hindsight, a $2 to $5 fee may seem inexpensive, but for prisoners who have an average hourly wage of 14 to 63 cents, paying for the copay is undoubtedly a significant obstacle for prisoners who are seeking immediate care (Sawyer, 2017). As a formerly incarcerated woman with firsthand experience in prison noted, “Some people don’t even go to the doctor because they’re going to be charged [,] and it’s already hard surviving incarcerated” (Wennerstrom et al., 2021). In eight states (Alabama, Arkansas, Florida, Georgia, Mississippi, Oklahoma, South Carolina, and Texas), no payment is given to prisoners despite their labor (Kent State, 2021). When applied to the noninstitutionalized society, a minimum wage worker would have to pay an average of $208.25 for medical copay (Sawyer, 2017); this number is 8 to 14 times higher than the average copay per visit in the general population ($15 to $25) (Fay, 2020). Adding on, the quality of medical care is often poor in prisons, with only one or a few physicians (Wennerstrom et al., 2021). Khan, a formerly incarcerated person who was wrongly convicted of a crime and spent 16 years in prison, mentioned that when a dime-sized bald spot suddenly appeared on the back of his head and went to the infirmary, they responded, “Oh, it’s alopecia, and here’s a [Wikipedia] printout of what it is. There is nothing we can do” (Ahébée, 2021). Further, mental health diagnoses are often poorly made: when a prisoner visited a psychiatrist, the only response she received was, “Yeah, you’re depressed,” and was prescribed an antidepressant pill that was not even necessary (Wennerstrom et al., 2021). Therefore, existing research well illustrates the adverse impacts of incarceration on the mental health of inmates, with both quantitative and qualitative studies indicating the negative health effects of

prison conditions on prisoners’ mental health.

The Relationship Between Mental Health and Accessibility of Mental Management Centers To prevent prisoners from facing disproportionately high rates of mental health disorders, investigating underlying factors for the unusual prevalence of mental illnesses seems necessary. As discussed earlier in the literature review, previous studies have indicated a direct correlation between healthcare access in prisons and the mental health status of prisoners. Despite rates of mental illnesses in prisons having increased over the past few decades, the number of psychiatric beds and mental health spending by states has decreased (Prins, 2015; Lamb, 1998; “Funding for Mental Health Services”). Healthcare is highly restricted for prisoners who require immediate attention and are under financial strain (Levins, 2023). The general procedure for healthcare access in prisons is as follows. First, if an inmate sees the need to visit the doctor, a correctional officer has to determine whether it is a medical necessity or not. If the condition is deemed a medical necessity by the correctional officer, then the inmate gets to see a nurse. Last, only after the inmate sees a nurse can he or she meet an actual physician (Levins, 2023). In other prisons, inmates can be required to send in a written request to the infirmary, but approval for this request often takes several days, and there is no guarantee that the request will be accepted either (“Medical Care”). Even before seeing a physician, there are multiple barriers hindering prisoners from receiving immediate care. Adding to this are the financial barriers as mentioned previously. With a mandatory copayment that is often unaffordable, prisoners avoid seeking medical attention, even when urgent. Another barrier presented to prisoners is scheduling medical appointments. Since all movements of inmates have to be recorded and controlled, medical appointments require multiple factors to align. For example, officers and transport from prisons are needed when a prisoner schedules a medical appointment. Providing all such resources for a single medical appointment is seen as a burden to the prison authorities, and processes are thereby delayed (Ahébée, 2021). However, even when prisoners do gain access to medical care, qualities tend to be poor, with some physicians and psychiatrists in infirmaries giving wrong diagnoses or medication (Ahébée, 2021; Wennerstrom et al., 2021). As the lack of healthcare provision in prisons suggests a higher prevalence of mental health disorders, diving deeper into the relationship between the two variables serves as an invaluable investigation. When referring to mental healthcare, multiple factors have to be considered. As Fraser et al. (2009) point out, health care alone is insufficient to provide comprehensive mental support due to the multi-layered nature of mental health disorders among prisoners. In other words, only prescribing medication like antidepressants or antipsychotics is not an adequate measure to manage the mental health of prisoners. Prisoners, in particular, are exposed to a multitude of factors that account for their mental health state like poor housing, relationships, poverty, and past traumatic events (Fraser et al., 2009). However, many prison infirmaries lack support groups or counselors who can help maintain and improve the mental health of prisoners. Indeed Norris et al. (2022) interviewed a former inmate in Arkansas who said, “It’d be nice to have more counselors … and see us more often than once a month.” With the lack of healthcare access being a significant barrier for prisoners from improving their mental health, the main factor of consideration here is mental healthcare access, namely the accessibility of mental management centers. Even though the lack of access to healthcare has been pointed out in multiple studies, a direct, explicit link between access to healthcare and mental health has not yet been examined. As such, this research explores the direct link between the two variables to indicate a bivariate relationship that will serve as a valuable tool in enhancing the mental health of prisoners.

Data and Methods Research Design This research employs online databases to obtain relevant data on the incarceration rate, mental health disorder rate among prisoners, suicide rate among prisoners, and availability of mental support facilities for each of the 50 states in the United States. After collecting raw data from online reports on the Bureau of Justice Statistics (BJS) and IPUMS, they were repurposed to create choropleth maps for better geographical visualization. Using the choropleth maps and data plots, the correlation between specific variables was determined for individual states.

Data Collection 1) Incarceration Rates Data on incarceration rates across states were available in a report published by the Bureau of Justice Statistics (BJS) on prisoners in 2021 (Table 7). This report is part of a series the BJS has been publishing since 1926. It includes data on the characteristics of prisoners mainly based on: 1) age, sex, race, and jurisdiction, 2) imprisonment rates, and 3) other data on prisoners and correctional officers. For this research, only one of the tables was used from the report: Table 7, “Imprisonment rates of U.S. residents, based on sentenced prisoners under the jurisdiction of state or federal correctional authorities, by sex, age, and jurisdiction, 2020 and 2021” (Carson, 2022). This data provides a general overview of the extent to which states are facing mass incarceration trends and have a high prison population. To analyze the most recent trends available, only data from the fiscal year 2021 was utilized and organized in a spreadsheet (excel) format. 2) Rate of Mental Health Disorders Among Prisoners Data on the rate of mental health disorders among prisoners were obtained from IPUMS (Integrated Public Use Microdata Series). Specifically, the IPUMS NHIS (National Health Interview Survey) was used to collect data on the rate of mental health disorders. This data, too, was then organized in a spreadsheet (excel) format. The rate of mental health disorders among prisoners directly informs the general mental health status of the prison population by state. It provides a measure to assess the mental health of prisoners. 3) Suicide Rates Among Prisoners Raw data on the suicide rates among prisoners were collected from a report published by the Bureau of Justice Statistics (BJS) on suicide in local jails, state prisons, and federal prisons during the years 2000 to 2019. Specifically, extracted data was under the subject of State Prisons to analyze suicide rates for every state. From the report, data from Table 11 was extracted and then organized in a spreadsheet (excel) form. This data directly addresses the state of mental health among prisoners, as suicidal behavior is commonly observed in prisoners suffering from mental health disorders. 4) Distribution of Medical Support Facilities and Medical Management Centers for Prisoners Data were obtained from the online database IPUMS (Integrated Public Use Microdata Series). In particular, the National Historical Geographic Information System (NHGIS) was utilized to gather the addresses of mental management centers in the United States. The addresses were then converted into geographic coordinates (latitude and longitude) using geocoding. This data serves as a preliminary tool to calculate the accessibility of mental healthcare facilities by dividing the number of mental management centers by the prison population (in 1,000). It directly addresses the accessibility of mental management centers for each state, serving as one of the key variables used to demonstrate a specific correlation.

Statistical Analysis Before running the statistical analysis, all data were collected and organized in a spreadsheet (excel) format. Then, data analysis was performed using QGIS 3.32 software (Quantum Geographic

Information System). QGIS is a free, open-source software commonly used to map and analyze geospatial information. For each of the different choropleth maps, slightly differing methods were used accordingly. 1) Incarceration Rates, Rates of Mental Health Disorders Among Prisoners, and Suicide Rates Among Prisoners After adding a vector layer, a shapefile for the map of the United States was input into the software first. Then, the according statistics were organized in a spreadsheet file and were input into QGIS. The Jenks, natural breaks classification, was utilized to display the data. This method minimizes the variation within each range, while maximizing the variation between different ranges (Chen et al., 2013). Instead of the default five natural breaks, seven natural breaks were selected for a more detailed classification based on subtle differences in the collected data. The output maps were then illustrated and displayed on QGIS. 2) Distribution of Medical Support Facilities and Medical Management Centers for Prisoners Similar to the aforementioned method, a vector layer was added first, and then a shapefile for the map of the United States was attached. Instead of numerical data, addresses of medical support facilities and mental management centers were converted to geographic coordinates (latitude and longitude) using the geocoding function on QGIS. Locations for each medical facility were then pinpointed on the map, and the output map was displayed.

Results and Limitations Results

[Figure 1. Incarceration Rates Across States (per 100,000)] Incarceration rates are high in states like Mississippi, Louisiana, and Kansas, while they are low in Massachusetts, Maine, and Rhode Island. Darker shades of red indicate higher incarceration rates, while lighter shades of red indicate lower incarceration rates. This analysis provides insight into the degree to which states have to handle the issue of incarceration. Incarceration rates tend to be higher in the southeastern states, while they are substantially lower in the northeastern states.

[Figure 2. Rate of Mental Health Disorders Among Prisoners Across States (per 1,000)] Rates of mental health disorders among prisoners are highest in Texas, California, and Florida and lowest in Vermont, Delaware, and Rhode Island. Darker shades of blue indicate a higher rate and lighter shades of blue indicate a lower rate. This analysis provides a visual representation of the varying degrees of mental health disorder prevalence in prisoners, serving as one measure of mental health in prisoners. No explicit pattern is observed by geography or the location of states.

[Figure 3. Suicide Rates in Prisoners Across States (per 100,000)] Suicide rates among prisoners are highest in Rhode Island, Utah, and Alaska and lowest in Kentucky, Maine, and North Carolina. Darker shades of green represent higher suicide rates, and lighter shades represent lower suicide rates. Suicide rates serve as another indicator of mental health among prisoners, alongside rates of mental health disorders. Here, too, no explicit pattern is indicated from the geographical location of states.

[Figure 4. Distribution of Mental Management Centers for Prisoners Across States] North Dakota, Maine, and Massachusetts have the highest density of mental management centers per 1,000 prisoners. In contrast, Oklahoma, Pennsylvania, and Delaware have the lowest density of mental management centers per 1,000 prisoners. In general, many of the mental management centers are located in the northeastern states, while fewer are in the western states.

[Figure 5. Correlation Between the Density of Mental Management Centers per 1,000 Prisoners and the Rate of Prisoners with Mental Health Disorders]

[Figure 6. Correlation Between the Density of Mental Management Centers per 1,000 Prisoners and Suicide Rates per 100,000 Prisoners] Data used to generate choropleth maps were also utilized to create a scatterplot that shows the relationship between the density of mental management centers and the mental health of prisoners. The density of mental management centers was calculated by dividing the total number of mental management centers by the total number of prisoners in 1,000. Two measures of mental health employed in this research were the rate of prisoners with mental health outcomes and suicide rates per 100,000 prisoners. After plotting the data sets on the scatterplot, a trendline was added to model the general relationship between the variables utilized. Looking at Figure 5, many data sets are clumped in the bottom left corner. This implies that many have a low to medium density of mental management centers with a low rate of mental health disorders in prisoners. However, some notable outliers are present. One is Texas, which has a low density of mental management centers (5.58 per 1,000 prisoners) and surprisingly high rates of mental health disorders (915 per 1,000 prisoners). Another is California, which also has a low density of mental management centers (2.74 per 1,000 prisoners) and high rates of mental health disorders (553 per 1,000 prisoners). Along with the presence of outliers, some data points exactly aligned with the trendline. Georgia has a low density of mental management centers (7.42 per 1,000 prisoners) and a mid-range rate of mental health disorders (212 per 1,000 prisoners). Following the trendline is West Virginia, which has a median density of mental management centers (67.90 per 1,000 prisoners) and a low rate of mental health disorders (78 per 1,000 prisoners). Near the end of the trendline is Vermont which has a high density of mental management centers (101.01 per 1,000 prisoners) and an extremely low rate of mental health disorders (18 per 1,000 prisoners). In general, a downward trend is observed in the trendline, indicating a slightly negative correlation between the density of mental management centers and rates of mental health disorders among prisoners: as the density of mental management centers increases, the rates of mental health disorders decrease. In Figure 6, data sets are more dispersed, but many data set points are still clumped near having a low density of mental management centers and a low rate of suicides. More outliers are evident in this analysis. The first one is Pennsylvania, which demonstrates an extreme correlation. There is a low density of mental management centers (1.99 per 1,000 prisoners) and a staggering high suicide rate (44 per 100,000 prisoners). In fact, the suicide rate among prisoners in Pennsylvania is the highest figure in the United States. Another outlier is Texas, which demonstrates an unusually high suicide rate (43 per 100,000 prisoners) and a low density of mental management centers (6.84 per 1,000 prisoners). California, Massachusetts, and North Dakota are major states aligned with the trendline.

California has a low density of mental management centers (5.45 per 1,000 prisoners) with a higher suicide rate (21 per 100,000 prisoners); Massachusetts has a median density of mental management centers (25.86 per 1,000 prisoners) and a median suicide rate as well (16 per 100,000 prisoners); North Dakota has a high density of mental management centers (43.81 per 1,000 prisoners) and a low suicide rate (14 per 100,000 prisoners). Like Figure 5, Figure 6 also demonstrates a downward trendline with a slightly negative correlation between the density of mental management centers and suicide rates among prisoners. As the density of mental management centers increases, suicide rates among prisoners decrease.

Limitations on Data Analysis The first limitation of this data analysis was the inconsistency of the collected data. Even though the most recent versions of all data were collected and organized, not all of them were from the same year or period. For instance, while most of the data were collected from the fiscal year 2021, some were from the fiscal year 2019. This could have led to inconsistencies that reduced the reliability of the findings. A major concern of data from 2019 and 2021 is the impacts that the COVID-19 pandemic had on prison populations and prison health outcomes. During the pandemic, for instance, incarceration was implemented in some states to prevent the spread of COVID-19 in overcrowded facilities like the U.S. (Schuck et al., 2020). Thus, the difference in data from 2019 and 2021 may have been more significant than the other years, considering that the pandemic would have had substantial impacts on the number and profiles of prisoners. Future research should prioritize data consistency to produce reliable and consistent results. Second, data on the rates of mental health disorders among prisoners may not have reflected the actual proportion of prisoners. This is, in part, due to the incomplete diagnoses of mental disorders in prisons. Not only are prisoners hesitant to seek diagnoses, but the inadequate mental health screening leaves many with mental health conditions undiagnosed. As such, future research involving the mental health of prisoners would benefit greatly if the accuracy and validity of provided data on the mental health of prisoners were reviewed. Moreover, the variation in mental healthcare provision across different management facilities hinders a more accurate comparison and analysis of the availability of mental health centers. While all of them may provide psychiatric assessments and medication prescriptions, the types of therapies that each center offers differ. Even though this research only focused on the general availability of mental management facilities, future studies can include a more scrutinized review of the services provided and analyze the mental health of prisoners depending on the types of therapies offered. Finally, the capacity of each mental management center was not considered in this study. Given the overcrowding issue in numerous prisons, understanding the capacity of each facility can provide a more comprehensive analysis of the availability and accessibility of mental health support. Future studies can include a detailed quantitative analysis of the capacity of each center relative to the number of prisoners with mental health conditions to investigate the adequacy of mental healthcare services for prisoners.

Conclusion In this quantitative analytical study, the correlation between the accessibility of mental healthcare facilities and the mental health of prisoners was investigated, with a particular focus on the United States. A geographical analysis was performed to map trends across states, followed by a bivariate analysis of individual data. Overall results demonstrated a negative correlation between the two variables, indicating that higher accessibility to mental healthcare facilities is associated with lower rates of mental health disorders and suicide in prisoners. Some states represented the broad negative correlation in which limited access to healthcare access was associated with poor mental health outcomes. These states are encouraged to receive more attention on granting more healthcare access to prisoners. Other states also represented a broad negative correlation, but one in which higher access to healthcare access was associated with lower rates of mental health disorders and suicide. The mental healthcare system in these states can serve as a model for other states to address potential strategies for successfully managing mental health in prisoners. Conversely, some outliers did not conform to the

general pattern. For these states, it is encouraged that a more thorough investigation of other factors that account for an abnormal trend is made in future studies. Even though the results obtained from this research provided valuable insight into the correlation between the accessibility of mental management centers and the mental health of prisoners, two main limitations regarding the scope of the research are present. 1.

Utilization of More Variables to Assess the Mental Health of Prisoners

This research only looked into one variable, the availability of mental health management centers, on the mental health impacts of prisoners. The mental health impacts, too, were only measured through suicide rates and the rate of prisoners with mental health disorders. A more comprehensive measure of mental health impacts could be made if more variables were measured. For example, drug overdose rates could have been a possible factor in assessing the mental health of prisoners. From 2019 to 2020, opioid overdose deaths increased by a staggering 37.2% (“The Opioid Epidemic”). With a surging opioid overdose death rate each year, the opioid epidemic is sweeping populations in the United States, and prisoners are no exception. Rates of substance use disorder (SUD) in prisons are notoriously high, with 85% of the prison population having an active SUD or having been incarcerated for a drug-related crime (“Criminal Justice,” 2023). Also, Ranapurwala et al. (2018) found that two weeks after release, former inmates were 40 times more likely to die from opioid overdose. As the opioid crisis disproportionately impacts the incarcerated population, an analysis of mental healthcare facilities and drug overdose death rates would serve as valuable data to improve the health of prisoners. By doing so, a more comprehensive review involving multiple perspectives on the mental health of prisoners could be measured. 2.

Understanding the Relationship Between the Availability of Mental Management Centers and the Mental Health of Prisoners in Specific Groups (i.e., race groups and serious offenders)

This analysis only focused on the mental health of prisoners in general, not specific subgroups within prisoners. This, however, can be improved by analyzing the same relationship in specific subgroups based on race and offenses committed by prisoners. The difficulty in obtaining data for specific groups, especially by race, is the biggest obstacle in conducting this type of research. Not only are prisoner data highly limited, but prisoner data broken down by race and state are deemed confidential and not publicly reported even upon request. However, if this obstacle is overcome, valuable analysis can be made on improving the health of specific race groups, especially those of color who are disproportionately represented in the prison system. By doing so, the unique challenges that people of color face while incarcerated can be identified and prevented through appropriate interventions. Exploring the relationship based on offenses committed by prisoners would also provide deep insight into which criminal offenses tend to be associated with a higher prevalence of mental health disorders. This way, appropriate rehabilitation and treatment programs to promote mental health can be provided to specific groups of inmates. Based on the findings presented in this research, prison medical policies are encouraged to be modified and improved upon to ensure quality healthcare for prisoners and maintain their mental health. First, it is suggested that there is a system in which the prison offers mandatory mental health screening to prisoners, contrary to the existing system in which prisoners have to seek mental care if needed. Due to the presence of multiple barriers preventing all prisoners from seeking mental healthcare, prison authorities can provide free mental health screening to all prisoners regularly, preferably in the form of in-person interviews with a psychologist. Even though online questionnaires would be more costeffective and convenient, self-reporting methods tend to include a lot of bias that, in turn, generates inaccurate and unreliable diagnoses (Salters-Pedneault, 2023). Offering mental health screening in the form of in-person interviews with a psychologist would grant all prisoners access to diagnosis of mental healthcare for adequate treatment to be provided while incarcerated.

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The second suggestion is to incorporate more correctional therapists or counselors into mental health treatment programs. Despite the effectiveness of psychiatric medication, they are often costly, which could increase the copayment that prisoners are required to pay. Holding mentally ill prisoners is more costly than other prisoners, mainly due to increased resource needs, one of which is psychiatric medications (“Serious Mental Illness,” 2016). To reduce costs while treating mental health disorders in prisoners, an option would be to implement more counseling programs for psychological therapy. As Anno (2001) pointed out, supportive counseling programs tend to be significantly cost-friendlier than other types of mental health care. Former inmates themselves have also pointed out the desire for counseling sessions: “It’d be nice to have more counselors” (Norris et al., 2022). Specifically, a mixture of in-person and virtual counseling sessions could serve as a more effective option. McDonald et al. (1999) have discovered that telemedicine consultations in psychiatry are equally effective as in-person consultations. Virtual consultations are even cost-friendlier than in-person counseling sessions, as Nacci et al. (2002) demonstrated: telemedicine consultation was over two times cheaper than conventional face-to-face consultation ($71 vs. $173). In short, virtual counseling sessions can improve the accessibility of healthcare provision for prisoners by providing great convenience in receiving quality mental healthcare within the prison context. Adequate provision of mental healthcare services can improve the mental health of prisoners, which may contribute to lower recidivism rates and improvements in public health, as many prisoners with mental health disorders are released untreated. If more prisoners with mental health disorders are treated, struggles in reintegration would be reduced, contributing to lower recidivism rates and safer communities. Addressing healthcare reform in prisons can serve as a powerful means of promoting better mental health outcomes among incarcerated individuals. Specifically, unique interventions can be made by policymakers or correctional authorities to tackle specific challenges faced by prisoners in different regions.

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41. Sawyer, W., & Wagner, P. (2023, March 14). Mass Incarceration: The Whole Pie 2023. Www.prisonpolicy.org; Prison Policy Initiative. https://www.prisonpolicy.org/reports/pie2023.html. 42. Schuck, J., Backes, E. P., Western, B., & Wang, E. A. (2020, October 20). Summary. Www.ncbi.nlm.nih.gov; National Academies Press (US). https://www.ncbi.nlm.nih.gov/books/NBK 566317/. 43. Scommegna, P. (2012, August 10). U.S. Has World’s Highest Incarceration Rate. PRB. https://www.prb.org/resources/u-s-has-worlds-highest-incarceration-rate/. 44. Serious Mental Illness (SMI) Prevalence in Jails and Prisons SUMMARY. (2016). In Treatment Advocacy Center. https://www.treatmentadvocacycenter.org/storage/documents/backgrounders/smi-in-jailsand-prisons.pdf. 45. Serious Mental Illness GENERAL BACKGROUND. (n.d.). https://www.va.gov/PREVENTS/ docs/PRE013_FactSheets_SeriousMentalillness_508.pdf. 46. Steadman, H. J., Osher, F. C., Robbins, P. C., Case, B., & Samuels, S. (2009). Prevalence of Serious Mental Illness Among Jail Inmates. Psychiatric Services, 60(6), 761–765. https://doi.org/10.1176/ps.2009.60.6.761. 47. The Opioid Epidemic in the United States. (2020, August 25). State Health Access Data Assistance Center. https://www.shadac.org/opioid-epidemic-united-states. 48. Thigpen, M. L., Solomon, L., & Ortiz, M. (2001). Correctional Health Care: Guidelines for the Management of an Adequate Delivery System (2001 Edition). https://s3.amazonaws.com/static. nicic.gov/Library/017521.pdf. 49. Torrey, E. F., Lamb, R., & Pavle, J. (2010). More Mentally Ill Persons Are in Jails and Prisons Than Hospitals: A Survey of the States. In Treatment Advocacy Center. https://www.treatment advocacycenter.org/storage/documents/final_jails_v_hospitals_study.pdf. 50. U.S. Criminal Justice Data. (n.d.). The Sentencing Project. https://www.sentencingproject.org/ research/us-criminal-justice-data/. 51. Wagner, P., & Bertram, W. (2020, January 16). “What percent of the U.S. is incarcerated?” (And other ways to measure mass incarceration). Prison Policy Initiative. https://www.prisonpolicy.org /blog/2020/01/16/percent-incarcerated/. 52. Wendy Sawyer. (2017, April 19). The steep cost of medical co-pays in prison puts health at risk. Prison Policy Initiative. https://www.prisonpolicy.org/blog/2017/04/19/copays/. 53. Wennerstrom, A., Sugarman, M., Martin, D., Lobre, C. B., Haywood, C. G., & Niyogi, A. (2021). “You have to be almost dead before they ever really work on you in prison”: A qualitative study of formerly incarcerated women’s health care experiences during incarceration in Louisiana, U.S. Health & Social Care in the Community. https://doi.org/10.1111/hsc.13556. 54. Widra, E. (2020, December 21). Since you asked how overcrowded prisons were before the pandemic, and at this time of social distancing, how overcrowded are they now? Prison Policy Initiative. https://www.prisonpolicy.org/blog/2020/12/21/overcrowding/. 55. Wilper, A. P., Woolhandler, S., Boyd, J. W., Lasser, K. E., McCormick, D., Bor, D. H., & Himmelstein, D. U. (2009). The Health and Health Care of US Prisoners: Results of a Nationwide Survey. American Journal of Public Health, 99(4), 666–672. AJPH. https://doi.org/10.2105/AJPH.2008.144279.

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Opposing Common Conception: Weak Positive Relationship Between Academic Performance and Exercise Author

: Kim, Ashley

Full Name (Last Name, First Name)

School Name

: Moorestown High School

ABSTRACT: Current high school curriculums mandate physical education programs. In fact, it is well established that exercise improves overall health, and the concept of “healthy kids learn better” emerged to promote and justify the development of new physical education programs in schools. To evaluate current justifications for said programs, this study aims to investigate the relationship between regular exercise and academic performance. Three surveys were conducted, each focusing on a different group of randomly selected participants. The initial survey included 186 participants (high school students in New Jersey enrolled in honors/AP classes). Exercise is measured by the number of weekly exercise hours, and academic performance is measured by class grades on a GPA scale (A+=4.3, A=4.0, A-=3.7, B+=3.3, B=3.0, B-=2.7, C+=2.3, C=2.0, C-=1.7). Four statistical tests were administered: the Pearson Correlation Coefficient (r), Spearman’s Correlation (rs), the Coefficient of Determination (R2), and the p-value test (pp for Pearson’s correlation and ps for Spearman’s correlation). The initial survey yielded values of 0.0617 (r), 0.0573 (rs), 0.0038 (R2), 0.4028(pp), and 0.4189 (ps), respectively. A subsequent study included 78 high school students in New Jersey enrolled in on-level classes. Each statistical test yielded values of 0.0120 (r), 0.0476 (rs), 0.0001 (R2), 0.9170 (pp), and 0.6689 (ps). Finally, a small, randomly selected sample (n=43) of students enrolled in either IB/honors or on-level classes in Korea were surveyed. The statistics yielded values of 0.0319 (r), 0.0690 (rs), 0.0010 (R2), 0.8391 (pp), and 0.6327 (ps), respectively. All results from the studies indicated little to no correlation between exercise hours and academic performance.

KEYWORDS: High school students; Academic Performance; Physical Education; Pearson’s Correlation Analysis; Spearman’s Correlation Analysis

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INTRODUCTIONG Physical Education is generally a required part of public and private education for schools all across the country. Out of the 50 states in the United States, 39 states require physical education in elementary school, 37 states require physical education for junior high school students, and 44 states require physical education in high schools [21]. The average American student participates in 52-58 minutes of physical education class per day for five days a week [18]. 57.4% of students are also student-athletes [16] and usually participate in 10-12 hours of practice after school per week [14]. This can be mentally as well as physically taxing for already-burdened students. Additionally, many students also complain that they see a drop in their performance during their sports seasons, specifically varsity athletes [17], and that their overall physical exhaustion from sports is exacerbated by their obligations to participate in physical education for 52-58 minutes every day. On the other hand, physical education is regarded as more of a minor area of study in South Korea and is not as widely available across schools as it is in the United States. The idea of a movement-focused class is a Western concept [12]. Korean elementary and middle school students participate in an average of 120 minutes of physical education classes per week, but they mostly become optional as students enter high school [13]. Across the nation, only 2-8% of students fulfill the recommended exercise in school, and many instead utilize the time to study and learn other subjects [9]. G

G The relationship between brain function and exerciseG It is commonly assumed and accepted that implementing physical education programs can benefit students in various ways. It is also widely accepted that since exercise is beneficial for the body, it must be beneficial for the brain [5], therefore, beneficial for academic performance. Beneath such belief lies a biological insight into how exercise influences brain function. Increased levels of oxygen to the brain caused by active exercise leads to an increased amount of neurotransmitters (specifically glutamate and acetylcholine), which ultimately aid in the memory-processing function of the hippocampus [22]. In addition, the brain also requires a high amount of nutrients to be delivered and has high metabolic demand. An increase in oxygen flow improves the circulation of blood cells, which in turn satisfies the brain’s need for nutrients. Furthermore, exercise may increase the amount of brain-derived neurotrophic factors (BDNF), which are specific molecular targets that have the potential to increase the formation of synapses, which is called synaptogenesis. Synaptogenesis aids in memory consolidation and can increase the retention of memory over a longer period of time [11]. The type of exercise has also proven to be important in determining the overall benefits for the brain. Aerobic exercise (such as running) includes exercises that cause the heart to pump blood quickly or sweat to be produced at a higher rate [10]. These functions contribute to the overall enlargement of the hippocampus, which encourages longterm and verbal memory [3]. Different parts of the brain, specifically the prefrontal cortex and medial temporal cortex, have a greater volume in the brain of people who exercise versus people who do not exercise. These two structures are vital in controlling thought processes and prolonging memory [4]. G

G Prior studies G Several studies have previously been conducted exploring the relationship between academic performance and physical activity. A research team in Atlanta, US, has reviewed different studies exploring this relationship (Rasberry, 2011). 48 studies were conducted under the category of physical education and academic achievement. Out of the 48 studies, 25 found a positive correlation, 22 found a neutral correlation, and 1 found a negative correlation between the variables. 30 other studies were conducted under the category of extracurricular physical activity and academic achievement. Out of the 30 studies, 14 found a positive correlation, 15 found a neutral correlation, and 1 found a negative correlation between the variables. Based on these studies, it can be concluded that the significant majority of the studies found either a positive or neutral correlation between academic achievement and level of exercise [15]. Another study explored the relationship between the number of physical education classes and academic performance in Korean students (Kim, 2012). This study found a positive correlation between the number of physical education classes and school performance. Students

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who took part in three or more physical education classes per week reported higher school performance, whereas students who took part in less than three classes per week reported lower school performance [6]. G

G HypothesisG Due to the statistical nature of this study, it required two hypotheses: a null hypothesis and an alternative hypothesis. A null hypothesis asserts that between the two variables, there is no statistical significance, while an alternative hypothesis asserts that the two variables are statistically significant. Therefore, the null hypothesis for this study was set as follows: more exercise does not necessarily lead to better academic performance, and, in turn, the alternative was set as more exercise will lead to higher levels of academic performance.G

G G METHODSG Survey G Initially, 186 freshmen, sophomores, juniors, and seniors were randomly selected to participate in a survey to collect data. All participants were between the ages of 14-18 and were enrolled in honors/AP classes, specifically Honors Biology, Honors English, AP Statistics, or AP Calculus AB/BC. The survey, distributed via Google Form, was anonymous and asked participants to specify their level of exercise per week, class, and grade point average. From the given data, the four statistical methods utilized in this study were conducted and analyzed. The statistical tests were calculated both on paper and verified with an online algorithm. The initial survey was solely conducted with students in honors/AP level classes, which challenge students with a demanding curriculum that explores more topics at a deeper level. The subsequent study conducted involved students solely in on-level classes, meaning that the course covers less material and is less demanding on the students. The subsequent study was conducted with the purpose of ruling out the difficulty of classes being a potential factor introducing bias into the survey result. It involved 78 students specifically enrolled in on-level Algebra, Biology, and PreCalculus classes. Finally, in order to rule out the possibility of location affecting the data, a final study was conducted with 43 randomly selected high school students in Korea in either IB/honors or on-level math, science, or English classes. The statistical models utilized in the initial study were also applied to these two groups of students as well. G

G Pearson Correlation G The first method used is called the Pearson correlation (r-value). The word correlation in this context refers to the expectation that a variable will change in the same direction as the other variable. This specific method measures both the direction (positive or negative) and the strength (strong or weak) of that relationship. The value is always between -1 and 1. If the r-value is between 0 and 1, a positive correlation exists, and the strength of the correlation increases from weak to strong as the value approaches 1. If the r-value is purely 0, it signifies that there is absolutely no correlation between the given variables. If the r-value is between 0 and -1, a negative correlation exists, and the strength of the correlation goes from a weak negative correlation to a strong negative correlation as the value approaches -1. To give the specifics of this calculation, first, the sum of all of the “x-values” or hours of exercise per week was calculated. The final calculation needed for the formula was the sum of the deviation scores squared. The deviation scores indicate the distance between the data point and the data’s typical value (mean). As exemplified by the formula in the supplementary information section, the deviation score is calculated by subtracting the mean of the x-values from the specific x-value, adding all of the scores together, then squaring the final value. The exact process applies to the y–values as well, in this case, the numerical grade point average of each participant. Those values are multiplied together to find the product of the deviation scores. Finally, all of the calculated values are plugged into the formula, and an r-value is determined [7]. G

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Spearman Correlation G The second method utilized was Spearman Correlation (rs-value). Similar to the Pearson correlation, this analysis determines the relative strength and direction of the relationship between the two variables. However, the difference between the Pearson and Spearman correlation is that the Pearson correlation assesses the linearity of the two variables while the Spearman correlation assesses the monotonicity of the variables. The Spearman correlation coefficient value always is between -1 and 1. When it is between 0 and 1, it indicates a positive correlation; when it is between -1 and 0, it indicates a negative correlation. The closer the value is to 0, the weaker the strength of the relationship between the two variables. Before calculating the rs-value, each data point must be assigned a rank (this applies to both the x and y values). This is done by assigning the number “1” to the largest number in the set, “2” to the second largest number, and so on. If there are two or more points that have equal values, then the average rank will be given, meaning that the sum of the points’ positions (for instance, 6th position) relative to the other points will be divided by the number of points, resulting in the average rank. Next, the difference between Rankx and Ranky is squared, resulting in the value d2. All of these values are then utilized in the formula (specified in the Supplementary Information section), and Spearman correlation is calculated [8]. G

G Validity of Statistical TestsG The Pearson correlation is a type of inferential statistic, which means that the resulting value can be used to test statistical hypotheses, in this case, the alternative and null hypotheses. One of the assumptions of using this test is that the data will be normally distributed [23]. Since the sample size for this study is 187, 78, and 43 students for each group, it is assumed that the dataset is large enough to test for normal distribution of data.G The Spearman correlation was calculated as a follow-up to the Pearson correlation. Unlike the Pearson correlation, a normal distribution of the data is not one of the assumptions of this statistical test. Instead, the statistical test considers data that does not follow a normal distribution; in other words, it is the nonparametric form of the Pearson correlation [8]. Even though the sample size is supposedly large enough to provide a normal distribution, the Spearman correlation was calculated in the event that the data does not provide a normal distribution. It was also utilized to verify that the weak positive correlation initially found is consistent with another type of statistical test and further determine the linearity or monotonicity of the dataset.G

G Coefficient of DeterminationG After calculating and analyzing the Pearson correlation and Spearman correlation, the coefficient of determination was calculated as a follow-up. The coefficient of determination (also known as r-squared, R2) measures how well a model can predict a certain outcome. This value is between 0 and 1, with higher r-squared values signifying a higher ability to predict an outcome. Essentially it is a measure of how close the data points will be to the line of best fit. The lesser the value, the farther the data points will be to the linear regression line. The Coefficient of Determination was determined by simply squaring the previous r-value, hence the name, r-squared [1]. G

G P-valueG To add another reinforcement to the statistical analysis of the data, the p-value test was utilized to determine if the null hypothesis should be rejected. The p-value is initially calculated, assuming that the null hypothesis is true. The lower the p-value is, the more evidence there is against the null hypothesis. Therefore, in this case, if the p-value is greater than 0.05, which is the significance level, the null hypothesis cannot be rejected, but if it is less than 0.05, it may be rejected, and the hypothesis may be accepted [2]. P value was calculated for each Pearson (pp) and Spearman correlation (ps) to investigate the statistical validity of each analysis.

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RESULTS & DISCUSSION Initial study - Honors/AP course students in the U.S.

Figure 1. Distribution of students in honors/AP courses based on their exercise hours and GPA The first group of statistical tests solely involved honors/AP students. There was a total of 186 students in the group, and they were asked to answer the amount of exercise hours per week and their academic performance in the form of GPA (Fig. 1). Histograms of the distribution of students’ exercise hours and GPA were plotted to see if the dataset was normally distributed (Fig. 2, 3). When drawn based on the GPA, the distribution displayed a bell curve, or a normal distribution, justifying the use of the Pearson correlation (Fig. 2). However, when drawn based on the exercise hours, the distribution of students does not necessarily follow the pattern of a normal distribution, justifying the use of Spearman correlation (Fig. 3). The Pearson correlation coefficient was calculated to be 0.0617. The proximity of the value to 0 indicates that there is almost no correlation between the variables. The r-value itself is above 0, indicating that there is a weak but positive relationship between the two variables. The resulting Spearman correlation was 0.0573. While the positive value indicates that the direction of the relationship between exercise and academic performance is positive, the close proximity to 0 indicates that it is a very weak, positively correlated relationship. By comparing the Pearson (0.0617) and Spearman (0.0573) correlation coefficients, it is confirmed that the relationship between exercise hours and GPA is positive, but at the same time, very weak. Further, it could be inferred that the dataset shows a more linear relationship, rather than a monotonic relationship since the Pearson correlation coefficient is greater than Spearman’s.

Figure 3. Honors student distribution (Exercise hours)

Figure 2. Honors student distribution (GPA)

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The coefficient of determination (R2) was further calculated by squaring the initial r-value, and it was calculated to be 0.0038 (Fig.4). The closer the value is to 0, the more significant the variance is between the two given variables. To finalize the calculations involving students in higher-level classes, the ppvalue was calculated to be 0.4028, and the ps-value was 0.4189. Not only do the p-value calculations prove that the result is not statistically significant, but it also demonstrates that the null hypothesis cannot be rejected, since both values are significantly greater than 0.05. The lower the p-value is, the more evidence there is against the null hypothesis. In this case, since the p-value is relatively high, it is more promising to, in turn, not reject the null hypothesis (‘more exercise does not necessarily lead to better academic performance’) while the alternative hypothesis is neither supported (‘more exercise will lead to higher levels of academic performance’).

Figure 4. Visualization of R2 for initial study

Subsequent study - On-level course students in the U.S. After calculating the results of the initial study, a subsequent study was conducted with the students taking on-level courses. This was to rule out the difficulty of classes as a potential bias factor, given that the on-level courses are considered relatively less demanding compared to the honors/AP courses. There was a total of 78 students in the on-level group, and they were asked the same question (Fig. 5).

Figure 5. Distribution of students in on-level courses based on their exercise hours and GPA

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The same calculations were applied to this group of participants as well. First, histograms of the distribution of students’ exercise hours and GPA were plotted to test the normal distribution (Fig. 6, 7). However, both exercise hours and GPA histograms did not show a clear bell-shaped curve, presumably because of the smaller dataset size. Therefore, it was mandatory to analyze both Pearson and Spearman correlation because the normality of the dataset was unclear.

Figure 6 On-level student distribution (GPA)

Figure 7. On-level student distribution (Exercise hours)

The r-value, or the Pearson correlation, was calculated to be 0.012, while the rs-value, or the Spearman correlation, was calculated to be 0.0476. Again, a positive correlation was observed for both Pearson and Spearman analysis, but the coefficients were notably small, confirming a very weak correlational relationship between exercise hours and academic performance. What is different from the initial study is that the rs-value is bigger than the r-value, meaning that the dataset has a more monotonic tendency than linear. The coefficient of determination (R2) was calculated to be 0.0001 (Fig. 8). Since the value is a very minuscule number and close to 0, it can be determined that the distance between the values and the linear regression line is far, limiting the ability to predict an outcome. The ability to predict an outcome is applied in the alternative hypothesis: the more exercise a student participates in, the higher the student’s grade will be. However, as indicated by the low coefficient of determination, the model will not be able to predict such an outcome well, and the assertion will not apply to every case. Finally, the p -value was calculated to be 0.9170, and the ps-value was 0.6689, both of which are significantly higher than 0.05. In comparison to the initial study only involving honors/AP students, all of the statistical values indicated that there was a lesser correlation between the variables in on-level students than in honors/AP students. The Pearson correlation (r) and the coefficient of determination (R2) were both closer to 0 in the subsequent study, and the p-values were both greater in this study than in the initial study. p

Fig. 8 Visualization of R2 for subsequent study

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Final study - Honors/IB & on-level course students in Korea: Lastly, to rule out the possibility of the conclusion only applying to students within the United States, 43 randomly selected Korean students taking courses corresponding to honors/IB and on-level courses were surveyed to investigate the hypothesis. Like the previous two studies, students were asked about the hours of exercise and their GPA. Since Korea has a different grading system, all numbers were converted into the 4.3 GPA scale that is utilized in the United States (Fig. 9).

Figure 9. Distribution of Korean students based on their exercise hours and GPA Similar to the subsequent study, histograms of the distribution of students’ exercise hours and GPA were first plotted to determine the normal distribution (Fig. 10, 11). However, both exercise hours and GPA histograms did not show a clear bell-shaped curve, presumably because of the even smaller dataset size. Since the normality of the dataset was unclear, it became necessary to analyze both Pearson and Spearman correlation.G G GPA

Figure 11. Korean student distribution (Exercise hours)

Figure 10. Korean student distribution (GPA)

The same calculations applied to this group as well. The Pearson correlation was calculated to be 0.0319, and the Spearman correlation was calculated to be 0.069. Both coefficients being extremely close to zero reveals that there is a negligibly weak positive correlation between the exercise hours and GPA, notwithstanding the national and cultural difference. In the case of the final study, however, again the rs-value was greater than the r-value, meaning that the Korean student group dataset displays more monotonic than linear characteristics. The coefficient of determination (R2) was calculated to be 0.001 (Fig. 12). Since this value is also very close to 0, it indicates a significant variance between the data points and the linear regression line.

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Finally, the pp-value was calculated to be 0.8391, and the ps-value was 0.6327, suggesting that the null hypothesis is not able to be rejected.

Fig. 12 Visualization of R2 for final study

CONCLUSION According to the results of the conducted studies, the findings imply that the relationship between exercise and academic performance may be insignificant or minimal, regardless of the difficulty of the courses, cultural background, or location. While exercise has proven to be beneficial in the general population, the additional pressures that students are under, such as time or stress, may cloud the benefits of exercise. As indicated in the title of this research, there is a positive correlation between the variables, meaning that there is not absolutely no correlation; however, the proximity of the values to 0 indicates that the correlation is very weak. This weak correlation does not mean that exercise cannot be beneficial but simply means that an overall increase in a student’s exercise will not necessarily increase the student’s academic performance. Further, two out of three studies indicated that the relationship between exercise hours and GPA is increasing rather monotonically than linearly, which implies that the variables tend to move in the same direction, but not necessarily at a constant rate. This could be again interpreted as the amount of exercise does not guarantee higher academic performance. Therefore, given the weak correlation found, schools should take student opinions about the intense physical education requirement into more careful consideration and think about the overall physical burden on these students, especially for highly pressured student-athletes. The current education system in place also has the opportunity to be revamped, considering that the excuse that “more exercise leads to higher grades” was disproved by this study. Educational curriculums should be made to better fit students’ needs, even if it entails modifications. Going back to the prior studies mentioned previously, this study furthered and improved the results found in the prior study. While it holds true that the significant majority of the studies found a positive/neutral correlation between the specified variables, they fail to determine the strength of the correlation. This current study, however, found that a weak, positive correlation exists between academic performance and exercise. Although the second study conducted with Korean students seemed convincing, it was specified that the level of school performance was obtained subjectively, meaning that participants themselves “graded” their school performance. This current study collected academic performance objectively, basing the data points on a verified GPA scale. This objective collection strengthens the findings of this study. Future research should focus on the consequences of students’ stress levels on academic performance. Since many other studies have proven that exercising is beneficial for the overall performance and health of students, finding a moderate number of exercising hours that actually help reduce the stress levels can provide the students with a better ability to learn and which can ultimately lead to optimal academic performance. It was also mentioned that an increased amount of oxygen in the hippocampus

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leads to the growth of neurotransmitters, effectively increasing memory and learning capability. With that being said, more research should be done with aerobic methods such as meditation to investigate a potential correlation with GPA. These kinds of exercises could be offered as potential alternatives or even better solutions for students. Overall, the results demonstrate a weak, positive correlation between exercise and academic achievement, giving the scientific community a new opportunity to reanalyze and determine how students learn best. G

G SUPPLEMENTARY INFORMATIONG Initial study (honors/AP):G Raw DataG HoursG GPAG

HoursG

GPAG

HoursG

GPAG

HoursG

GPAG

HoursG

GPAG

3.7G

3.3G

4.3G

3.3G

10G

3.7G

15G

12G

4.3G

15G

3.3G

3.7G

15G

1.7G

15G

3.7G

1.7G

12G

10G

3.7G

10G

3.3G

3.7G

10G

3.3G

15G

3.3G

3.7G

3.3G

10G

3.7G

3.3G

12G

4.3G

15G

3.3G

10G

3.3G

10G

2.7G

2.3G

3.7G

15G

3.7G

15G

3.3G

10G

3.7G

15G

3.3G

3.7G

10G

3.7G

2.7G

12G

3.3G

15G

3.7G

3.3G

10G

3.3G

10G

3.7G

10G

3.7G

3.3G

2.3G

15G

3.7G

15G

3.7G

3.3G

3.7G

10G

3.7G

10G

1.7G

3.7G

10G

3.7G

10G

2.7G

12G

3.7G

12G

10G

2.7G

15G

3.3G

Hours G

GPAG

Hours G

GPAG

Hours G

GPAG

Hours G

GPAG

Hours G

GPAG

12G

1.7G

10G

3.7G

12G

3.7G

15G

4.3G

15G

4.3G

3.3G

12G

3.7G

15G

3.7G

3.3G

10G

3.7G

4.3G

15G

12G

3.3G

15G

3.3G

4.3G

12G

15G

3.7G

12G

3.7G

10G

3.3G

15G

10G

15G

3.3G

10G

3.7G

1.7G

10G

15G

4.3G

10G

15G

10G

3.7G

15G

3.7G

15G

4.3G

114

15G

3.7G

12G

3.3G

15G

3.7G

3.3G

15G

4.3G

15G

3.3G

15G

3.7G

10G

2.3G

3.3G

15G

3.7G

15G

12G

15G

3.7G

3.3G

12G

15G

3.7G

15G

3.3G

15G

10G

3.3G

15G

3.3G

15G

3.7G

12G

-G

10G

3.7G

12G

-G

1.7G

15G

12G

3.7G

-G

10G

3.7G

15G

3.7G

4.3G

-G

G SI-Table 1. Hours of exercise and GPA of honors/AP studentsG

G Pearson Correlation [19]G x=1,599.00G Mean = 8.597G Sum of deviation scores squared: (X-Mx)2=SSx=4148.758G

G y=659G Mean= 3.543G Sum of deviation scores squared: (Y-My)2=SSy=61.396G

G N=186 (sample size) G Product of deviations scores:G (X-Mx) (Y-My)=31.126G

G r ; - My)(Y - 0[ ¥ 66[ 66\

r2= 0.00380689G

G pp-value: 0.402817 (based off of 185 degrees of freedom) G

G Spearman Correlation [20]: G

G 5DQNೋG

Rank G

(R -R ) G

5DQNೋG

Rank G y

(R -R ) G

5DQNೋG

Rank G

(R -R ) G

105.5G

90.5G

225G

78G

38.5G

1560.25G

21G

135.5G

13110.25G

147G

135.5G

132.25G

147G

38.5G

11772.25G

132.5G

162G

870.25G

21G

135.5G

13110.25G

147G

6.5G

19740.25G

147G

6.5G

19740.25G

105.5G

38.5G

4489G

78G

135.5G

3306.25G

21G

90.5G

4830.25G

78G

135.5G

3306.25G

147G

176G

841G

168G

38.5G

16770.25G

115

181G

162G

361G

78G

90.5G

156.25G

147G

38.5G

11772.25G

124G

135.5G

132.25G

147G

38.5G

11772.25G

181G

38.5G

20306.25G

168G

135.5G

1056.25G

147G

38.5G

11772.25G

147G

90.5G

3192.25G

168G

38.5G

16770.25G

78G

90.5G

156.25G

51.5G

38.5G

169G

78G

162G

7056G

147G

38.5G

11772.25G

124G

135.5G

132.25G

147G

162G

225G

78G

90.5G

156.25G

181G

172G

81G

21G

135.5G

13110.25G

168G

162G

36G

21G

90.5G

4830.25G

78G

38.5G

1560.25G

51.5G

90.5G

1521G

105.5G

90.5G

225G

21G

90.5G

4830.25G

105.5G

6.5G

9801G

51.5G

135.5G

7056G

78G

90.5G

156.25G

21G

38.5G

306.25G

78G

179G

10201G

21G

90.5G

4830.25G

105.5G

90.5G

225G

181G

176G

25G

147G

38.5G

11772.25G

51.5G

179G

16256.25G

124G

90.5G

1122.25G

181G

162G

361G

78G

135.5G

3306.25G

78G

162G

7056G

132.5G

172G

1560.25G

105.5G

90.5G

225G

78G

162G

7056G

105.5G

135.5G

900G

168G

90.5G

6006.25G

21G

135.5G

13110.25G

78G

90.5G

156.25G

124G

162G

1444G

51.5G

183.5G

17424G

168G

162G

36G

21G

135.5G

13110.25G

168G

135.5G

1056.25G

105.5G

183.5G

6084G

78G

172G

8836G

78G

90.5G

156.25G

105.5G

90.5G

225G

147G

90.5G

3192.25G

105.5G

38.5G

4489G

51.5G

38.5G

169G

105.5G

90.5G

225G

168G

162G

36G

21G

38.5G

306.25G

21G

90.5G

4830.25G

21G

38.5G

306.25G

181G

38.5G

20306.25G

78G

90.5G

156.25G

168G

38.5G

16770.25G

78G

38.5G

1560.25G

78G

135.5G

3306.25G

168G

6.5G

26082.25G

21G

90.5G

4830.25G

105.5G

38.5G

4489G

78G

135.5G

3306.25G

124G

135.5G

132.25G

51.5G

38.5G

169G

21G

135.5G

13110.25G

147G

135.5G

132.25G

21G

38.5G

306.25G

21G

38.5G

306.25G

21G

90.5G

4830.25G

21G

90.5G

4830.25G

21G

90.5G

4830.25G

51.5G

38.5G

169G

51.5G

90.5G

1521G

51.5G

38.5G

169G

21G

38.5G

306.25G

51.5G

90.5G

1521G

21G

6.5G

210.25G

116

21G

38.5G

306.25G

21G

38.5G

306.25G

78G

176G

9604G

124G

90.5G

1122.25G

21G

135.5G

13110.25G

21G

38.5G

306.25G

78G

90.5G

156.25G

51.5G

90.5G

1521G

147G

38.5G

11772.25G

124G

183.5G

3540.25G

168G

38.5G

16770.25G

181G

38.5G

20306.25G

78G

90.5G

156.25G

78G

38.5G

1560.25G

21G

135.5G

13110.25G

78G

90.5G

156.25G

78G

90.5G

156.25G

51.5G

38.5G

169G

168G

38.5G

16770.25G

105.5G

38.5G

4489G

51.5G

38.5G

169G

124G

6.5G

13806.25G

124G

135.5G

132.25G

105.5G

90.5G

225G

181G

135.5G

2070.25G

124G

38.5G

7310.25G

124G

6.5G

13806.25G

21G

90.5G

4830.25G

168G

90.5G

6006.25G

21G

6.5G

210.25G

78G

38.5G

1560.25G

147G

135.5G

132.25G

105.5G

135.5G

900G

147G

183.5G

1332.25G

147G

90.5G

3192.25G

51.5G

38.5G

169G

21G

38.5G

306.25G

147G

135.5G

132.25G

124G

38.5G

7310.25G

124G

38.5G

7310.25G

124G

90.5G

1122.25G

105.5G

135.5G

900G

21G

90.5G

4830.25G

147G

38.5G

11772.25G

147G

38.5G

11772.25G

21G

90.5G

4830.25G

51.5G

38.5G

169G

181G

6.5G

30450.25G

21G

6.5G

210.25G

124G

38.5G

7310.25G

21G

135.5G

13110.25G

21G

90.5G

4830.25G

21G

6.5G

210.25G

21G

90.5G

4830.25G

21G

135.5G

13110.25G

51.5G

135.5G

7056G

-G

147G

135.5G

132.25G

51.5G

162G

12210.25G

-G

G SI-Table 2. Rankx, Ranky, and (Rx-Ry)2 of honors/AP students G

G x:G m G m G m G m G m G m G m G m G m G m G y:G m G m G m G m G m G m G m G m G 1

41G 20G 33G 22G 15G 2G 27G 15G 11G 12G

52G 52G 38G 15G 5G

G SI-Table 3. Repeated ranks for x and y values (honors/AP students)G

G n=186G d2= (Rx - Ry) G 2

117

R= 0.0573G

G Ps-value = 0.41886G

G Subsequent study (on-level classes):G Raw dataG HoursG GPAG HoursG GPAG 2G 3.7G 4G 3G 12G 3G 6G 4G 2G 4G 8G 3.7G 4G 4G 15G 4G 8G 4G 2G 3.3G 10G 2.3G 10G 4G 10G 2.7G 4G 3G 15G 3.3G 15G 4G 10G 2.7G 0G 4G 15G 4.3G 8G 4G 15G 1.7G 15G 4.3G 15G 2.3G 15G 3G 12G 4.3G 15G 3.7G 15G 4G 8G 3.7G 15G 4G 15G 3.3G 2G 4G 6G 3.7G G

HoursG

GPAG

HoursG

GPAG

HoursG

GPAG

4.3G

12G

3.7G

10G

3.7G

10G

3.7G

3.3G

15G

1.7G

10G

3.7G

15G

12G

3.7G

2.3G

15G

3.7G

15G

3.7G

12G

2.3G

15G

3.7G

10G

2.7G

10G

15G

12G

3.7G

3.3G

12G

4.3G

3.3G

12G

3.7G

12G

2.7G

3.7G

10G

3.7G

15G

2.7G

10G

2.3G

-G

15G

3.3G

3.7G

-G

SI-Table 4. Hours of exercise and GPA of on-level studentsG

G Pearson Correlation: G x=698G Mean= 8.949G Sum of deviation scores squared: (X-Mx)2 =SSx=1761.795G

G y=267.3G Mean= 3.427G Sum of deviation scores squared: (Y-My)2=SSy=33.453G

G N=78 (sample size) G Product of deviation scores: (X-Mx) (Y-My)= 2.908G

G U ; - My)(Y - 0[ ¥ 66[ 66\ G r2= 0.000144G

118

G pp-value: 0.916952 (based off of 77 degrees of freedom) G

G Spearman Correlation: G

G 5DQNೋG

Rank G

(R -R ) G

5DQNೋG

Rank G

(R -R ) G

5DQNೋG

Rank G

(R -R ) G

71.5G

36G

1260.25G

45.5G

16G

870.25G

35G

36G

25G

58.5G

1122.25G

10.5G

56.25G

45.5G

16G

870.25G

71.5G

16G

3080.25G

10.5G

58.5G

2304G

10.5G

36G

650.25G

63.5G

16G

2256.25G

10.5G

36G

650.25G

25G

72G

2209G

45.5G

16G

870.25G

45.5G

36G

90.25G

54.5G

67G

156.25G

35G

72G

1369G

10.5G

49G

1482.25G

35G

58.5G

552.25G

35G

67G

1024G

54.5G

36G

342.25G

25G

36G

121G

10.5G

49G

1482.25G

45.5G

1806.25G

25G

484G

35G

67G

1024G

35G

36G

45.5G

36G

90.25G

10.5G

56.25G

35G

58.5G

552.25G

45.5G

16G

870.25G

10.5G

77.5G

4489G

10.5G

77.5G

4489G

63.5G

36G

756.25G

10.5G

72G

3782.25G

10.5G

16G

30.25G

35G

72G

1369G

25G

484G

54.5G

72G

306.25G

54.5G

36G

342.25G

10.5G

16G

30.25G

45.5G

16G

870.25G

76.5G

58.5G

324G

10.5G

16G

30.25G

35G

16G

361G

54.5G

49G

30.25G

71.5G

16G

3080.25G

54.5G

16G

1482.25G

71.5G

58.5G

169G

63.5G

58.5G

25G

76.5G

16G

3660.25G

25G

36G

121G

54.5G

16G

1482.25G

63.5G

58.5G

25G

10.5G

36G

650.25G

45.5G

36G

90.25G

25G

58.5G

1122.25G

10.5G

36G

650.25G

10.5G

16G

30.25G

63.5G

36G

756.25G

45.5G

16G

870.25G

71.5G

49G

506.25G

35G

36G

10.5G

16G

30.25G

35G

16G

361G

10.5G

67G

3192.25G

63.5G

49G

210.25G

63.5G

58.5G

25G

10.5G

49G

1482.25G

76.5G

49G

756.25G

10.5G

16G

30.25G

63.5G

75.5G

144G

25G

67G

1764G

76.5G

16G

3660.25G

71.5G

75.5G

16G

63.5G

58.5G

25G

119

63.5G

36G

756.25G

25G

36G

121G

54.5G

58.5G

16G

G SI-Table 5. Rankx, Ranky, and (Rx-Ry)2 of on-level students G

G x:G m G m G m G m G m G m G m G m G m G y:G m G m G m G m G m G m G m G m G 1

20G 9G 11G 10G 8G 10G 6G

21G 19G 7G 12G 5G

G SI-Table 6. Repeated ranks for x and y values (on-level students)G

G n=78G

R= 0.0476G p - value = 0.66885G S

G Final Study (Korean students): G Raw dataG HoursG GPAG HoursG GPAG

HoursG

GPAG

HoursG

GPAG

HoursG

GPAG

1.7G

2.7G

1.7G

4.3G

3.7G

1.7G

4.3G

3.3G

10G

4.3G

3.7G

4.3G

3.7G

1.7G

3.3G

3.7G

10G

4.3G

1.7G

15G

1.7G

4.3G

2.7G

12G

4.3G

15G

4.3G

1.7G

3.7G

4.3G

2.7G

4.3G

15G

4.3G

15G

4.3G

3.7G

-G

1.7G

4.3G

-G

G SI-Table 7. Hours of exercise and GPA of Korean studentsG

G Pearson Correlation: G x=200G Mean= 4.651G Sum of deviation scores squared: (X-Mx)2=SSx=801.767G

G y=151.5G Mean= 3.523G Sum of deviation scores squared: (Y-My)2=SSy=41.937G

G N=43 (sample size) G

120

Product of deviation scores: (X-Mx) (Y-My)= 5.849G r ; - My)(Y - 0[ ¥ 66[ 66\ G r2= 0.00101761G

G pp-value: 0.83908 (based off of 42 degrees of freedom) G

G Spearman Correlation: G

G 5DQNೋG

Rank G

(R -R ) G

5DQNೋG

Rank G

(R -R ) G

5DQNೋG

Rank G y

(R -R ) G

8.5G

39.5G

961G

19G

34G

225G

31G

10.5G

420.25G

40G

39.5G

0.25G

11G

22G

121G

31G

10.5G

420.25G

40G

10.5G

870.25G

11G

22G

121G

19G

39.5G

420.25G

40G

26.5G

182.25G

19G

39.5G

420.25G

2.5G

32G

870.25G

2.5G

39.5G

1369G

31G

30.5G

0.25G

31G

26.5G

20.25G

31G

34G

19G

26.5G

56.25G

19G

10.5G

72.25G

8.5G

10.5G

40G

10.5G

870.25G

19G

26.5G

56.25G

2.5G

10.5G

64G

31G

10.5G

420.25G

31G

26.5G

20.25G

40G

39.5G

0.25G

2.5G

10.5G

64G

40G

30.5G

90.25G

31G

34G

19G

10.5G

72.25G

19G

39.5G

420.25G

19G

10.5G

72.25G

31G

10.5G

420.25G

31G

10.5G

420.25G

19G

10.5G

72.25G

19G

10.5G

72.25G

31G

26.5G

20.25G

6.5G

10.5G

16G

40G

10.5G

870.25G

19G

10.5G

72.25G

11G

22G

121G

6.5G

10.5G

16G

-G

10.5G

30.25G

19G

39.5G

420.25G

-G

G SI-Table 8. Rankx, Ranky, and (Rx-Ry)2 of Korean students G

G x:G

mG 1

mG 2

mG 3

mG 4

mG 5

13G

mG 6

11G

y:G

mG 8

mG 9

mG 10

mG 11

mG 12

20G

G SI-Table 9. Repeated ranks for x and y values (Korean students)G

121

n=43G

R= 0.069G ps-value = 0.63267G

G G G G REFERENCESG [1] Academic Skills Kit. (n.d.). Coefficient of Determination, R-Squared. Numeracy, Maths and Statistics - Academic Skills Kit. https://www.ncl.ac.uk/webtemplate/askassets/external/maths-resources/statistics/regression-and-correlation/coefficient-ofdetermination-r-squared.html G [2] Dahiru, T. (2008). P - value, a true test of statistical significance? A cautionary note. Annals of Ibadan postgraduate medicine, 6(1), 21-6. https://doi.org/10.4314/aipm.v6i1.64038 G [3] Erikson, K. L., et al. (2011). Exercise Training Increases Size of Hippocampus and Improves Memory. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 108(7), 3017-3022. https://doi.org/10.1073/pnas.1015950108 G [4] Godman, H. (2014, April 9). Regular Exercise Changes the Brain to Improve Memory, Thinking Skills. Harvard Health Blog. https://www.health.harvard.edu/blog/regular-exercise-changesbrain-improve-memory-thinking-skills-201404097110 G [5] Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: Exercise effects on brain and cognition. Nature Reviews Neuroscience, 9(1), 58-65. https://doi.org/10.1038/nrn2298 G [6] Kim, S. Y., & So, W. Y. (2012). The relationship between school performance and the number of physical education classes attended by korean adolescent students. Journal of sports science & medicine, 11(2), 226–230. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737878/ G [7] Laerd Statistics. (2018). Pearson Product-Moment Correlation. In When You Should Run This Test, the Range of Values the Coefficient Can Take and How to Measure Strength of Association. https://statistics.laerd.com/statistical-guides/pearson-correlation-coefficientstatistical-guide.php G [8] Laerd Statistics. (2018). Spearman's Rank-Order Correlation - A Guide to When to Use It, What It Does and What the Assumptions Are. https://statistics.laerd.com/statisticalguides/spearmans-rank-order-correlation-statistical-guide.php G [9] Lindberg, R., Seo, J., & Laine, T. H. (2016). Enhancing Physical Education with Exergames and Wearable Technology. IEEE Transactions on Learning Technologies, 9(4), 328-341. https://doi.org/10.1109/TLT.2016.2556671 G [10] Luders, E., et al. (2008). The Effects of Aerobic Exercise on the Structure and Function of the Human Brain. Journal of Applied Physiology, 105(4), 1358-1366. https://doi.org/10.1152/japplphysiol.90324.2008 G [11] McGregor, G. (2022, January 28). How Exercise Affects the Brain. BYU Life Sciences. https://lifesciences.byu.edu/how-exercise-affects-your-brain G [12] Park, S., et al. (2014). Effects of Physical Education, Extracurricular Sports Activities, and Leisure Satisfaction on Adolescent Aggressive Behavior: A Latent Growth Modeling Approach. PLOS ONE, 9(4), e0174674. https://doi.org/10.1371/journal.pone.0174674 G [13] Park, K. (2022, September 1). All Study and No Play Makes Korean Teens Less Physically Active than Their Grandparents. The Hankyoreh. https://english.hani.co.kr/arti/english_edition/e_national/1057130.html G

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Global Imports in the War on Ukraine: How Big of an Impact Has Russia’s Invasion Had on the World Economy? Author 1

Full Name

Kim, Dayeon

Chadwick International School

(Last Name, First Name)

School Name

ABSTRACT: The commencement of the Russian-Ukrainian War has led to many changes in the present economies of many countries. This research focuses on quantifying the impact the Russian-Ukrainian War had on the global economy by analyzing separate entities’ range of imports of Ukrainian products from different sectors. While examining the economic impact of the war in the research, the reports of organizations such as the OEC, World Trade Organization, World Bank, and IMF were used. According to the reports, it is possible to conclude that since Ukraine is such a heavy supplier of agricultural products, the range of imports decreased after the war. This decrease has eventually led to inflation in the prices of such products.

KEYWORDS: Russo-Ukrainian War, Agricultural goods, Inflation rate, Trading, Economic Relationship

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პ ,QWURGXFWLRQ The global economy has experienced more turbulence in recent years. Ukraine's deepening relations with the EU and NATO disturbed Russia, leading to the annexation of Crimea and the occupation of Eastern Ukraine. Crimea declared its independence using the right of "self-determination," which caused controversy, and the region was then annexed by Russia through a referendum. In 2022, Putin ordered the invasion of Ukraine, which broke out into the Russo-Ukrainian War. Ukraine is a major agricultural supplier and one of the world's leading producers of crops such as wheat, corn, and sunflower seeds. Many countries rely on these agricultural products, so both developed and developing countries have experienced indirect and direct economic consequences. It is important to identify the products that the Russo-Ukrainian War has impacted. By identifying these factors, we can use the results of this research to reduce the ongoing damage that the war has caused on the economic front. This research paper aims to identify the products that Ukraine mainly exported to three trading entities. We will do this by taking statistical information periodically regarding several countries' scale of imports from Ukraine. We will then compare and contrast the data to find any correlations between the times and range of impact. This will specifically tell us how much the Russo-Ukrainian War impacted the global economy.

,, 'LVFXVVLRQ %DFNJURXQG RU /LWHUDWXUH 5HYLHZ 1. Historical Events 1.1 Situation after the Collapse of the Soviet Union The dissolution of the Soviet Union in 1991 led Ukraine to become an independent country (Fournier, 2023). However, political tension between Russia and Ukraine remained, as the two countries shared deep connections. Ukraine is of great significance to Russia's identity and global vision. Notably, around eight million ethnic Russians reside in Ukraine, primarily in southern and eastern regions. Moscow often uses the protection of these Russians as a pretext for its actions in Crimea and Donbas. Consequently, any separation from Ukraine is viewed by Russian politicians as both a mistake and a threat to their country's standing as a great power (Masters, 2023). In 2008, the Russian government decided to annex Crimea. However, the new Ukrainian president, Viktor Yanukovych, reduced the need for annexation by increasing the penetration of Russian citizens and financial dependence between Russia and Ukraine. This led to the Revolution of Dignity in 2014 when citizens demanded a proWestern government. The former president and other Ukrainian officials who were closely connected to Russian security fled the country and asked Russia for help. Russia condemned these changes as a "coup" (Beiber, 2015). As a result, pro-Russian demonstrations took place in southern and eastern Ukraine, leading to the annexation of Crimea.

1.2 Russian Invasion of Ukraine On February 24, 2022, Russian President Vladimir Putin launched a military operation in Ukraine with the stated aim of "demilitarizing and denazifying" the country. Putin said that Russia had no intention of occupying Ukraine but that it would support the right of self-determination for the people of the Donbas region, which is predominantly Russian-speaking. He also claimed that the operation was necessary to protect the people of Donbas from "genocide" by the Ukrainian government (Orhan, 2022).

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2. Literature Review 2.1 The Impact on the Global Supply Chain The Russia-Ukraine conflict has had a significant impact on the global economy, primarily through increased energy prices, weakened confidence in financial markets, and the implementation of international sanctions on Russia. The conflict has disrupted global agricultural commodity markets, leading to pressure on wheat supplies, stocks, and food prices. Orhan (2022) identified three primary channels through which the conflict impacts the global economy: financial sanctions, commodity prices, and global supply chains. Caldara et al. (2022) found that the conflict is likely to lead to a decrease in global GDP and an increase in global prices. Millard (2022) found that the conflict has had a negative impact on commodity prices and household spending in countries that are heavily exposed to Russia and Ukraine. The conflict has had a particularly negative impact on developing countries, which are more reliant on imports of food and energy from Russia and Ukraine. Nazeeruddin (2022) found that the conflict has caused the economy to slow down and inflation rates to soar in India. Glauben et al. (2022) found that the conflict seriously affected the agricultural market, particularly in the MENA region and sub-Saharan Africa. Hellegers (2022) highlighted the need for a global approach to address the vulnerability of countries' food security. The conflict has disrupted global supply chains, impacting various industries and economies worldwide. Baumeister (2023) found that the sources of oil price fluctuations associated with the war played a role in the recent inflation surge. Ruiz Estada (2022) found that the conflict has had large spillover effects on inflation and unemployment worldwide.

,,, 'DWD DQG 0HWKRGV 1. Choropleth Map

>)LJXUH 0DS RI WKH 86 (8 DQG &KLQD@ The data will be shown visually through a choropleth map, as shown in Figure 1. This is a type of thematic map that uses various shades, colors, or patterns to represent data values across different geographic regions, such as countries, states, counties, or other administrative boundaries. In this research, the colors in the choropleth maps represent the volume the three countries have imported from Ukraine. A lighter color corresponds to a lower volume of imports and vice versa (Pedriquez, 2022).

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To comprehensively examine the economic repercussions of the Russo-Ukrainian War, the United States, China, and the European Union (EU) are three entities that are important to be scrutinized. They represent prominent economic powers that wield substantial economic influence in global markets and maintain significant trade relationships. The United States plays a crucial role in international trade and finance while extensively engaging in military commitments. Subsequently, the evaluation of how the Russo-Ukrainian War impacted both its economic and global interactions is vital. China, although considered a developing nation, has the second-largest global economy. As a major trading entity and a key player in global supply chains, the disruptions stemming from the war could significantly affect China’s domestic economy and trade. Analyzing the impact of the war on China becomes pivotal due to its substantial economic interdependence and influence on the global economic landscape (USTR). The European Union, comprising 27 member states, constitutes a substantial economic bloc (European Union). It is a major trading entity with substantial economic ties with the US and China. Additionally, Russia had been a member of the EU until the war started, evidently resulting in the two countries having numerous trade relationships. Assessing the economic impact of the Russian-Ukrainian war on the EU is relevant due to its interconnection with these economies and its role as a major market and trading partner (European Parliament). The time set for this research will be set from 2021 and 2023. This will allow a comprehensive analysis of the economic impact over a specific period that covers the conflict's immediate and medium-term aftermath. This time frame allows the documentation of the initial disruptions and shocks to the economies of Russia, Ukraine, and potentially neighboring countries and examines the subsequent recovery and reconstruction efforts. It provides a reasonable period where changes in trade patterns, investment flows, macroeconomic indicators, and other relevant economic factors that are influenced by the war can be observed. Additionally, including 2023, it allows for a more up-to-date analysis, considering that the scenario may dynamically change over time and new data becomes available. Data from each of these countries will be collected from worldwide institutions such as the Organization of Economic Complexity (OEC) and the World Bank. Both are considered trustworthy sources for collecting data regarding imports and exports due to their robust methodologies, extensive data collection networks, and commitment to transparency and accuracy. The OEC, developed by researchers at the Massachusetts Institute of Technology, provides comprehensive data on international trade, including detailed information on product-level trade flows. Their data collection approach involves aggregating data from official government sources, customs databases, and international trade databases (MIT Media Lab). Similarly, the World Bank, an international financial institution, rigorously collects and verifies data from national statistical agencies, trade documents, and other reputable sources. They employ standardized methodologies and quality control measures to ensure data reliability and consistency (World Bank Group). Additionally, both organizations are committed to transparency as they openly share their methodologies, data sources, and documentation to facilitate research and analysis.

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2. Sectors The data collected will be divided into three sectors that the war had such an impact on due to the trade being ceased: agricultural products, manufactured goods, and natural resources. Table 1 shows a comparison of the range of imports from the three nations in 2021 and 2023.

Natural Resources

Agricultural Products

Wheat

0DL]H

0DQXIDFWXUHG *RRGV

Rapeseed Oil

Sunflower Seed Oil

Cereal

Iron & Steel

)HUWLOL]HU

Y R

$ 854 M

$ 641 M

$ 1840 M

$ 944 M

$ 590M

$ 1.85B

$ 1.03 B

$ 1.25B

$ 2.9B

$ 1.42B

$ 18.7 B

$ 14.7B

$ 1.73 B

$ 2.67B

$ 2.89 B

$ 1.02 B

$ 644M

$ 113 M

$ 7.83B

$ 0.74 B

$ 12.8 B

$ 2.76 B

$ 30.9 B

$ 3.10 B

$ 23.4 B

$ 11.24 B

$ 9.94 B

$ 2.02 B

C H

$ 2.11 B

$ 0.82 B

$ 773M

$ 148 M

$ 2.94B

$ 0.58B

$ 4.69 B

$ 5.55 B

$ 18B

$ 18.4 B

$ 33.3 B

$ 9.42B

$ 2.68 B

$ 0.95 B

>7DEOH )OXFWXDWLRQV RI ,PSRUWV RI 3URGXFWV LQ @

>)LJXUH &KRURSOHWK 0DS RI 5DSHVHHG 2LO @ Beginning the explanation of the impact of natural resources, Ukraine was a heavy supplier of rapeseed oil (World Trade Organization, 2023). Data shows that the 1.87 billion dollar imports in the US decreased from 2021 to 2023—comparably, 1.29 billion dollars of imports in China. The imports in the EU decreased by 213 million dollars: from 854 million in 2021 to 641 million in 2023. From this data, the United States had the most severe economic impact compared to the other two entities. So, Figure 2 shows a big color difference for the United States from 2021 to 2023.

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>)LJXUH &KRURSOHWK 0DS RI 6XQIORZHU 6HHG 2LO @ Sunflower seed oil is also another natural resource that Ukraine has exported to these nations (World Trade Organization, 2023). The map shows that the imports of all three entities have decreased within two years. 531 million dollars of imports decreased in the US, 625 million in China, and 894 million in the EU. Therefore, in Figure 3, although all of the entities in 2023 have a brighter color than in 2021, the EU has the biggest color difference (World Bank, 2022).

>)LJXUH &KRURSOHWK 0DS RI :KHDW @ To then discuss agricultural products, Ukraine was a heavy supplier of wheat (World Trade Organization, 2023). The imports in the US decreased by 6.57 billion and China by 2.16 billion. So, as shown on the map, the color for both China and the US became lighter in 2023 compared to 2021. The EU, in contrast, increased their imports by 1.26 million: from 589.7 million dollars in 2021 to 1.85

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billion dollars in 2023. Subsequently, the color of the EU in 2023 became darker than in 2021 in Figure 4.

>)LJXUH &KRURSOHWK 0DS RI 0DL]H @ Maize is also an agricultural product that Ukraine supplies for these three entities (World Trade Organization, 2023). The imports in the US decreased by 10 billion dollars. The maize supply in China and the EU, however, rather increased. 0.86 billion increase for China, while the EU increased its supply by 0.22 billion. So, in Figure 5, while the US’s color did become lighter, the color of China and the EU became darker (World Bank, 2023).

>)LJXUH &KRURSOHWK 0DS RI &HUHDO @ In addition to that, Ukraine supplied cereal to these trading nations (World Trade Organization, 2023). The US imported 30.9 billion dollars of cereal in 2021, which decreased to 3.1 billion dollars in 2023. China and the EU, on the other hand, have increased imports. China ramped up 0.46 billion, while the EU decreased from 2.9 billion to 1.42 billion (World Bank, 2023). Therefore, only the US has a big color difference, while China and the EU remain similar from before, as shown in Figure 6.

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>)LJXUH &KRURSOHWK 0DS RI ,URQ DQG 6WHHO @ One of the manufactured goods that Ukraine exported was iron and steel (World Trade Organization, 2023). The imports of the US decreased by 12.2 billion, China by 23.9 billion, and the EU by 4 billion (World Bank, 2023). Therefore, although all the entities' imports decreased, China had the most significant change, as seen in the color difference in Figure 7.

>)LJXUH &KRURSOHWK 0DS RI )HUWLOL]HUV @ Fertilizers are among the top manufactured products that Ukraine has exported to these entities (World Trade Organization, 2023). Fertilizers play an essential role in agricultural purposes, as they replenish the nutrients in the soil. The imports of the United States dropped by 7.92 billion and China by 1.73 billion. The EU increased by 0.94 billion: from 1.73 billion to 2.67 billion (World Bank, 2023). Consequently, in Figure 8, the US and China did decrease in color while the EU’s color instead became darker.

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ს 5HVXOWV DQG /LPLWDWLRQV

[Figure 9: Inflation Rates of $JULFXOWXUDO 3URGXFWV@ Studies have shown that if the range of imports decreases, the inflation rate will increase. Since a decrease in imports suggests a reduction in the availability of foreign goods in the domestic market, consumers will shift their preference for domestically produced available goods. Therefore, companies may raise prices to compensate for these increased costs, contributing to inflationary pressures (Hansen, 2023). Ukraine is the leading supplier of agricultural products for all three countries, as studies have shown that Ukraine is the world's seventh-largest wheat producer (USDA, 2022). Subsequently, in the agricultural sector, the US has been the hardest hit by the decline in imports, with its imports of wheat, maize, and sunflower seed oil falling by 96%, 94%, and 97%, respectively. China has also seen a significant decline in imports, with its imports of wheat, maize, and sunflower seed oil falling by 76%, 78%, and 81%, respectively. However, compared to the US and EU, China is a developing country. Hence, although statistics show how greatly China has been impacted, in reality, it does not show much significance through the graph (Tang, 2022). The EU has seen a smaller decline in imports, with its imports of wheat, maize, and sunflower seed oil falling by 44%, 46%, and 51%, respectively. Therefore, although the United States and the EU have shown distinct differences throughout the years in Figure 9, the inflation rates of China remain consistent.

>)LJXUH ,QIODWLRQ 5DWHV RI 0DQXIDFWXUHG *RRGV@

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Ukraine is also ranked fourth globally in terms of the total assessed value of natural resources (Brewster, 2022). The US has been the hardest hit by the decline in imports, with its imports of iron and steel falling by 82%. China has also seen a significant decline, with its imports falling by 58%. The EU, in contrast, has seen a smaller decline in imports, with iron and steel falling by 37%. So, as shown in Figure 10, the US has the greatest inflation rate of 3.6 in 2023, then China at 3.4, and the EU following after.

ტ &RQFOXVLRQ Overall, the data and results clearly show that the Russian-Ukrainian War has notably impacted the various sectors, with all three entities seeing a decrease in imports of key products such as wheat, maize, and sunflower oil. These declines in imports have led to higher prices for these products in the affected regions, creating negative repercussions for consumers and businesses. The war's impact on the agricultural and natural resources sectors has been severe for the US, substantial for China, and relatively milder for the EU. To conclude, the war has significantly impacted the agricultural and natural resources sectors of the US, Europe, and China. The import decline has led to higher product prices, harming consumers and businesses. This can be implied from the evidence which shows that Ukraine is one of the major agricultural suppliers of those nations. The evaluation of the ongoing war has posed challenges in conducting intricate research on its economic impact due to limited data availability. A substantial amount of time was dedicated to data collection efforts. Furthermore, obtaining accurate information has been a struggle, particularly with skepticism surrounding the reliability of statistics from China, where government manipulation concerns have been raised (Reuters, 2022). However, despite these challenges, recognizing the economic significance of Ukraine as a major supplier of agricultural products and natural resources for other nations remains crucial. The economic impact concept's complexity necessitates carefully considering alternative data sources and methodologies to overcome the limitations and enhance the research's comprehensiveness and validity. Possible suggestions include utilizing proxy indicators, qualitative data, or expert opinions to complement the existing data and offering a nuanced perspective on the subject matter. Additionally, seeking collaboration with international organizations or independent researchers may help gain access to more reliable and unbiased data.

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Insights on Korean Perceptions of Chinese Environmental Issues Based on a Big Data Analysis Author 1

Full Name

Kim, Donghyuk

St. Johnsbury Academy Jeju

(Last Name, First Name)

School Name

ABSTRACT: This research is mainly focused on finding a change in Korean perception of China from the period with rapid industry development growth (2010 to 2023). With the significant increase in conflict between Korea and China, this research will make a supporting point about whether environmental factors (especially fine dust and yellow dust) in China are causing a change in perception. Other studies were mostly done through surveys, and interviews focused on specialized and strict opinions of Korean citizens to find their perception. Still, this research used SNS, social networking services, to find naive opinions on Korean perception compared to those two methods. This research found that a relationship between depth of understanding of air pollution after 2010 led to a trend of continuous increase of antipathy toward China.

KEYWORDS: Big Data, Environment, China, Word Cloud, Pollution, Climate Change

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პ ,QWURGXFWLRQ Korea and China have a close economic relationship, but their geographic proximity has also led to shared environmental issues and animosity between the two countries. That said, the yellow dust has become a conversation topic on the environmental front. Since the beginning of the 21st century, South Korea has become more concerned about its environmental issues with the dust from China’s development of industries. With data from Statista showing 325,609 designated size of industrial enterprises in China, it is no surprise that peripheral countries have become wary of China’s industrial consequences, especially South Korea. According to the Department of Chemistry at Jeju National University, South Korea has suffered in a way that reached 2712፠ per ፓ yellow dust rate in March 2010 (Kim & Lee et al.), approximately 18 times more severe than the ‘extremely high’ rate for yellow dust, which claims it is causing a variety of health problems including respiratory, cardiovascular, or weight loss in fetuses; business problems with increasing costs to address environmental issues; and inactivity of people due to being unable to do outdoor activities, unlike usual. As a result of the massive amount of factories in China and the worst yellow dust record in history in 2010, the public raised anger in Korea against China. Keeping this in mind, Korea’s perception of China is in decline, creating unforeseen consequences, with 69.5% of survey respondents agreeing that China is selfish and 65.7% agreeing that China is impolite. It is crucial to determine what factors affect Korea’s perception of China, as finding these factors will help delude the tensions between South Korea and China, alongside providing a fraction of information on how to solve environmental problems between countries as well. The methodology of extensive data analysis on social media will be used to determine Korea's current perception of China. It is effective because the general public’s opinion on SNS (Social Networking Service) can be collected more effectively than in a setting such as public hearings, which could limit viewpoints. This will determine the relationship between Koreans' perception of China in the 21st century in three distinct periods, including 2010 to 2015 (the period developed concerning air pollution), 2016 to 2020 (the period having more focus on solving the issue), and 2021 to the present (the period viewing air pollution in civil perspective).

ჟ 'LVFXVVLRQ %DFNJURXQG RU /LWHUDWXUH 5HYLHZ 1. Environmental Issues in China Despite rapid economic growth over the 20th century, China remains reliant on inefficient and pollutive technologies, resulting in an industrial energy efficiency that is roughly half that of a developed country, which became the world's greatest producer and consumer of coal. Alongside such titles, China is one of the world's most forest-deficient countries. This, in turn, has consequently made China an environment for generating yellow dust (Liu & Jared, 2005). This is prevalent in the environmental sphere as dust storms can cause human disorders of respiratory disorders (including asthma, tracheitis, pneumonia, allergic rhinitis, and silicosis), cardiovascular disorders (including stroke), conjunctivitis, skin irritations, meningococcal meningitis, valley fever, diseases associated with toxic algal blooms and mortality related to transport accidents (Goudie, 2014). About 30% of all deaths in Korea were caused by fossil fuel fine dust, indicating that the level of air pollution has become noticeably fatal to the bystanders of this deadly phenomenon (Lee, 2021). To further emphasize that yellow dust has become a serious problem, data shows that China’s air pollutants also account for neighboring countries. In South Korea, 19 percent of the weekly average PM10 concentrations were affected by season by 12-30 percent. For a period of 10 years (2005-2014), Big Data was used to analyze daily average concentrations of air pollutants and weather monitoring data in South Korea. The data shows that winds

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blowing in the southwest direction have the largest year-round impacts on South Korea's ambient air pollution levels, which is consistent with the direction of emissions from Shanghai, resulting in worse South Korean pollution levels (Kim, 2019).

2. Big Data Analysis for Social Issues Big Data analysis is an effective methodology using machine learning, data mining, computational intelligence, information fusion, the semantic Web, and social networks. The great adoption of social media and mobile technology creates a massive data set as millions of people all around the world use SNSs to upload photos, and videos, update their current status and post daily comments (Sepideh Bazzaz Abkenar & Mostafa Haghi Kashani et al., 2016) (Bello-Orgaz, et al, 2016). This also includes examining social issues as extensive data analysis can be effectively used in a way that requires a large set of data from unspecified groups in an accurate way. According to Pasquale (2017), applying the Big Data analysis method to social issues has been proven to be a more accurate and efficient way to analyze social issues, especially in the contemporary era. In particular, Pasquale conducted a case analysis regarding smart tourism, pointing out that the development of technology has led to more reliable and helps to find more diverse and accurate information. Such examples indicate that the Big Data analysis method is most fit for examining social issues, with the environmental issues regarding China being no exception.

რ 'DWD DQG 0HWKRGV 1. Data As mentioned, this research intends to use Big Data Analysis methods to determine Korea’s perception of China regarding environmental issues. Two factors should be considered to employ the Big Data analysis method. First, it is necessary to set the period of data collection to track the evolution of public sentiment over different periods. Second, spatial range has to be set to prevent biased results.

(1)

Time Scope

a. 2010~2015 The first phase will be from 2010 to 2015. This period was marked by rapid economic growth and environmental damage in China, which began to impact neighboring countries. To go into further detail, China’s economy grew immensely, reaching the second largest economy in the world behind the U.S. (Yao, 2011), causing conflict with the U.S. related to international trading issues such as currency manipulation. During this period, the neighboring countries of China became more suspicious of China, as the air pollution and yellow dust rates would noticeably cause consequences to neighboring countries. This would lead to an increase in participation in diplomatic contacts with China to solve environmental issues.

b. 2016~2020 In the second period, from 2016 to 2020, complaints from Korea became extremely frequent due to the fine dust caused by China. As a result, 62.6% of Korean citizens strongly supported the Korean government's countermeasure of fine dust reduction by compensation and aggressively requested China to do so. As neighboring countries were severely affected by yellow dust, tensions rose against China.

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This period can be recorded as the escalation of tension, therefore serving as a perfect middle point to observe. As the general public is aware of the extent of the effects of fine dust caused by China, the general public has begun to appeal for damages. It was a period when the issues with China began to expand into the realm of personal issues. The noticeable increase in people’s health problems and the damage caused by respiratory diseases: all served as the last straw. The public began to come up with more strict countermeasures and urged their respective governments to develop a more aggressive approach while also pressuring the U.N. and other diplomatic channels.

c. After 2020~ The last period, after 2020, is an essential period with environmental issues. Those who had previously pressured the government have begun to take personal actions like reducing environmental damage through litigation. Such actions are characterized by the fact that people have taken actions into their own hands. No longer are the governments the only proponents trying to solve environmental issues, with people now constructing their Non-Governmental-Organizations (NGOs for short) to relieve the damage. The European Union has already recognized individual legal rights for environmental problems since 2015. These NGOs have been actively demanding civil compensation from the people responsible for the cause of environmental pollution. For example, in 2016, civil lawsuits were filed in various parts of the world, including the Philippines, the Netherlands, Norway, Pakistan, Peru, Switzerland, and the United States, to prevent fossil fuel mining, slow climate change, and keep the environment healthy. Following this phenomenon of people taking measures into their own hands, Asian countries have also begun to take action. Since 2021, Asia has actively engaged in various activities tackling environmental pollution and relieving the damage. Previously, the government relied solely on the nation's policies while focusing on identifying the cause of environmental damage. Such actions have been determined to be lackluster, therefore influencing people to take active action after this period rather than just recognizing environmental issues.

(2) The Scope of Spatial Range The spatial scope of the data collection for analysis is as follows. As mentioned above, opinions online are analyzed to find out the opinions of general people. Such a survey method, which involves only specific people responding, may result in biased results due to the wide scope of the collection. Therefore, online collection has the advantage of minimizing this bias Therefore, to find out people's opinions on the environment and perception, this study targets video materials such as Naver, Google posts and blogs, 17 newspapers and broadcasting websites provided by the Korea Press Foundation, and Facebook, Twitter, and YouTube. In particular, video materials such as YouTube were included in the analysis range based on the provided script.

2. Big Data Analysis (1) Web Crawling Big Data analysis is created with a web crawling method. The web crawling method used a theme dictionary that contains noun words of “perception, awareness, China, and environment.” This word from the theme dictionary is helpful to specify the contents that contain a Korean perception of China. From the theme dictionary, web crawling was applied to the source code given by Google Web crawler, which includes Korean domestic major news, blogs, Social Network Services (Twitter, Facebook, etc), and posts from portal sites. The temporal scoop was divided into three periods: 2010 ~ 2015, 2016 ~ 2020, and 2021 ~ 2023. The HTML source provided by Google Web crawler was converted to Python

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2.7 code and stored in a CSV-type file (comma-separated values file that allows data to be saved in a tabular format). Specifically, Scrapy 1.6, one of the Python plug-in platforms, encoded the source given and elicited the word and frequency value of the word that is related to the theme dictionary and a relative adjective that is on the line by using NLP (natural language processing) chosen by a period created. This method has the advantage of not costing a lot of money, unlike many other methods, such as interviews and extensive research.

(2) Word Cloud Using a CSV format file, it was inserted into a word cloud generator called “R tag cloud generator.” This generator creates a cloud-shaped diagram that shows specific words on the CSV format file by a different size and frequency. A word cloud allows clear visualization: "the ease in which you can try the tools that produce insightful graphics and images. The growing availability of free tools makes it increasingly accessible, even for individuals with little to no experience with design or data analysis” (Brigham, 2016). This benefit is highly effective for Big Data analysis on perception to readers to get an easier understanding.

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ს 5HVXOWV DQG /LPLWDWLRQV 1. Big Data Analysis on the Internet Accounted for the Environment 2010 - 2015

Figure 1[Big data analysis on Korean perception of China in the time range of 2010-2015]

The first period can be considered a recognition period because Koreans were concerned with the unfamiliar topic, air pollution, and needed recognition of that topic. The topic of pollution that was once ignored has changed, as Korea (alongside other East Asian Regions) has begun to study the contamination and air pollution caused by China. In the past, although the public did not have a good grasp on pollution, most East-Asian citizens were well aware of the fact that China had a significant influence on increasing air pollution rates. Consequently, the negative perception towards China heightened with the words that suggest negative connotations, such as aggravating, selfish, terror, etc., would increase in usage. The word terror alludes to the consequences caused by China, specifically, the dust affecting neighboring countries. This not only shows aggression against China but also shows rising tensions between China and Korea. These rising tensions have caused the citizens to target companies and factories in China, such as PetroChina, the first company to hit a 1 trillion market value in 2007, which is being shown on the word cloud. Petro China holds to be one of the biggest oil and gas-producing companies in Asia and produces an immense amount of pollution. Such influences have coerced the public into wanting stricter policies against these companies. With implementing policies

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comes protection, specifically technology that aims to lower pollution. However, the emergence of such amendments proved to be inefficient, with the prior pollution damages being too big to mend with mere policy and equipment. To sum up, from the 2010 to 2015 period Korean citizens mainly focused on air pollution globally, not on their personal effects.

2016 - 2020

Figure 2[Big data analysis on Korean perception of China in the time range of 2016-2020]

The second period can be regarded as an active and publicly focused period. 2014 was the peak of the PM 2.5 rates, with twice as much mean population exposure of PM 2.5 compared to the OECD Average. Consequently, early mortality increased to 4.3 million in South Korea; since early mortality in 2000 by air pollution was 2.9 million, it evinces a significant increase in health issues. The word ‘blame’ and ‘strong-willed’ was the main topic of the 2015 ~ 2020 period because of the censure of air pollution issues in South Korea. The hatred toward China also increased with the words “invasion, racial, selfish, hate, annoyed, censure” as shown on the word cloud. Between January and March of 2017, South Korea had a massive decrease in affection for China from 4.31 to 3.21 within a 0~10 score survey held by a Research & Research company. This shows air pollution affected a notable change in the perception of China; However, this change can not just be defined as a consequence of air pollution on the one hand. In July 2016, South Korea deployed THAAD (Terminal High Altitude Area Defense) to defend against North Korea's missile threat and watch over Chinese movement with its radar system. Hereafter, the

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Chinese started retaliating economically by prohibiting travel to Korea. It led to a detrimental effect on Korean companies targeting Chinese travelers, and the Hyundai car company couldn’t have increased its sales by exporting its cars to China. Though China’s action of economic retaliation was not severe since they did not prohibit the trade of rare earth elements, an essential source of building semiconductors, Korea did not suffer massive damage. Therefore, THAAD issues would not have affected the major's negative perception of China. In this period, there was more global focus on climate and environmental issues rather than personal ones. Koreans wanted neutrality with legislation accounted for by the committee as words (landfill, plastic, water, waste, green, ESG) indicate it. In parallel, as ‘strong-willed’ and ‘solving’ shows in the word cloud, Koreans were enthusiastic and aggressive in solving the pollution. In fact, according to KEI, the Korea Environment Institute, they claimed that over 70 percent of Korean citizens have a significant interest in environmental issues. 72.4 percent of Koreans were willing to participate in the Citizen practice movement for reducing fine dust. The Koreans viewed air pollution as a public problem, not as their individual. To sum up, Korea had the stance of blaming the Chinese as a main factor of air pollution creation but also had the will to solve the problem for the public.

2020 - 2023

Figure 3[Big data analysis on Korean perception of China in the time range of 2020-2023]

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In the third period, the focus on environmental issues had shifted from global to personal and civil issues, which is wanting compensation as an individual, not by a country. Words like “cancer, atopy, asthma, individual values, hair loss, deformity, fetus, respiratory” show that concerns about health issues accounted for with air pollution began the major view of the baneful effect of pollution. The more interest in health issues increased the interest in litigation or suing and getting compensation as the word “compensation” in the word cloud has the biggest size. For instance, KDCA, Korea Disease Control and Prevention Agency, claimed Korea had reached a peak atopy rate in 2020. The Ministry of Environment announced that atopy is significantly accounting for air pollution. This increase in disease rate is possibly to be one of the reasons for increased interest in getting compensation from China for their suffering from the disease. There were actions to get compensation from China for the damage received from air pollution that is created in Chinese territory. In December 2020, 7 Korean citizens and Choi, the CEO of the Korean Environment Foundation, had litigation for damages about the Chinese government not having countermeasures and control of fine dust However, all of the actions could not be compensated since China responded with the principal of exemption from sovereignty under international law, saying that answering or attending the lawsuit itself could violate China's sovereignty and security. In addition, there was a new category of interest: which is education. There could be an addition of education categories because the perspective on air pollution and climate change has been changed. The period before 2020 had active words such as planning (suggesting that there is no plan yet), urge, switch, and demand which is very aggressive in solving the issue in the short term as soon as possible. However, words like a plan (meaning that plans are made) and youth in the third period show that the focus had gradually changed to solve this problem until the next generations. This could have led to increased interest in Koreans educating their children to overcome the climate crisis for a longer period than before. One more additional topic of interest was money and business using environmental issues. According to the Renewable Energy Agency, China is rapidly increasing its renewable energy installation by reaching half of its 1,200 GW target by installing 635 GW of wind and solar capacity and becoming the largest offshore wind market in the world. To that, the interest in funding renewable energy businesses in the Chinese market could have increased. Consequently, one of the biggest renewable energy companies, the Power Construction Corporation of China, had a massive stock price increase in July 2021 by over twice. In the last, there was more interest in movement and campaigns. Social media could have spread a new trend in the environmental movement, which also increased interest in campaigns and environmental organizations of UNEP and ESG. In short, the third period had a perception of China and the environment as an “issue to solve” and a “personal problem” which is having a process and air pollution is significant on their health.

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2. General Korean Survey by Pew Research

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a) 2010 ~ 2015 In a survey of the 2010 ~ 2015 period based on the Pew Research Center, South Korea had equal rates in favorable and unfavorable or even had more favorable rates than unfavorable rates in the early period. However, after having a peak increase in 2015, there was a sudden decrease in the favorable rate.

b) 2016 ~ 2020 In a survey of the 2016 ~ 2015 period based on the Pew Research Center, the graph shows that Korean perception toward China keeps getting worse. In 2017 the increase in negative perception stopped and there was a slight increase in positive perception of approximately 5%. Nevertheless, the negative perception increased after that point.

c) 2021 ~ 2022 In a survey of the 2010 ~ 2015 period based on the Pew Research Center, the Korean perception toward China keeps getting worse. By the end of the graph, which is 2022, it recorded the lowest point of favorable rate.

3. Compare and Contrast Between Big Data Analysis and General Survey By accounting for Big Data analysis on the Internet and survey results from Pew Research, it can find one insight. Big Data analysis designated that the Korean citizen had a shift in understanding toward air pollution and more interest in personal compensation by the trend of the period, and a survey which indicated an increase of negative views by time shift from 2002 to 2022 shows that better understanding of air pollution and interest on personal compensation led to increasing of negative perception toward China.

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4. Limitation This Big Data analysis has limitations. The Big Data model is done on Social Networking Services, which is not causing bias on geological or under-expression of citizen’s opinions. Still, they may create bias based on people’s age and aggression. Although the Internet is widely available in South Korea, some elders cannot access the Internet or do not actively use it. With these concerns, there is the possibility of collecting biased results in collecting heavy internet users, primarily young generations. With the characteristic of the internet providing an anonymous environment, people on the internet get aggressive and overly express their opinions. Especially since the perception highly fluctuates with people’s aggressiveness, it is possible to create more aggressive results.

ტ &RQFOXVLRQ With the increasing concern about Koreans toward air pollution and the decline of Korean perception of China, this research tested the shift of Korean perception toward China. The Korean perception of China was tested by Big Data analysis and a survey done by Pew Research. The temporal scope for this research was from 2010 to 2023, which has a most fluctuating change of perception by the appearance of severe air pollution in South Korea and globally. Comparing two different focuses of data which is broad in the causal effect of Korean perception on China and Big Data analysis which is only focused on the environmental effect. As a result, it came up with the final assumption that a better understanding of air pollution would lead to a decline in the Korean favor view of China. This hypothesis can be further supported in building a plan to enhance the relationship between Korea and China or other countries that conflict with an environmental issue.

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Entwined Economies: Exploring Evolving US-China Relationships in a Globalized World — is it in the US’ interest to decouple from China economically? Author 1

Full Name

Kim, Junseo

Korea International School, Jeju Campus

(Last Name, First Name)

School Name

ABSTRACT: The intricate and evolving relationship between the United States and China is of paramount importance in our globalized world. This paper delves into the multifaceted dimensions of this relationship, considering the potential impacts of economic decoupling and China's Belt and Road Initiative (BRI) on both nations. It explores the interconnected nature of their economies, detailing the complexities of supply chains, market integration, and collaborative ventures. Highlighting the potential economic consequences of decoupling, the paper discusses impacts on consumers, businesses, and employment opportunities. Furthermore, it examines the implications of the BRI for global trade dynamics, addressing concerns about Chinese economic dominance and the potential for nations to align with China's economic policies. The paper also assesses the potential effects of decoupling on the value of the US dollar, considering the impact of China's holdings of US assets. To navigate these challenges, the paper proposes a multifaceted strategy, emphasizing sustained engagement, diplomacy, multilateral cooperation, people-to-people interactions, economic collaboration, technology partnerships, and strategic alliances. It concludes by advocating for a nuanced approach that values dialogue, cooperation, and shared prosperity, envisioning a future where the US-China relationship is characterized by mutual benefit and collaboration in an interconnected world.

KEYWORDS: Belt and Road Initiative (BRI): This is China's ambitious global infrastructure and economic development strategy, aiming to connect Asia, Europe, and Africa through a network of roads, railways, ports, and other infrastructure projects. The BRI seeks to enhance connectivity, trade, and investment among participating countries, but it also raises concerns about China's increasing influence and potential geopolitical implications. Economic Decoupling: Economic decoupling refers to the process of reducing or severing economic ties between two countries. In the context of your paper, it refers to the potential scenario where the United States and China significantly reduce their economic interdependence, such as trade and investment, due to various geo-political or economic reasons. Supply Chains: Supply chains are networks of companies and processes involved in producing and delivering goods and services to consumers. In a globalized world, supply chains often involve multiple countries, with each contributing specific components or stages of production. For example, a smartphone's supply chain might include components manufactured in different countries and assembled in yet another country before being sold globally. US Dollar Value: The US dollar value refers to the exchange rate of the US dollar compared to other currencies. It represents the purchasing power of the dollar on the global market. Changes in the US dollar's value can have significant economic implications, affecting trade, investments, and inflation in both the United States and other countries.

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PAPER: In an era when global interdependence has become the bedrock of wealth and progress, the relationship between the United States and China has emerged as a vital axis, changing the fundamental fabric of our linked world. Currently, the ever-evolving geopolitical landscape of the bipolar world has caused tensions to rise and economic decoupling conversations to steam, creating a focal point of international concern. The military and economic growth of China, exemplified by its grandiose Belt and Road Initiative (BRI) program, is at the heart of this complicated dynamic. Given the complicated web of dependency and competitiveness that defines their presence in our multipolar world, the United States must wonder whether it is in the best interests of theirs to consider economic decoupling from China. It is also critical to remember that minimum-scale alternative solutions will not solve the complex difficulties that lie ahead. As we engage on this voyage of discovery, imagining a society where mutual prosperity and cooperation are cherished, we will reveal a transforming road ahead via the prism of nuanced partnership, rather than the sentiments built upon aggravated animosity. Decoupling from China could have profound and far-reaching economic consequences for American consumers and businesses, given the intricate and interconnected nature of the economic partnership between the two countries. The extensive supply chains, integrated markets, and collaborative ventures that have developed over the years have facilitated the exchange of goods, services, and investments, resulting in significant benefits for both nations (Siripurapu and Berman, 2022). To maximize these benefits, today, the US bases its imports mostly from products that are made in China, while China also functions as one of the largest export markets for U.S. goods and services. In 2021, China functioned as the third-biggest trade partner of America (Bureau of Industry and Security, 2021). 8.6% of total U.S. exports, pricing up to 1.8 trillion dollars of national income, were exported to China—17.9% of total U.S. imports, accumulating up to 2.8 trillion dollars, were imported from China (Washburn, 2023). From this data, it can be analyzed that America based about one fifth of its imports from China, and how difficult will it be for the United States to recover from the loss of imported products should they decouple from China. It will take a long time to find other countries to fill up the amount of imports that has a value of 2.8 trillion dollars, during which the United States will inevitably go through an economic loss until they find another “resource mine.” The following data table illustrates the type of products and their respective worth, among the United States imports from China.

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As a wide range of Chinese commodities were imported to the US in massive quantities, consumers have been able to buy products at a cheaper price while companies were able to maximize their benefits by inducing more product consumption through selling their products at a more customer-friendly price. Furthermore, maintaining the current trade agreement with China lowers inflation (Lardy, 2001). It has also been found that trade with China contributes significantly in creating jobs for American workers, exports to China supporting over 1 million jobs and Chinese companies that have invested in the United States employing more than 150,000 workers (US-China Business Council, 2022). The potential disruption to international supply networks is one of the main issues with decoupling. In order to satisfy domestic demand and support their production methods, many American companies substantially rely on imports from China. China supplies vital items and materials that support American enterprises and gratify consumer demands, from consumer electronics to car components and pharmaceutical chemicals (Varadarajan and Varas, 2020). The search for alternate sourcing and manufacturing arrangements would result in bottlenecks, delays, and increased prices if existing supply chains were to be disrupted through decoupling. As a result, American consumers may see price increases on a variety of commodities, including furniture and electronics as well as apparel and home goods. In addition, China’s economic growth has been skyrocketing, being an important source of global demand. Though it might short-term decrease commodity demand, its economic rebalancing will open up new chances for manufacturers that export their products. Through commerce, investment, and ideas, China has also been wielding an increasing impact on other emerging nations' economies. US companies do a significant amount of business on the ground there. According to 2023 data from The World Bank In China, sales by American companies invested in China reached $370 billion. That is more than double the value of US exports to China. Companies can then reinvest in R&D and develop cutting edge technologies, which contributes to the United States’ position as a leader in global innovation. Consequently, it has become increasingly important for US companies to access the growing Chinese market. For many products, it is critical for companies to be close to its largest customers. With China having lots of people with rapidly increasing levels of economic capacity, commercial relations with China will remain important. The Chinese economy will increase by 5.2 percent for 2023; meanwhile, there would only be a 2.9 percent increase for the world economy (IMF, 2023). This means global competitiveness for multinational corporations depends on their success in the Chinese market. In response, companies such as Apple and Google have been moving Final Test & Assembly centers to nations like India. IPads are now made in northern Vietnam, Microsoft’s Xbox game consoles come from Ho Chi Minh City, and Amazon’s Fire TV devices are manufactured in Chennai, India. In the past, all of these items were exclusively produced by the Chinese workforce (Wakabayashi and Mickle, 2022). However, this move is only a band aid that is unable to mitigate the potential economic loss by decoupling from China. Final Test & Assembly it is labor intensive but does not require skilled labor (Lewis, 2006). It might be possible to get some Chinese manufacturing and sourcing partners to open operations in nations like Vietnam and Malaysia. Local labor would be used, but the skilled management and key personnel would be Chinese. Other companies are making this transition. However, this is a slow process and it takes years to build up a similar level of expertise. Moreover, some of these nations have their own challenges. For example, according to the Global Organized Crime Index, Vietnam has a 6.28 criminality score, poor transportation infrastructure and an organized crime problem. Decoupling would also make American companies less competitive in the global economy. Many American businesses have found China to be an appealing production location due to its strong manufacturing capabilities, low production costs, and access to a sizable consumer market. American businesses have been able to remain competitive globally and provide consumers with cost-effective products by utilizing China's skilled labor population and advanced industrial infrastructure. Decoupling would compel businesses to rethink their production plans, which would result in increased production costs, fewer economies of scale, and decreased competitiveness on the global market.

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Finding alternative suppliers or setting up new production facilities could be extremely difficult for small and medium-sized businesses, endangering their survival and possibilities for growth. Decoupling can also have a detrimental effect on employment opportunities in America. The establishment of jobs in a number of industries, including manufacturing, technology, and services, has been made easier by the country's economic ties with China. Directly and indirectly, employment possibilities have been encouraged by Chinese demand for American goods and services in a variety of sectors and locales. Jobs may be lost if this economic interdependence is disrupted, especially in industries that rely significantly on interconnected supply chains or exports to China. The negative effects on employment could be amplified if the ripple effects spread to allied industries and sectors that depend on the affected enterprises. According to McDaniel, if the United States separates from China, its economy will contract because 40% of US imports from China, or 1.26% of GDP, would. The United States must also keep in mind that 21% of its imports, a significant economic sector that accounts for 15% of total American consumption, come from China (McDaniel, 2022). As 3.15% of the U.S. GDP is made up of imported goods and jobs associated with them, a decline in the standard of living for each individual is inescapable. Hence, unilateral decoupling measures could disrupt these intricate economic linkages, leading to higher costs, reduced competitiveness, and negative effects on employment in both countries. While concerns about trade imbalances and infringements on intellectual property rights continue, it is important to handle these problems cautiously and in the long run. To safeguard American interests without endangering the broader economic benefits received from the US-China commercial relationship, it is crucial to address these issues through focused negotiations, enforcement measures, and cooperation agreements. It is possible to correct economic imbalances and encourage more reciprocity by looking at alternative options, such as trade agreements, to level the playing field and assure fair competition. Initiatives should also emphasize strengthening intellectual property protections and maintaining present laws and regulations. This can be achieved by promoting bilateral and multilateral interactions, enhancing R&D collaboration, and aiding homegrown innovative industries By adopting a balanced strategy that addresses these problems while upholding the benefits of economic integration, the US can manage the complexities of the US-China relationship and support a mutually beneficial economic environment. Decoupling from China, in conclusion, would negatively impact American consumers, businesses, and employment. Among the possible economic repercussions of decoupling are supply chain disruption, cost growth, diminished competitiveness, and job losses. As a result, it is crucial to take prudent measures to resolve trade imbalances and abuses of intellectual property rights without jeopardizing the larger economic benefits associated with the US-China economic partnership. By doing this, the US may find a balance between upholding its interests and promoting an economic partnership that benefits both parties. China's Belt and Road Initiative (BRI) presents both economic and political challenges that need to be carefully considered. As China seeks to strengthen its global presence and increase its geopolitical influence through massive infrastructure projects and investments, concerns arise regarding the potential threats posed by the BRI to the United States and its allies. Economically, the BRI raises concerns about Chinese domination in the international market. By financing and constructing major infrastructure projects across Asia, Africa, Europe, and beyond, China aims to enhance connectivity and facilitate trade routes, ultimately expanding its economic reach. In 2022, the added value of BRI finance and investments accumulated as much as 67.8 billion dollars, the digit being 68.7 billion in 2021. Nations have also been growing active in their level of BRI engagement, the investment levels reaching up to 48% in 2022, while it was only 29% in 2021 (Green Finance and Development Center, 2022). Since 2013, funds collected through BRI engagement have accumulated

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up to 962 billion dollars, 573 billion dollars coming from construction contracts and 389 billion dollars coming from non-financial investments.

This has led to apprehensions that the BRI could create an economic network heavily influenced by Chinese interests, potentially sidelining other players in the international arena, including the United States. The sheer scale and scope of the BRI projects, coupled with China’s substantial financial resources, provide China with significant leverage and the ability to shape economic norms and standards (Li et al., 2022). This raises questions about the extent to which the United States can effectively compete in these regions and maintain its influence in the face of China’s expanding economic presence.

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Furthermore, the BRI's economic power may cause a cascade of nations to switch to China as their primary trading partner. According to Jie and Wallace (2021), China can foster an atmosphere that is favorable for expanded trade and economic cooperation by investing in infrastructure development and trade facilitation initiatives in BRI partner nations. This might encourage states to place greater emphasis on their economic connections with China than with other countries, such the United States. As a result, it might be difficult for the United States to preserve current business links and find fresh business possibilities in the BRI's target territories. Countries may align themselves with Chinese policies, rules, and standards as they integrate more deeply into China's economic system, strengthening China's influence and potentially undermining US interests. To make matters worse, China is the top supplier of imports to the US, selling $536.3 billion worth of goods in 2022, according to the Office of Technology Evaluation under the US Department of Commerce (2022). China's exports to the country climbed at an average pace of 15.5 million dollars, starting from a low of 130,000 dollars in 1983 (Trading Economics).

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The process won't be simple due to China's Belt and Road Initiative's success, as the U.S. would be too late to forge new relationships with other nations since China has had a head start in doing so with potentially "nutritious" countries that the U.S. may do so. Should the US decouple from China, they will have to find other nations to cover up for this significant amount of loss from the goods acquired through Chinese imports. Decoupling might not be the best course of action for addressing the potential dangers posed by the BRI. Instead, in the face of China's growing power, the United States may capitalize on its own advantages to compete favorably and protect its interests. For instance, the United States continues to have a significant advantage in military technological innovation (Luckenbaugh, 2023). The United States can ensure its position as a global leader in cutting-edge technologies by continuing to invest in research and development, encouraging entrepreneurship, and upholding a favorable regulatory framework. This can lower the likelihood of lagging behind in important industries and boost American competitiveness against China. The US can also establish strategic ties and alliances with nations taking part in the BRI. The United States can strengthen diplomatic and economic connections with BRI partner countries, balancing China's influence and advancing common goals and principles. Through this cooperative strategy, the United States may interact with BRI nations, provide alternative investment opportunities, and encourage openness, good governance, and sustainable development (McCarthy, 2022). Achieving this alignment with international standards and norms while also defending US interests and values can help determine the BRI's future. Hence, despite the fact that the Belt and Road Initiative poses political and economic difficulties for the United States, responding by decoupling may not be the best course of action. Instead, by utilizing its

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technological innovation, creating strategic alliances, and cooperating with BRI participant nations, the United States can compete successfully. With this strategy, the United States can counterbalance China's growing influence, provide alternative investment opportunities, and advance its interests and values in a shifting international environment. The United States can manage the Belt and Road Initiative's intricacies and defend its place in the international arena by taking a sophisticated and aggressive approach. A significant concern associated with the decoupling of the United States and China is the potential impact on the value of the US dollar. If decoupling were to occur, there is a possibility that China may choose to call in its holdings of US Treasury bonds and other US assets as indicated by this year’s trend of falling US treasury holdings by Chinese investors (Nikkei, 2023). As the largest foreign holder of US debt, China's decision to sell or reduce its US holdings could have significant repercussions for the value of the US dollar and the stability of global financial markets. Without undertaking extensive research and analysis, it is difficult to gauge the impact's size on the US dollar. The size of China's divestment, how other market participants responded, and how central banks and monetary authorities responded would all have an impact on the result. It is critical to take into account all possibilities and evaluate the potential rippling effects on asset prices, investor mood, and global currencies. The value of the US dollar might be under pressure if China were to sell off a significant amount of its US assets. As China converts its holdings into other currencies or assets, there may be a greater supply of US dollars on the market as a result. For a variety of stakeholders, including businesses, consumers, and investors, the US dollar's decline might have far-reaching effects. For businesses, a declining US dollar would have an effect on the price of imports, particularly those from China, as the US dollar's relative worth falls. This might result in higher import costs for goods and raw materials, thus reducing profit margins and reducing the ability of US businesses to compete internationally (US Bureau of Labor Statistics, 2022). A decline of the US dollar could make it more expensive for foreign investors or lenders to enter the US market, which could pose problems for enterprises that depend on foreign funding or investment. A weakening US currency can potentially have an impact on consumers. The cost of imported products, such as electronics, apparel, and cars, could rise, thus resulting in a decrease in purchasing power. A weakened US currency would make travels overseas more expensive for American tourists, which could also have an effect on travel and tourism (Iacurci, 2023). According to the 2023 Hopper Consumer Travel Index, 34% of US travels will be destined for cities in Europe, while 28% are to cities in Asia. If the dollar weakens, international trips will cost more for US travelers. The atmosphere would be complicated and uncertain for investors. As investors look for more stable currencies or alternative investment possibilities, a decline in the value of the US dollar might cause capital to leave US markets. This might increase market volatility and possibly have an impact on asset prices in different industries. To effectively manage their portfolios, investors owning US assets would need to carefully evaluate the risks that could arise and take diversification methods into account. The entire effects of China selling its US holdings and the subsequent decline in the value of the US dollar, however, would rely on a variety of factors, including how authorities and market participants react. It is possible for central banks and monetary authorities to take action to stabilize their own currencies and lessen the impact of capital flows (New York Times, 2022). Governments and international organizations can also put policies into place to support stability and reestablish trust in the global financial system. Understanding the relationships and dynamics at play in detail is essential given the potential ramifications for the US dollar and international financial markets. Decoupling's possible effects on the US dollar's value must be evaluated further in order to establish risk-mitigation and stability-maintaining methods.

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As a result of the decoupling between the US and China, there is a chance that China would sell its US holdings, which might cause the US dollar to weaken. The precise effect on the value of the currency depends on a number of variables and would take careful investigation and analysis to completely identify. However, it is crucial to be aware of any potential repercussions and to take into account the economic implications of decoupling, including how it can affect investors, firms, consumers, and the stability of global financial markets. To ensure a stronger relationship between the United States and China and prevent the undesirable outcome of decoupling, a multifaceted strategy is required. First and foremost, sustained engagement is essential. Maintaining open channels of communication and fostering dialogue at various levels of government and society can help bridge the differences and build understanding between the two nations (Hass, 2023). This could involve regular high-level exchanges, diplomatic talks, and bilateral meetings provide platforms for constructive discussions on areas of common interest and concerns. In handling disagreements and confrontations between the United States and China, diplomacy is essential. Both nations must place a high priority on diplomatic efforts to settle differences amicably. This entails making use of already in place forums, such the Strategic and Economic Dialogue, to address difficult problems and look for win-win solutions (Freeman and Glaser, 2011). Strong diplomatic efforts can foster stability, ease tensions, and stop escalations that might cause the partnership to fall apart. Another key component of enhancing the US-China relationship is multilateral cooperation. Both nations should actively participate in international forums and cooperate on issues of shared concern, such as climate change, global health, and nuclear non-proliferation, in recognition of the interdependent character of today's global challenges (Reuters, 2023). The United States and China can show their commitment to international stability and deal with shared threats that cut beyond national boundaries by cooperating within multilateral structures. Furthermore, for strengthening the relationship between the two countries, trust-building and improving people-to-people encounters are essential. According to a study by the Open Doors Project, cultural ties through media, journalism, studying abroad, and tourism between the US and China reached a significant low point (The Guardian, 2023). Greater mutual understanding and respect can be fostered by fostering cultural and educational exchanges, encouraging tourism, and facilitating commercial partnerships. Stereotypes and false beliefs can be removed, resulting in a more beneficial and peaceful relationship, by developing links and encouraging pleasant encounters between inhabitants of both nations. Economic cooperation must also be given priority in order to stop decoupling and advance a stronger US-China partnership. Given the significance of trade and investment relations between the two nations, efforts should be made to address issues with trade imbalances, intellectual property rights, and market access through constructive talks and agreements (Bateman, 2022). Both countries profit from keeping their economic connections open and equitable since it enables the exchange of goods, services, and investments that spur economic expansion and job creation. Another area where cooperation in technology can improve the relationship is in communication. The United States and China can combine their respective capabilities to address global challenges and progress technology by developing cooperative research and development projects, sharing scientific knowledge, and innovative partnerships. This partnership has the potential to enhance quality of life, promote economic success, and tackle important global problems including energy transition and sustainable development. Strategic partnerships and alliances can also be extremely important in preserving a strong US-China relationship. A strong foundation for collaboration may be established and assist counterbalance China's expanding influence by strengthening current alliances, such as those with European and Asian nations,

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and creating new partnerships based on common values and interests. The United States can effectively address shared concerns and influence the global order in a way that is consistent with its interests and values by utilizing the collective power and influence of like-minded states (The Brookings Institution, 2023). Thus, developing closer ties between the US and China necessitates a holistic strategy that prioritizes engagement, diplomacy, multilateral cooperation, people-to-people interactions, economic collaboration, technology collaborations, and strategic alliances. By aggressively pursuing these options, the two nations can resolve their differences, handle conflicts, and advance stability, averting the unfavorable consequences of decoupling. In an increasingly interconnected world, a positive and strong US-China relationship benefits both countries' interests as well as the world's peace, prosperity, and cooperation. Despite worries about economic separation being stoked by US-China tensions, a careful analysis exposes the necessity for a nuanced strategy. When it comes to tackling political, economic, and security challenges, decoupling could not produce the desired results. In order to safeguard its interests, sustain economic advantages, and successfully manage the changing US-China relationship, the US should instead give priority to dialogue, diplomatic initiatives, and multilateral collaboration. The US can handle the difficulties presented by China while honoring its values and advancing global stability by implementing this all-encompassing policy. In a nutshell, at an era of global interdependence, the complex relationship between the United States and China necessitates careful study and nuanced methods. While some find the notion of economic decoupling from China appealing, it has substantial and far-reaching economic ramifications for both American consumers and enterprises. The complicated and linked structure of the two countries' economic collaboration has resulted in enormous benefits for both, and any abrupt divorce might disrupt supply networks, increase consumer costs, and severely harm job possibilities. Likewise, China's Belt and Road Initiative (BRI) poses both economic and political problems. While concerns about Chinese dominance in the world market and future shifts in trade allegiances are genuine, reacting to the BRI through decoupling may not be the most effective method. Instead, the United States may leverage on technical innovation, form strategic alliances with BRI member nations, and promote alternative investment possibilities to compete favorably and protect its interests in a changing global context. Besides, the possible influence on the value of the US dollar in the case of decoupling must be carefully evaluated. China's holdings of US debt and assets provide substantial leverage, and any unexpected disengagement might lead to a depreciation of the US currency and broader ramifications for businesses, consumers, and investors. Proactive steps and regular monitoring of market dynamics are required to guarantee stability and reduce hazards. In negotiating the tight web of dependency and rivalry between the United States and China, a balanced strategy emphasizing collaboration, negotiation, and the protection of national interests is necessary. Rather than succumbing to economic division or rising hostility, it is vital to envision a future of shared prosperity and partnership. By addressing trade imbalances and intellectual property issues via focused dialogues and cooperative agreements, the United States can develop a productive economic cooperation while safeguarding its essential beliefs and interests. The United States has the chance to demonstrate its resilience, adaptability, and leadership in a multipolar world throughout this voyage of discovery. The United States can effectively handle the intricacies of the US-China relationship, develop strategic partnerships, and remain competitive on the global arena by embracing a nuanced and aggressive policy. Let us approach the future with pragmatism, innovation, and a dedication to creating a society where mutual prosperity and collaboration are valued, so that this century is one of unprecedented growth and prosperity.

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The Association between Islamophobia in South Korea and the Perceived Distance of Muslims Author 1

Full Name

Lee, Haejun

Hankuk Academy of Foreign Studies

(Last Name, First Name)

School Name

ABSTRACT: In 2022, Islamophobia in South Korea rose to attention after locals in Daegu gathered to halt the establishment of a mosque that was ruled lawful by the Supreme Court. Since Islamophobia is becoming more and more salient as the Muslim population in South Korea has been increasing, we analyzed the mechanism by which Islamophobia appears in South Korea by implementing the concept of perceived distance. Perceived distance refers to the physical distance between in-group and out-group as judged by an individual. The four cases we chose to analyze are the 2008 Islamophobia spread by Christian media, the 2015 ISIS and Syrian refugee crisis, the 2018 Yemeni refugee crisis, and the 2021 Daegu mosque crisis due to them covering different dimensions of factors that affect perceived distance. We found that the concept of perceived distance was effective in explaining the mechanisms that led to the previously noted four Islamophobia outbursts. This gives a positive outlook for combatting Islamophobia in South Korea as known measures to attenuate the effects of perceived distance may be applicable.

KEYWORDS: Islamophobia, South Korea, Physical Distance, Inter-group Threat, Perceived Distance

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Introduction In December 2022, a group of protesters gathered in Daegu to demonstrate their hostility towards a new mosque that was in the midst of construction. They organized a barbecue party in front of the mosque and put the carcasses of pigs on display in order to deter Muslims. Such movements indicate the rise of Islamophobia in South Korea; there have been more than twenty mosques established in South Korea by 2022, but this is the first time such a large-scale antipathy was expressed outwards. How, can such Islamophobic outbursts be explained in the South Korean context? While multiple previous research focused on analyzing Islamophobia in Europe or North America, Islamophobia in the South Korean context has not been understood well yet. Recent research regarding ethnic diversity and trust may provide insight. A meta-analysis of ethnic diversity and trust found that the two factors had a negative correlation. The insight from this research gives clues to understanding why Islamophobia is strengthening in the face of an increase in the influx of Muslims of various ethnicity; however, this result alone cannot explain the suddenness of this phenomenon. The shortening of physical distance between Muslims and Korean locals does seem to play a role in inciting Islamophobia, but this approach alone has flaws. Since research surrounding Islamophobia in South Korea focused more on its presentation and effect, we would like to focus on the potential causes of Islamophobia. To better understand the mechanism by which Islamophobia is fortified, we implemented the concept of perceived distance. Perceived distance refers to the judgment of physical distance between the ingroup and out-group. Using this concept, the four instances of Islamophobic outbursts in South Korea will be analyzed and explained: the appearance of Christian media as the primary Islamophobic entity in 2008, the rise of Islamic State(ISIS) and the Syrian refugee crisis of 2015, the Yemeni refugee crisis of 2018, and the Daegu Mosque conflict of 2021. These four incidents were chosen not only because of their significance in shaping Islamophobia in South Korea but because of their unique characteristics in terms of physical and perceived distance combinations that set them apart from each other. Focusing on these four cases reveals that perceived distance effectively explains the mechanism by which Islamophobia was strengthened despite the varying factor dimensions. Finally, the implication of this study and possible measures to remedy the problem will be discussed.

Literature Review Theoretical Background Islamophobia refers to “indiscriminate negative attitudes or emotions directed at Islam or Muslims” (Bleich, 2011). Now that the definition of Islamophobia has been established, the general trend in social conflicts rising from different groups residing in the same area can be analyzed to gain insight into the nature of Islamophobia. As stated above, the meta-analysis of ethnic diversity and social trust found that increased ethnic diversity is related to decreased social trust (Dinesen et al., 2020). In this paper, the researchers divided social trust into several categories including generalized trust, in-group trust, out-group trust, and trust in neighbors. They found the strongest negative correlation in trust in neighbors while the correlation was intermediate for in-group and generalized trust. They concluded that ethnic diversity impacted people’s trust on a local scale the most, and also that people were most influenced by ethnic diversity experienced at a local scale. This research is of value for our purpose since the influx of Islam into South Korea is strongly associated with an increase in ethnic diversity as most Muslims in South Korea are of an ethnicity different from Korean. Since social mistrust is a negative emotion, the incitement of mistrust may be understood as the creation of Islamophobia according to our definition of it. In such a case, this paper implies that the increased proximity of Muslims would be correlated with an increase in Islamophobia. However, as seen from the Daegu crisis surrounding the mosque establishment, this theory alone does not explain the suddenness of the crisis despite the steady increase in the Muslim population in the region. To address this, the relationship between physical distance and inter-group threat can help us

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better understand this phenomenon. To define inter-group threat, “intergroup threat is experienced when members of one group perceive that another group is in a position to cause them harm” (Nelson, 2009). A study examined the US-Mexico border, cross-town rival universities, and baseball fans to better understand how threats and other factors affected our perception of physical distance (Xiao et al., 2016). This perception of physical distance will be referred to as perceived distance from now on. The study was founded upon previous findings that increased threat of an out-group led to shorter perceived distances (Cole et al., 2013); this study found that shorter perceived distances led to greater conflicts between groups. We think this concept of perceived distance can explain most Islamophobic outbursts in South Korea. Perceived distance has its basis in physical distance, but can shrink or lengthen depending on psychological effects from surroundings. We expect the social factors with the greatest effect on the perceived distance of an out-group to be policies regarding them and media coverage; but since South Korea does not have a specific policy that targets Muslims, media coverage would have the greatest effect on shaping the perceived distance of Muslims in South Korea. Past research has shown that exposure to threatening news changed people’s attitudes toward the human rights of immigrants, suggesting media coverage of threats has a direct effect on intergroup threats (Seate et al., 2016). Thus, media coverage would affect the inter-group threat that in turn influences the perceived distance. With this understanding, we can organize the factors that shape the perceived distance between locals and Muslims in South Korea. First, there is the physical distance. Physical distance is the most important factor in determining perceived distance as the entire distance judgment has its basis in real-life distance. Second, there is the inter-group threat. The greater the threat, the shorter the perceived distance appears to be. Third, there is the media coverage of the out-group. The media coverage affects the perceived threat of the out-group, and this inter-group threat affects perceived distance as stated before. Finally, previous research suggests measures that influence inter-group interactions such as barriers or apologies influence the perceived distance between the two groups (Xiao et al., 2016). This framework will be used to analyze the turning points of Islamophobia in South Korea. To visualize this framework, a figure is provided below. Figure 1 Framework for Understanding Perceived Distance and Islamophobia

Note. Rectangles refer to factors, while rhombi refer to real-life results.

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Analysis of Islamophobia in South Korea The framework above can be used to analyze why certain events led to Islamophobic outbursts. To illustrate this, four cases of Islamophobic outbursts in South Korea will be analyzed using the framework: the 2008 Islamophobia by Christian media, the 2015 ISIS and the Syrian refugee crisis, the 2018 Yemeni refugee crisis, and the 2021 Daegu mosque crisis. These four events were chosen because they each cover a different dimension regarding the factors that affect the perceived distance. The two factors we focused on were physical distance and inter-group threat. Table 1 clarifies the relationship between the two factors and the four events. As for the earlier two events, there is not a significant change in either of the two factors; on the other hand, the latter two events are characterized by a shift in one of the two factors. In the 2008 Islamophobia by Christian Media, the physical distance between Muslims and locals was far yet the media portrayal led to a high inter-group threat; in the 2015 Isis and the Syrian refugee crisis, the physical distance was far and inter-group threat implied through survey results was low as well; the 2018 Yemeni refugee crisis led to a rapid shortening of the physical distance between Muslims and Korean locals and the media portrayal shows high Inter-group threat; the 2021 Daegu mosque crisis saw a rapidly heightened Inter-group threat while the physical distance between the two groups was always close. Table 1

2008 Islamophobia by Christian Media: Islamophobia first began spreading in South Korea in 2008 led by Christian communities. This is the turning point after which a large, organized, and aggressive Islamophobia came to be (̡Ѱ‫ח‬, 2017). Korean Christian media published anti-Islamic articles that focuses on the threat posed by Islam(‫ܹࣗ؃‬, 2017). In this case, the coverage of threats posed by Muslims by Christian media increased the intergroup threat. Research on immigrants has shown that shocking portrayal of threats posed by immigrants had decreased people’s concern for the human right of immigrants, suggesting that such negative news can affect the intergroup threat (Seate et al., 2016). Not only that, but the anti-Islam gatherings from 2008 to 2017 also likely heightened the intergroup threat (‫ܹࣗ؃‬, 2017). This increased threat contributes to the shortening of perceived distance, leading to increased conflict between groups. In summary, Christian media’s portrayal of Islam increased intergroup threat thereby shortening the perceived distance and giving birth to large-scale Islamophobia. 2015 ISIS and Syrian Refugee Crisis: As for the second case, the rise of the Islamic State(ISIS) and the Syrian refugee crisis is noted. This case is important as it exemplifies a case with a high threat yet far physical distance. Another unique point about this incident is that it did not affect the extent of Islamophobia in South Korea to a large extent at the time. The analysis of news data regarding Islam and Muslims in South Korea from 2015 to 2017 showed that the discussion of Islam was from a thirdperson’s point of view; that is, South Korea was considered to be a bystander that was not greatly affected by the threat of ISIS(ࢇܹࢽ & ফѿࠒ, 2020).

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Furthermore, a study that analyzed people’s perception of the Middle East during this time concluded that people’s perception of the Middle East was neutral to positive while the perception regarding refugees coming into South Korea was not. This shows the importance of physical distance; when the opposition party is placed at a far physical distance, the increase in the threat of theirs does not seem to have as great of an impact on Islamophobia. To understand this using our framework, the fact that perceived distance has its basis in physical distance needs to be emphasized. While factors such as intergroup relationships and inter-group threat do affect perceived distance, physical distance is the primary factor in engendering group conflicts whose proximity functions similarly to a prerequisite. The fact that questions that hypothesized shortened physical distance mostly received negative responses supports this understanding. This case is representative of other Islam-related crises with high threats and far physical distances such as the 9.11 incident or terrorism by immigrants in Europe. These cases also did not largely impact people’s perception of Muslims prior to later crises according to the surveys mentioned previously. 2018 Yemeni Refugee Crisis: In 2018, the Yemeni immigrant influx into South Korea suddenly quadrupled compared to the previous year from 131 to over 552 as the civil war prolonged. Islamophobia spread widely among news media since 2018 after this refugee crisis. Media coverage of Islam and refugees increased significantly in 2018, and so did Islamophobic tendencies (ࢇܹࢽ & ফ ѿࠒ, 2020). In this case, the physical distance was short as the number of Yemeni refugees entering South Korea, especially through Jeju island, skyrocketed in 2018. This influx of immigrants placed the out-group solidly in South Korea, drastically shortening the physical distance between Muslims and locals. This decreases the perceived distance. The media portrayal of the refugee and Islam was widely negative, from which an increase in inter-group threat is expected. An increase in inter-group threat further shortens the perceived distance. Analysis of news reports shows that since this incident South Korea was considered no longer a bystander but an actively engaged party in the relationship between Muslims and other nations by the media (ࢇܹࢽ & ফѿࠒ, 2020); this corroborates the perceived distance between the in-group of South Korean people and the out-group of Muslims shortened after this occasion. The Islamophobia that was prevalent during the time can be understood as the result of this drastically shortened perceived distance. Moreover, other frameworks that have been used to analyze intergroup conflicts also support our hypothesis in this context. The politicized places theory suggests that hostility toward immigrants often rises when a sudden influx of immigrants coincides with salient national rhetoric heightening the threat (Hopkins, 2010). In this incident, the large influx of Muslim immigrants taking refuge was met with the national media’s often negative portrayal of Muslims; thus, the politicized places theory can also explain the rapid increase in hostility toward Muslim immigrants. However, as can be seen in the Daegu mosque crisis analyzed next, the rapid influx of immigrants is sometimes not observed prior to Islamophobic outrage. In this sense, the perceived distance framework can be understood as an extension of the politicized places theory. The rapid influx of immigrants in the politicized places theory corresponds to the shortening of physical distance, while the promotion of threat by salient national rhetoric corresponds to the heightened inter-group threat due to shocking media portrayals. 2021 Daegu Mosque Crisis: Finally, Islamophobia rose to attention again after the Daegu Mosque conflict in 2021. This conflict led to the submission of official pleas to stop the establishment of a Mosque, and even though the Supreme Court ruled that the halting of establishing the Mosque had no legal basis, local residents continued to plead and held gatherings to stop the establishment (࡫࣯ࡕ & ࢇ‫ܕ‬ୱ, 2022). This case is notable since it shows the importance of using perceived distance for analysis. Prior to the establishment of the Darul-eeman Mosque in Daegu, there was an already established long-term trend of increase in Muslim foreign exchange students in the region. They have always used the area whereupon the Mosque was established as a location for religious gatherings;

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however, the Islamophobic backlash was shown on a large scale only after the Mosque almost completed its establishment (࡫࣯ࡕ & ࢇ‫ܕ‬ୱ, 2022). Prior to the establishment of the mosque, the physical distance itself was short while the perceived distance was not because no official religious gatherings or buildings were in place. However, the establishment of the Mosque and its portrayal in the news media rapidly decreased the perceived distance. Since the prerequisite of having a short physical distance was met, people’s recognition of Muslims in proximity as well as the increased inter-group threat by media coverage decreased the perceived distance by a great extent. This is unlike the case of 2015, where the inter-group threat posed by Muslims was greater due to terrorist attacks of ISIS; although the establishment of a mosque is not as violent or harmful in truth, the perceived distance was shortened by a larger extent as the physical distance – the basis for distance judgment – was shorter, to begin with. This shows that the perceived distance is important when analyzing Islamophobia; although the distance between the Muslim population and Koreans did not change before and after the establishment of the Mosque, Islamophobia was heightened after their threat was widely broadcasted. This shows that the theory of perceived distance can better explain some events in the South Korean context where the politicized places theory fails (Hopkins, 2010); even without the sudden influx of immigrants, the preliminary proximity between the two groups was enough to trigger hostility when national rhetoric heightened inter-group threat. Summary: As can be seen, the four turning points of Islamophobia in South Korea can all be explained using the concept of perceived distance. To summarize, perceived distance is affected by two primary factors: physical distance and intergroup threat. While the physical distance becomes the basis for distance judgment, intergroup threat can affect the perceived distance to a lesser degree. In the three cases where Islamophobia was greatly heightened, Korean people’s perception of the distance between self and Muslims was greatly shortened. From these examples, we infer that the increase in Islamophobia is correlated with the decrease in perceived distance.

Conclusion and Discussions In this research, we tried to find the relationship between the perceived distance between Muslims and Korean people and Islamophobia in South Korea. In conclusion, Islamophobia in South Korea seems to be negatively associated with the perceived distance between Muslims and Korean people. The two primary factors that influence perceived distance are physical distance and intergroup threat, and intergroup threat specifically is influenced by media portrayal. Regarding the specificity of the South Korean context, we think the reason why perceived distance better explains Islamophobia in the Daegu Mosque incident than the politicized places theory is partly due to the monoethnic nature of South Korea (Hopkins, 2010). Unlike the U.S. where the study focuses on, South Korea has historically been monoethnic, and thus the presence of people of different ethnicity in close proximity may have had a different effect than on those in the U.S. who are culturally and experientially exposed to greater ethnic diversity. Of course, Islam is a religion that includes devotees of various ethnicities, making it difficult to exactly pinpoint the mechanism or the variables. Further study on hostility toward different groups in the South Korean context or on Islamophobia in other monoethnic nations can be useful for understanding this aspect. As for broader implications, we believe that the results of this research hint at potential preventative measures for Islamophobia. Since past research regarding the judgment of physical distance has found that inter-group interaction also plays a role in distance judgment (Xiao et al., 2016), employing the measures that attenuate the effects of physical distance may help combat Islamophobia. Future policies may focus on factors that affect the perceived distance and manipulate them in a way that would lengthen the perceived distance to reduce tensions between groups. Future studies may focus on exploring other factors affected by intergroup threat, such as size judgment

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or inferences of mental health. Moreover, other sources of Islamophobia in South Korea can be studied for a more holistic view of this topic. Finally, studies for mitigating conflicts rising from a perceived distance are suggested. Previous research has found that means such as barriers or apologies can attenuate the effect of physical distances on the intergroup threat(Xiao et al., 2016); further research on such measures would help combat Islamophobia in South Korea when Muslim residents in South Korea are only expected to increase in the future. As for the limitations of this study, the followings exist. While the concept of distance is used as the chief focus of the study, other factors also affect threat and thus Islamophobia. For example, increased intergroup threat not only has the effect of shrinking the perceived distance but also the effect of exaggerating group size judgment. (Xiao et al., 2016) Other studies also suggest intergroup threat may affect the perception of mental state(Hackel et al., 2014) or skin color(Caruso et al., 2009). Furthermore, perceived distance is unlikely to be the sole cause of Islamophobia in South Korea.

References ̡Ѱ‫(ח‬2017). ೽ࡉչЕ ࠳ ࢇ‫ݞ‬Ԇࡶ ୅ࠝଟ̧?೾, ˁ̛, ۴࡭. Kim, D. (2017). Woorineun wae islameul hyeomohalkka? ̡࡬ܹ and ରѰࣱ(2018). ΢‫ یݪ ׷‬2, 3ʎࡖΰ ցঙ ‘ऑज ΢‫ ߾’׷‬оଞ ࠝଥ ८Я. Ѱ߅ ࢊ‫ؿ‬. https://www.donga.com/news/article/all/20180630/90832058/1 ‫ ׵ࡪ؃‬and ߇ࢽ˲. (2023). ଞ˲୉ ࢇ‫ݞ‬Ԇ૦‫ ߅ٸ‬উѦ(K-IS) ʎ؈. ଞ˲ࣸѰଝୣϢদ, 43(3), 147-182. ‫ܹࣗ؃‬. (2017). ଞ˲‫ی‬ୣࢂ ࢇ‫ݞ‬Ԇ୅ࠝ ୃۘ˕ ࢪࢺ: ۘ୎‫ח‬୘࣯ࢂձ ࣸ‫ࡳݪ‬Ի. ࣗˬ‫ח‬୘ ࠉ˱, (29), 49-70. ࡫࣯ࡕ and ࢇ‫ܕ‬ୱ. (2022). о˱ ٖ˱ ࢇ‫ݞ‬Ԇ‫ ࡕی‬ʀҟࡶ ੼ଥ ‫ܽࢠࡢ ࢂࢂ࣯ࣗࢉ ق‬. ߅ ‫߅ݤ‬չ٫, 12(1), 33-65. ࢇ‫ ࠒܕ‬and ϼծ‫ݝؿ‬. (2014). ଞ˲ ࢇ‫ݞ‬Ԇ̀ ࢇ࣯‫ ࢂ׷‬ʀҟٗ۱ -ࣸ߅߅‫ ؀ ߅ݤ‬Χ߅‫߅ݤ‬ ‫ݞה‬սࡶ ࣸ‫ࡳݪ‬Ի. ࢉ‫˕ח‬ଝࠉ˱Ϣদ, 35(1), 437-471. ࢇܹࢽ. (2018). ଞ˲ ΰ ֻ‫ٗ ਺ݛ‬૦ࠪ ࢇࡈ߾ оଞ ୃଢ଼ ࠉ˱. ଞ˲ࣸѰଝୣϢদ, 39(2), 97-120. ࢇܹࢽ and ফѿࠒ. (2020). ࢇ‫ݞ‬Ԇ˕ ˲ΰ ߯Խࢂ ‫ݤ‬ɽ: 2011-2019ϗࡶ ࣸ‫ࡳݪ‬Ի. ଞ˲ࣸѰ ଝୣϢদ, 41(1), 95-122. ࢠएߦ and ʈ঻˱. (2020). ଞ˲ࢉࢂ о(㠒)ࣸѰ ࢉ‫ ࢶॺࢽ ˕ݥ‬ଡࢂ. ߅‫ࡕ˱ࠉॺࢽۏ‬. Anita Atwell Seate & Dana Mastro (2016) Media's influence on immigration attitudes: An intergroup threat theory approach, Communication Monographs, 83:2, 194-213, DOI: 10.1080/03637751.2015.1068433

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Bleich, E. (2011). What Is Islamophobia and How Much Is There? Theorizing and Measuring an Emerging Comparative Concept. American Behavioral Scientist, 55(12), 1581–1600. https://doi.org/10.1177/0002764211409387 Caruso EM, Mead NL, Balcetis E. Political partisanship influences perception of biracial candidates' skin tone. Proc Natl Acad Sci U S A. 2009;106(48):20168–73. Cole, S., Balcetis, E., & Dunning, D. (2013). Affective Signals of Threat Increase Perceived Proximity. Psychological Science, 24(1), 34–40. https://doi.org/10.1177/0956797612446953 Dinesen, P. T., Schaeffer, M., & Sønderskov, K. M. (2020). Ethnic Diversity and Social Trust: A Narrative and Meta-Analytical Review. Annual Review of Political Science, https://doi.org/10.1146/annurev-polisci-052918-020708 Hackel, L., Looser, C., & Van Bavel, J. (2014). Group membership alters the threshold for mind perception: The role of social identity, collective identification, and intergroup threat. Journal Of Experimental Social Psychology, 52, 15-23. doi: 10.1016/j.jesp.2013.12.001 Hopkins, D. (2010). Politicized Places: Explaining Where and When Immigrants Provoke Local Opposition. American Political Science Review, 104(1), 40-60. doi:10.1017/S0003055409990360 Nelson, T.D. (Ed.). (2009). Handbook of Prejudice, Stereotyping, and Discrimination: 2nd Edition (1st ed.). Psychology Press. https://doi.org/10.4324/9781841697772 3XWQDP 5 ' ( SOXULEXV XQXP 'LYHUVLW\ DQG FRPPXQLW\ LQ WKH WZHQW\ဨILUVW FHQWXU\ WKH Johan Skytte Prize Lecture. Scandinavian political studies, 30(2), 137-174. Xiao YJ, Wohl MJA, Van Bavel JJ (2016) Proximity under Threat: The Role of Physical Distance in Intergroup Relations. PLoS ONE 11(7): e0159792. https://doi.org/10.1371/journal.pone.0159792

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Protection Trade Fosters Domestic Production and Real Gross Domestic Product Author 1

Full Name

Lee, Heejoon

Korean Minjok Leadership Academy

(Last Name, First Name)

School Name

ABSTRACT The COVID-19 pandemic has caused the rise of protectionism with trade barriers worldwide, and the conflict between the US and China exploded with mutual restrictions to international trade. Even though free trade enables lower prices for consumers and increases exports, protective trade developing from putting one's own country’s interests first has several advantages. I described the rationale of protection trade with the tariffs based on the multiplier effects and the change of the domestic supply and demand. As evidence, I compared the multiplier effects between the Obama government of free trade and the Trump government of protection trade by calculating the marginal propensity to save (MPS), and marginal propensity to consume (MPC) from announced data of U.S. Bureau of Economic analysis. The calculated marginal propensity to consume (MPC) in the Trump government was 0.66~0.87, compared with 0.57~0.84 in the Obama government. The increased amount of Real Gross Domestic Product GDP (RGDP) in the Trump government on protectionism trade was 396.4-1100.7 billion dollars, higher than those in the Obama government showing 242.5-458.2 billion dollars. Therefore, if the governmental revenue from tariffs is invested willingly, then this can contribute to the increase of the RGDP in protection trade despite a global pandemic.

KEYWORDS: Protection trade; Trade barriers; Multiplier effects; Marginal propensity to save; Marginal propensity to consume

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INTRODUCTION Human history is a cycle of conflict and war. In the past, humans fought with guns and swords to occupy territory, but now we are fighting an invisible economic war. Leaving behind the tension between the United States and the Soviet Union, US vice president Pence declared a new cold war in October 2018 against the China trade (1). However, human beings are trying to survive through this era with the treaty and alliance. In spite of the establishment of the European Union (EU) and the Asian-Pacific Economic Cooperation (APEC) in 1993, China has become the second-ranked world economic power since 2001 after joining the World Trade Organization (WTO). US former president Donald Trump set the barrier of protectionism, imposing tariffs on foreign steel and aluminium in March 2018 (2), in order to occupy a better position in trading with other countries. Other than this, Trump quit the job-killing Trans-Pacific Partnership, abandoned the North American Free Trade Agreement, and substituted it with the fresh United States-Mexico-Canada Agreement (USMCA) in order to defend American workers. Powerful protections are provided by the USMCA for American manufacturers, car assemblers, farmers, and labourers. USMCA is also anticipated to bring about over $68 billion in fiscal enterprises and generate more than 550,000 new jobs in ten years (3). Critics quarrelled that this policy would eventually hurt domestic producers, consumers, workers, and the economy. Primary concern is that setting of the tariff would fall most heavily on allies, mainly Canada, which supplies steel and aluminium to both US companies and the military. In response to the tariff, the stocks fell. The industrial sector of Standard & Poor's 500 saw a decline of 1.9 percent, compared to the overall benchmark index which experienced a decrease of about 1.3 percent. Shares of American automakers, significant consumers of metals, as well as shares of Boeing, a major exporter vulnerable to potential retaliation from other nations due to United States tariffs, also experienced declines (2). Free trade essentially enables lower prices for consumers and increases exports, with various goods that can be chosen. David Ricardo, in his book, said that each country can assign its capitals and labours to proper employment in a system of perfectly free trade, and the advantage is good for all (4). However, protective trade developing from putting one's own country’s interests first has several advantages. Countries impose taxes and quotas and regulate imported goods with many other measures. It serves to safeguard domestic companies against unfair competition, boosts demand for local products, fosters job growth within the country, betters trade deficits, bolsters the competitiveness of trading partners, generates revenue, and imposes penalties on nations with unethical trade policies (5). Apart from the classic tariffs, non-tariff barriers act as a barrier to international trade, which involves import licensing, rules for the valuation, pre-shipment inspection, rules of origin, and investment measures. These kinds of actions prioritise domestic producers and maintain balance of trade (6). In addition, carbon border tariff responding to climate change (7) and barriers to digital technology trade (8) are new barriers arising in commerce that have significant effect for trade partners. Recently, the COVID-19 pandemic has complicated the international economy, causing the rise of protectionism with trade barriers worldwide (9), which seems to be less efficient. During the pandemic, the western world including USA relucted the China from where the COVID19 originate, and the conflict between the USA and the China exploded with mutual restrictions to international trade, after initial offensive violation, represented by intellectual property infringement of the China (10). Protectionism policy of the US government has somewhat been expected, provided with evidence and reasonable basis.

METHOD I read the textbook, Principles of Economics 8th edition by N. Gregory Mankiw. And then I searched and read the relevant articles in Jstor (https://www.jstor.org/). Furthermore, I tried to find relevant materials in published books listed in references.

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I described the rationale of protectionism trade with the tariffs, using the graphs and equations below, to demonstrate the contribution of protectionism trade by Donald Trump during his time (2017~2021), in contrast to ordinary free trade represented by the US. For the schematic presentation of figures, I used the Microsoft powerpoint (2016 version). For further calculation and estimation including the multiplier effect, I used the Microsoft Excel program (2016 version), based on the announced data from U.S Bureau of Economic analysis. I compared the multiplier effects between the Obama government of free trade and the Trump government of protection trade by calculating the marginal propensity to save (MPS), and marginal propensity to consume (MPC).

RESULTS Marginal Propensity to Consume and Marginal Propensity to Save Regular market consists of increasing supply and decreasing demand as the price rises, defined by the law of demand and the law of supply. Rational consumers demand less for the good as price increases, and rational producers increase supply as the price rises (11), as shown in figure 1. British Economist John Maynard Keynes came up with the idea of Marginal Propensity to Save and Marginal Propensity to Consume, which is used when considering consumer behaviour of spending or saving, having a big impact on the economy (12). MPC (Marginal Propensity to Consume) can measure additional increase in consumer spending when disposable income rises by $1, while MPS (Marginal Propensity to Save) measures additional increase in household savings when disposable income rises by $1. With the use of MPC and MPS, it is possible to drive the spending multiplier as the impact of government spending. When the government purchases goods from domestic firms, the primary effect of increased demand is a rise in the firm's employment and profits. This, in turn, leads to higher earnings for workers and increased profits for company owners. With this added income, both workers and company owners tend to spend more on consumer goods. Consequently, the higher demand generated by government purchases has a ripple effect, boosting demand for products from numerous other companies across the economy.

Figure 1: The schematic graph representing the multiplier effect of the government spending (13) (modified by Heejoon Lee)

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Real Gross Domestic Product and Multiplier effect The original Aggregate demand increases to Aggregate Demand as the immediate effect of the government purchase. The Aggregate Demand shows the multiplier effect on aggregate demand, resulting to have increase in Real Gross Domestic Product (RGDP) more than government’s spending. RGDP applies constant base-year prices to put values on the economy’s production of goods and services, which means RGDP is adjusted for price change. Because Real GDP is not affected by changes in prices, changes in RGDP casts only changes in the amount being produced. Thus, RGDP can measure an economy's production of goods and services.

Figure 2. The graph showing domestic market after imposing per-unit tax (14). Imposing tariff for imported goods is one of the strategies to move a market closer to the equilibrium point that would exist without trade. Before imposing tariffs, consumer surplus is A+B+C+D+F and producer surplus is G, as shown in figure 2. So, the total surplus before per-unit tax turns out to be A+B+C+D+E+F+G. After imposing tariff, consumer surplus is A+B and producer surplus is C+G. And since the government takes the revenue from the tariff they impose, government revenue is E. The total surplus after per-unit tax turns out to be A+B+C+E+G. Deadweight loss is D+F, which is a change in total surplus before and after imposing a per-unit tariff. The existence of deadweight loss usually convinces the public that imposing a per-unit tariff has a negative impact in terms of loss in economic efficiency, but the revenue the government gets can make up the loss, or even benefit the country. If the government fully uses the revenue acquired from the tariff into its spending, the multiplier effect comes into play. This is because each dollar spent by the government can stimulate aggregate demand for goods and services by more than just one dollar. As a result, government purchases can exert a multiplier impact on aggregate demand. The spending multiplier is equal to 1/(1-Marginal Propensity to Consume). The product of the change in government spending and the Spending multiplier is equal

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to the change in RGDP. ǻ *RYHUQPHQW 6SHQGLQJ [ -03& ǻ 5HDO *'3 Here, I would like to show that raising tariffs accelerate RGDP growth of a country, with the specific example of the US government.

Calculation and Comparison of real gross domestic product, marginal propensity, and tariffs in U.S government Cost unit; Billion dollars

MPS=Marginal Propensity to Save, MPC=Marginal Propensity to Consume Table1. Calculation from real gross domestic product (15), marginal propensity (16), and tariffs (17).

The assumption here is that the government fully uses the revenue from imposing tariffs to purchase the goods from the domestic producers, and only aggregate demand affects change in RGDP. By calculating the multiplier effect in both the Obama government and Trump government, using Microsoft Excel program, real announced data from the Bureau of Economic analysis was used for further calculation and estimation (15-17). As shown in above table 1, the increased amount of Real *'3 ǻ5*'3 in the Trump government on protectionism trade was relatively higher than those in the Obama government. The calculated marginal propensity to consume (MPC) in the Trump government was 0.66~0.87, compared with 0.57~0.84 in the Obama government. The supposed tariffs, taxes on production and imports, were 1367.4~1530.0 billion dollars in the Trump government, which were relatively higher than 1026.8~1311.6 billion dollars in the Obama government. As seen in above table 1, in 2020, change in RGDP was a negative number, due to the COVID-19 pandemic. But with the effective trade barrier, ǻRGDP doubled compared to 2019 ǻRGDP, which adjusted the loss from the year 2020.

DISCUSSION Based on the real gross domestic product and multiplier effect, protection trade driven by the Trump government in the U.S.A seems to have contributed to the economic growth of the U.S.A amid COVID19 pandemic. However, benefit and risk must be weighed carefully in these harsh international circumstances after the post COVID-19 era.

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The data, from what I’ve calculated in table 1, shows that the effect of having significant trade barrier increased the RGDP. Increase in RGDP indicates that country’s economic production of goods and services has expanded. In addition, Dow Jone index, which is the stock market index of 30 prominent companies in the United States, rised steeply in Trump government, and the unemployment rate has steadily declined from the 10% level in Obama government to 3.7% in Trump government (18). Therefore, if the governmental revenue from tariffs is invested willingly, then this portion would contribute more WR WKH LQFUHDVH RI WKH ǻ5*'3 LQ SURWHFWLRQLVP WUDGH In the data, MPC and MPS could not be calculated in 2021, because the impact of COVID-19 was too enormous for proper calculation. In addition, the measured MPC and MPS values could vary by the method of collecting data, in this case, credit card expenditures. Moreover, some people who can’t afford to save or use credit or who invested their assets in real estate may have liquidity constraints. These households can present a higher marginal propensity to consume than unrestricted people (12). Therefore, multiple circumstances must be considered in the further research. Considering the decoupling and hegemony dispute between the US and China, South Korea must set the strategic interest responding to both the core interest of China and the US, creating a path to break free from the identity of the shadow country (10). Reshoring of domestic companies could be considered to hold the long-term competitiveness and to save the cost. Full dependency to both countries should be avoided, and a new global supply chain must be sought (10). Additionally, information communication technology (ICT) standard competitiveness should be preoccupied, because China is trying to overtake South Korea in the field of digital technology. However, my research have several limitations. Firstly, I could not find more available updated data from U.S. Bureau of Economic analysis. Therefore, I could not compare the results of recent Joe Biden government with the Obama and Trump government. Secondly, free trade theory has been mainstream in international trade, but more relevant data from free trade from other countries including South Korea could not be suggested. Lastly, COVID-19 pandemic resulted in never-experienced massive impact on the world economy, therefore this special situation could not be generalised to usual ordinary circumstances.

CONCLUSION In this new-normal stage with COVID-19, new orders of changes would be settled amid uncertainty of international trade, like the occurrence of industrial revolution with the revitalization of international trade after the end of mid-centuries' black death caused by infectious disease, the plague in England (19). The tension between the free trade and protectionism trade will contribute to the emergency of a more valuable 4th revolution stage. To summarise, the governments impose trade barriers such as tariffs and quotas in order to stimulate the country’s economy, work as a catalyst for the RGDP growth, and promote the country’s production of goods and services. It is for the superior growth of the nation as well as domestic producers, firms, and manufacturers. The intervention of the government benefits the country as a whole, improving final goods and services, capital goods, and inventories. In a catastrophic event such as a global pandemic, from which I observed, having trade barriers is effective for the country, having the potential to increase RGDP.

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From Stigma to Inclusion: Rethinking Special Education for Learning Disorders in South Korea Author 1

Full Name

Lee, Yoona

St. Paul's School

(Last Name, First Name)

School Name

ABSTRACT: This research paper explores the impact of stereotypes on the advancement of special education for learning disorders in South Korea, examining barriers created by these biases and suggesting policy recommendations for fostering inclusivity within the education system. Learning disabilities, often referred to as specific learning disabilities (SLD), encompass various neurodevelopmental disorders affecting the acquisition and application of information. Despite advancements, challenges persist in achieving equal opportunities and inclusivity for individuals with learning disorders due to societal misconceptions. Stereotypes and limited public awareness contribute to stigma and discrimination, influencing attitudes among educators and students. This paper presents a comprehensive analysis of learning disorder definitions, South Korea's special education system, and the consequences of stereotypes on special education progress. To counter these issues, the paper advocates for education and awareness campaigns, system reforms promoting inclusivity, comprehensive teacher training, and collaborative efforts among stakeholders. By acknowledging the impact of stereotypes and implementing targeted measures, South Korea can pave the way for a more inclusive educational landscape that values diversity and empowers all students.

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Defining Learning Disorders The criteria for defining and identifying learning disorders for diagnosis can be found in the the two most internationally recognized classification systems of mental disorders: the International Classification of Diseases and Related Health Problems (ICD), from the World Health Organization (WHO), and the Diagnostic and Statistical Manual of Mental Disorders (DSM), from the American Psychiatric Association (APA). According to these systems, learning disorders, often referred to as specific learning disabilities (SLD), are a heterogeneous group of neurodevelopmental disorders that impact an individual’s ability to acquire, organize, retain, understand, or apply verbal or nonverbal information. These disorders can manifest in difficulties related to reading, writing, mathematics, attention, memory, language processing, and other cognitive functions. Dyslexia, for instance, is a type of learning disability where people face difficulty recognizing, decoding, and spelling words. Individuals often face difficulty in phonemic and phonological awareness, making it difficult for them to make sense of the sound structure of a certain word (Stanley & Petscher, 2017). Learning disorders are not indicative of intellectual deficiencies; rather, they reflect inherent neurological differences that can significantly hinder a person's academic progress despite average or above-average intellectual capacities. More importantly, learning disabilities (LD) can be differentiated from other disabilities as difficulties in acquiring skills that remain unaccounted for by intellectual, neurological or motor disorders, sensory impairment, lack of availability of education, or by psychosocial adversity (Pérez, 2020). The definition of LD was officially integrated into South Korean special education law in 1994 in the Special Education Promotion Act (SEPA), permitting identified LD students to access specialized education services. Initially, LD denoted students facing specific learning challenges in areas like counting, speaking, reading, or writing and those facing learning difficulties due to individual, familial, or environmental factors, sparking ongoing debates about its definition (Choi et al., 2017; A. Kim et al., 2018). The concept of learning disabilities (LD) in South Korea has evolved since then, most notably with the introduction of the Special Education Act for Individuals with Disabilities and Others (SEAIDO) in 2008. This move led to a broader definition, encompassing significant difficulties in learning abilities and academic achievement due to intrinsic factors. This legal shift, however, has faced criticism for its ambiguity and inconsistency in educational policies (A. Kim et al., 2018). The term “intrinsic” itself seems vague and in fact, several educators have criticized this law, claiming it is still unclear and that in terms of educational policy and schools, several related terms are inconsistently used (Shin & Choi, 2022). A recent trend that can be attributed to the impact of the unclear definitions and identifying criteria for LD is that the prevalence rate of students with LD in South Korea has been declining. According to statistics conducted by the Ministry of Education, the prevalence rate of LD has been declining from 8.7% in 2009 to an alarming 1.5% in 2019. Based on the same study, students with LD represent only 0.02% of the total school-age population. In contrast, in the United States, “...the percentage of children served by federally mandated special education programs, out of total public school enrollment, increased from 8.3 percent to 13.8 percent between 1976-77 and 2004-05. Much of this overall increase can be attributed to a rise in the percentage of students identified as having SLD from 1976-77 (1.8%) to 2004-05 (5.7%)” (Grigorenko et al., 2020). The assumption for this declining prevalence of LD in South Korea is that students with LD are severely underrepresented (Choi & Shin, 2022). Meanwhile, teachers express that they continue to encounter at-risk students and it is reported that 1-5% of schoolage children struggling with reading are at risk of having a LD (Choi & Shin, 2022). The absence of a well-defined definition of learning disabilities in South Korea has impeded progress in the country's special education system. This lack of clarity has led to inconsistent identification and support for students with learning disabilities, resulting in misdiagnosis or underdiagnosis and hindering crucial early interventions (Kang & Shin, 2022). Educator training, without a consistent definition, likewise suffers in being able to adequately identify and support students with LD. Moreover, the absence of a standardized definition contributes to stigma, public misunderstanding, and challenges in promoting inclusive education efforts. Research, advocacy, legal frameworks, and the overall

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advancement of services for individuals with learning disabilities are compromised by this lack of clarity, highlighting the need for a unified understanding of these conditions to drive positive change in South Korea’s education landscape.

Special Education System in South Korea South Korea’s special education structure includes special schools and classrooms dedicated to catering to the needs of students with disabilities. The process of identifying and assessing learning disorders involves multiple steps, such as requesting diagnosis or evaluation tests from district heads or superintendents. Educational support teams prepare individualized education plans, and students are placed in general or special classes based on recommendations (Choi et al., 2017). Despite these provisions, challenges persist in ensuring access to special education services, and the training of educators in handling learning disorders remains a crucial concern. Inclusive education initiatives have seen progress, with an increasing number of students with disabilities attending general schools (Kwon, 2015). Over the course of its development, the landscape of special education legislation and policies in South Korea has undergone transformative shifts that have deeply influenced the provision of education for students with disabilities. The early years, spanning the 1940s to the 1960s, witnessed the establishment of segregated special schools catering to specific disabilities, such as Bo-Myoung School for students with intellectual disabilities and Young-Hwa School for the deaf and hard of hearing (Kang & Shin, 2022). While special education was mentioned within general education laws, the absence of dedicated regulations for special education hindered the integration of disabled students into mainstream schools (Chae et al., 2018). The subsequent advent of the Special Education Promotion Act (SEPA) in 1977 marked a significant turning point by introducing essential legal provisions that guaranteed the educational rights of students with disabilities. This act also paved the way for the introduction of individualized education programs (IEPs) and the evaluation of students at risk for disabilities. With its reauthorizations, SEPA began emphasizing terms like “integration” and “least restrictive environment,” leading to an increase in the enrollment of mild to moderate disabilities students in public schools (Chae et al., 2018). However, critiques emerged, with experts highlighting the SEPA's focus on elementary and secondary schools at the expense of early childhood and postsecondary support, and the lack of clearly defined roles for governmental bodies to create inclusive educational environments (Jung, 2007). A pivotal shift came in 2008 with the introduction of the Act on Special Education for Persons with Disabilities (ASEPD), which brought about a series of significant changes. ASEPD expanded the scope of free public special education to encompass early childhood and college students with disabilities, a move unparalleled by many other nations. This expansion led to a substantial increase in students receiving special services, reaching 98,154 in 2021 (South Korea - Act on Special Education for Persons with Disabilities - Disability Rights Education & Defense Fund, 2022). The act also mandated the establishment and operation of Special Education Support Centers (SESCs), tasked with screening, diagnosing, and offering itinerant and specialized education services, along with training for special education teachers. ASEPD underscored inclusive educational settings to support the transition of disabled students to postsecondary life and societal inclusion. In 2013, further strides were made with the enactment of provisions mandating human rights-based professional development for general and special education teachers. Notably, the ongoing implementation of five-year special education development plans, driven by the Ministry of Education, have played a pivotal role in shaping the direction of special education and teacher preparation. These plans have targeted expanding the range of recipients of special education services, enhancing the quality of inclusive educational environments, and advocating for the human rights of students with disabilities (Kim et al., 2017). In light of these trends, it is evident that while South Korea has made significant strides in identifying and accommodating students with LD, certain challenges persist. The identification criteria for LD, as established by the Ministry of Education, Science, and Technology (MOEST) and the Korean Learning Disabilities Association (KLDA), have sparked an ongoing debate (Kang & Shin, 2022). Moreover, the

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absence of robust support systems has led to complexities in implementing preventive approaches to identify at-risk students before they fall significantly behind their peers. This challenge is further exacerbated by the absence of a comprehensive schoolwide support system, causing uncertainty among general education teachers regarding when to refer students struggling with LD for a comprehensive evaluation (Kang & Shin, 2022). In addition, SESCs, charged with assessing individuals with disabilities, have encountered difficulties in establishing clear guidelines for both identifying at-risk students and distinguishing between varying degrees of learning challenges within the LD spectrum (Kang & Shin, 2022). As South Korea continues to navigate these complexities, it becomes increasingly crucial to address these challenges and refine the identification and support systems for students with learning disabilities. In South Korea, achieving successful inclusion of students with disabilities in education faces challenges, particularly in improving general education teachers’ understanding of and readiness for inclusion. While progress has been made in increasing the number of students with disabilities attending general schools, there remains a significant gap in educators' knowledge and attitudes (Kang & Shin, 2022). General education teachers often prioritize high-achieving students, resulting in delayed referral processes for at-risk students and negative perceptions of those with disabilities (Kang & Shin, 2022). Overcoming these obstacles requires a concerted effort to enhance teacher training and preparation. Recent policies have aimed to address this by offering more training for in-service general education teachers and promoting co-teaching models involving special and general education teachers (Kim & Kim, 2015). However, preservice general education teachers continue to express concerns about their ability to effectively handle students with disabilities (Lee et al., 2018). As a result, continuous discussions about improving the education and support provided to preservice teachers are crucial to ensuring they possess the necessary skills and knowledge to create truly inclusive classrooms (Kang & Shin, 2022). Significant barriers to creating inclusive and integrated environments for students with LD is not only South Korea’s unique educational environment that prioritizes high-achieving students but also the stereotypes and lack of awareness among the general population.

Stereotypes and Misconceptions about Learning Disorders in Korean Society Stereotypes and misconceptions regarding learning disorders are prevalent in Korean society, contributing to stigma and discrimination faced by individuals with these conditions. Lack of awareness and understanding among the public, including educators and students, further compounds the issue. Research has shown that students lack proper understanding of learning disabilities, with surveys indicating limited familiarity with the term “learning disabilities” and negative perceptions towards peers with these conditions. For instance, according to a survey conducted in 2014 on 460 college students, respondents revealed a desire to socially distance themselves from peers with LD and held negative views on inclusive education (Choi et al., 2014). Media representation and cultural beliefs also shape attitudes towards learning disorders, often perpetuating negative biases as students mostly gain information on disabilities through the media. For instance, according to A National Survey conducted on South Korean High School Students’ Understanding of Learning Disabilities, 47.8% among 343 students stated that they acquired information on people with disabilities through the media such as the television or the internet (Lee & Shin, 2018). Upon examining what might have influenced the attitudes of the respondents regarding students with LD, it can be deduced that many stereotypes and negative perceptions of students with learning disabilities are acquired from the media (Lee & Shin, 2018). Furthermore, stereotypes play a role in the decline of the prevalence rate of students identified with LD in South Korea. There is ongoing debate on whether the low percentage of students identified with LD represents the actual population of students with LD or if students who really have LD are not getting the accommodations necessary (Shin & Choi, 2021). However, despite efforts to improve public awareness of learning disabilities, disabilities continue to be viewed negatively in South Korea. In a

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survey and social media analysis conducted in 2016, more than 60% of the respondents stated that there still existed widespread discrimination towards people with disabilities (Lee, 2016). Furthermore, many parents of children with disabilities stated that their children encountered violence in school and discrimination with educational opportunities (K. Kim & Kim, 2015). Thus, with the negative perceptions propelling discrimination within educational settings, it would not be surprising if parents chose to hide their children’s disability. From a nationwide perspective, South Korea faces a significantly low number of students identified with LD. This can be a result of the negative stereotypes and stigma present in Korean society. In the US during the 2021-2022 school year, 15% percent of American students received support under the IDEA (Individual with Disabilities Education Act) (National Center for Education Statistics, 2023). The IDEA, mandated in 1975, was created to enhance the educational performances of students with disabilities. The act not only provides assistance and services to students in public schools but the act also makes it obligatory for school districts to make services and accommodations accessible to students with disabilities who attend private schools (U.S. Department of Education, 2017). Out of the students receiving accommodations under the IDEA, the greatest reported percentage accounted for 32% for specific learning disabilities (National Center for Education Statistics, 2023). Compared to South Korea, services towards students with learning disabilities is more prevalent in the US, arguably due to less stigma associated with advocating for LD rights for students. This data further reveals how more parents and students are unashamedly seeking out the assistance needed for their learning disability in the US. In South Korea, however, such progress is yet to be made on LD advocacy starting from the home, as many families and students are still facing stigma around disabilities, leading to many parents hiding their child’s disability (Jung, 2007). This might be particularly true for South Korea’s unique social situation, as acknowledging any disability is seen more as a source of shame than an opportunity for targeted support and intervention.

Raising Public Awareness about Disabilities Creating a truly inclusive society depends largely on positive social acceptance. Yet, South Korea, like other nations, grapples with misconceptions and stigmas surrounding individuals with disabilities. Some parents, aware of unfair educational opportunities for their disabled children, resign to the situation due to perceived helplessness (Kim & Kim, 2015; Kwon, 2015). This points to a glaring lack of public awareness and understanding of disabilities (Shin & Choi, 2022). Addressing these concerns, policymakers and practitioners propose solutions. Aligned with global efforts to foster public awareness and acceptance (UN, 2006), South Korea emphasizes human rights, propelling initiatives like the 2022 Special Education Operation Plan and the Fifth Five-Year Development Plan for Persons with Disabilities (MOE, 2018, 2022). Central to these efforts is promoting disability awareness—educating to foster accurate perceptions and improved attitudes toward individuals with disabilities. The aim is to regard them as equal citizens entitled to their human rights (Disabled World, 2016; Leicester, 2008). School-based interventions are pivotal in enhancing disability awareness for nondisabled students. Various programs have been implemented, incorporating materials, role-playing, peer interaction, and human rights lessons (Lee, 2013; Kang et al., 2007; Jeong & Chu, 2016). Such efforts have led to a surge in peer-reviewed journal articles on disability awareness spanning from kindergarten to high school (Chae et al., 2018). The Ministry of Education (MOE) further extends awareness initiatives, mandating disability awareness classes twice a year for K-12 students without disabilities, and an annual participation requirement for government employees (ED-WAD, 2015). Multi-media campaigns employing e-books, websites, videos, and social networks are being leveraged to augment comprehension of individual strengths and weaknesses, disability-inclusive. However, altering perceptions demands sustained partnership and

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collaboration among agencies, a challenge for the forthcoming five-year plan. Despite legislative steps to shift perceptions and attitudes, the stigma attached to disabilities persists in South Korea. A survey by K. Lee (2016) and social media analysis revealed over 60% of respondents acknowledging ongoing discrimination against individuals with disabilities. Parents of disabled children highlighted experiences of school violence and educational discrimination (K. Kim & Kim, 2015). This negativity leads parents to conceal their children’s disabilities, unless comprehensive services for students with LD are provided. Notably, high school and college students display a limited understanding of LD, often unaware of its subcategories like dyslexia (Cho et al., 2014). Teachers also exhibit unfavorable perceptions toward students with LD, grappling with evaluation and teaching challenges (Byon & Park, 2013). With these persistently inadequate perceptions and negative attitudes toward LD, the declining recognition of LD will continue its course in South Korea, with unforeseeable consequences for those with LD who are slipping through the cracks.

Impact of Stereotypes on Special Education Progress Stereotypes present significant barriers to the progress of special education for learning disorders in South Korea. These biases hinder early detection and intervention, limiting access to essential resources and support for students with learning disorders. The psychological effects of societal prejudice can negatively impact students’ self-esteem and overall well-being. As mentioned earlier, educators’ attitudes and preparedness in dealing with learning disorders are also affected by stereotypes, as they prioritize high-performing students, potentially hindering effective inclusion efforts. Additionally, parental involvement and advocacy face challenges due to societal perceptions, sometimes leading to parents accepting unequal educational opportunities. In 2017, after years of protesting from parents on the need for more special education schools, the Seoul Metropolitan Office of Education (SMOE) promised to open three more schools in Seoul. However, the plan was met with opposition from parents who were fearful that opening special education schools would negatively affect the image of their neighborhood and the real estate prices (You, 2017). With the societal stereotypes on disabilities present in Korean society, efforts to accommodate the needs of students with disabilities are greatly hindered. Beyond the lack of awareness individuals have on learning disabilities, societal stereotypes continue to pose challenges in creating a more welcoming and inclusive environment for students with LD. According to A National Survey conducted in 2018 on South Korean high school students, results revealed that familiarity with terms related to learning disabilities did not result in significant differences in beliefs and attitudes towards students with learning disabilities (Lee & Shin, 2018). The fact that some students already had preexisting knowledge on learning disabilities and yet their attitudes to students with learning disabilities did not change reveal that there is a greater factor such as societal stereotypes that impact how students with disabilities are treated.

Recommendations To combat the impact of stereotypes on special education progress, a multi-faceted approach is essential. Education and awareness campaigns should be initiated to dispel misconceptions and promote understanding of learning disorders. Reforms within the special education system, focusing on inclusivity and equal opportunities, are necessary to create a conducive learning environment for students with disabilities. Comprehensive teacher training and professional development programs should address stereotypes and equip educators with the necessary skills to handle diverse learning needs effectively. Collaboration between educational institutions, parents, and society at large will play a pivotal role in dismantling stereotypes and fostering a more inclusive educational landscape. Drawing

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inspiration from successful special education models in other countries can offer valuable insights into best practices. The advancement of special education in South Korea has been significantly influenced by laws and policies, allowing more students with disabilities access to free public special education and educational content. However, several challenges remain unresolved, including policies that delineate clear definitions and identification procedures, inclusion advocacy, public awareness of learning disabilities, and the preparedness of special education teachers and curricula. Concerns regarding instructional approaches and service delivery within inclusive education have persisted since the 1990s. Addressing these matters is crucial for rendering special education more inclusive and preparing proficient teachers to enhance the learning experiences of disabled students. To fulfill the core objective of social inclusion for individuals with disabilities, a primary aspiration in South Korean special education, heightened efforts are necessary to enhance public awareness and advocate for their human rights (MOE, 2018). Additionally, both pre-service and in-service teachers require opportunities to collaborate across special and general education curricula for meaningful engagement in both physical and virtual learning environments. Recognizing the far-reaching impact of special education laws and policies on the overall trajectory of special education in the country, it is pivotal to establish systematic policies and corresponding initiatives to surmount these challenges. The collective efforts of policymakers, stakeholders, and practitioners are essential for creating and implementing policies that foster genuine interactions among families and students, regardless of disabilities. This collaborative approach can fortify the journey towards an inclusive educational landscape.

Conclusion The journey towards achieving inclusive and equitable education for individuals with learning disorders in South Korea is marked by progress, yet overshadowed by persistent stigmas. By understanding the impact of these biases and undertaking targeted efforts to combat them, the nation can move closer to ensuring that all students, regardless of their learning abilities, receive the education they deserve. The integration of policy recommendations, informed by empirical research and global best practices, will be crucial in shaping a more inclusive future for special education in South Korea. Addressing stereotypes is not only a necessity but a commitment to creating a society that values diversity and champions the potential of every individual. This research paper offers valuable insights into the impact of stereotypes on special education for learning disorders in South Korea. However, several limitations should be acknowledged. The reliance on surveys, academic analysis, and quantitative data may not fully encompass diverse perspectives and could introduce bias. Furthermore, since LD is still a relatively nascent development in the scope of special education in South Korea, the research available for review may not capture the full extent of recent developments, potentially limiting the relevance of the findings. In addition, ethical considerations related to data collection and privacy have not been extensively discussed. Finally, the representation of survey samples and the long-term implications of policy recommendations could be further addressed. Despite these limitations, the study provides a foundation for understanding the complex interplay between stereotypes, learning disorders, and special education in South Korea.

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Impact of White Noise on Cognitive Performance: A systematic review Author 1

Full Name

Oh, Phoebe

Seoul Foreign School

(Last Name, First Name)

School Name

ABSTRACT: Use of white noise to improve sleep and concentration has been demonstrated and practically applied in many settings. However, limited studies have examined the impact of white noise on cognitive performance. This study conducted a systematic review of published studies that evaluated the effect of white noise on cognitive tests and summarized the findings. In total, 11 relevant studies, which matched the inclusion criteria, were identified. These studies were conducted among both adults and children. Furthermore, the definition of white noise varied significantly among the studies. In addition, the included populations also varied; some studies examined healthy individuals, while others examined individuals with cognitive disorders. The studies also used diverse testing methods. Overall, white noise had a positive impact on cognitive performance, except for in a few studies. The impact of white noise was influenced by the study population and showed more consistently beneficial results in populations with cognitive impairments. Evidence for the use of white noise as an educational aid is compelling; however, additional studies using standardized approaches to allow comparability between populations are necessary.

KEYWORDS: white noise; memory; cognitive performance; ADHD

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BACKGROUND: The human brain comprises of a complex network of neurons that allows for infinite possible neural pathways and connections when functioning properly. The pathways coded within these networks relay information from sensory centers to nodes for interpretation and feedback. Some pathways are automatic and function unconsciously, such as the signals that control heart rate or hormone levels. Meanwhile, others require effortful processing, such as solving a math equation or reading directions on a map. Other tasks or stimuli also require significant processing power at first; however, they become easier over time as they are learned. Learning is the ability of higher-order organisms to process and apply new information more efficiently and effectively. Even lower-order organisms, such as single-celled microbes, insects, and fungi, have the capacity to learn, react, and adapt to their surrounding environment. The importance of memory in the acquisition of new skills and learning new concepts has been well established (1). Memories are formed when new connections are made between the neurons and reinforced through repeated signals between the synapses, spaces between neurons that allow for chemical signals to pass (2). The environment in which these connections are made could influence the speed and quality of forming working memories. Memories are often strongly linked to smell since the olfactory lobe, the part of the brain that processes smells, is closely linked to the hippocampus, the part of the brain that stores memories (3). Certain environments are more conducive to forming high-quality and lasting memories, particularly regarding learning and skill development. Ensuring that the key signals are clear and not drowned out by background “noise” is important in training the brain to prioritize and retain key information. Conditions that promote learning are a topic of interest in modern society, especially for school-aged children, who experience a period of rapid cognitive development. Educational experts, academics, politicians, teachers, and parents aim to provide an optimal learning environment for the children, students, and constituents. Strategies to enhance learning include reduction of class sizes (4), use of multimedia (5), modification of nutrition (6), and reformation of examination methods (7). The complexity of education systems and parenting has demonstrated that every student is unique. Hence, no single learning strategy can be truly effective for the entire population. Therefore, a customized, iterative, and adaptive approach must be used. However, memory, an important component of learning, is more direct and simpler to understand. Memory can be classified into two broad categories: short- and long-term memory (8). Short-term memory is a class of information stored for short periods of time, typically for as long as an ongoing relevant task. For example, an individual probably retains a locker number at a gym until they successfully retrieve their clothes and leave the changing room. Conversely, long-term memories are more durable and permanent, although modifiable, depending on whether new relevant information is obtained. One example is an individual recalling the moment that they received their university acceptance letter. Different types of memories are stored and processed in different parts of the brain. However, their underlying neurophysiology and biological mechanisms were out of the scope of this review. We primarily rely on short-term memory for learning. Neural connections between sensory receptors and their processing stations can be strengthened through frequent use or reinforcement. The key is to determine other external or internal factors that improve or impede memory formation, and thereby, learning. Researchers have explored numerous hypotheses to optimize learning pathways. A team from the Korean Advanced Institute of Science and Technology (KAIST) investigated the impact of lighting on academic performance and found that psychological alertness was highest when exposed to cool white lighting (6500 Kelvins)(9). Another study found that 22 degrees Celsius was the optimal temperature for academic performance (10). Ever-growing number of nutritional supplements and superfoods have been purported to stimulate brain health and cognition. Yet, their claims are supported by weak scientific evidence and limited, poorly conducted clinical trials. Sleep and exercise have also

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been closely linked to healthy brain function; however, it is difficult to quantify the impact of these factors on cognitive function (11,12). Recently, sound environment, soundscape, has gained attention related to aspects of health and cognition. Use of sound machines and audio tracks to enhance sleep quality have become popular and are widely promoted. The first practical application of a “white noise” machine was by James K. Buckwalter in 1963. He was inspired by his wife who had trouble sleeping; however, she found the sound of an air conditioner helpful (13). He developed a machine that replicated the sound of an air conditioner and did not produce cold air, and filed a patent for it, the SleepMate. The mechanical sound produced by the air conditioner with this sleep-inducing effect was later termed “white noise.” White noise is similar to white light as it contains a mix of sound waves across a broad spectrum, which effectively creates a sound bubble in which specific frequencies or noises are muffled. The principles that enable white noise machines to enhance sleep have also been applied to learning environments. The ability of white noise to improve cognitive function in children and adults with attention-deficit/hyperactivity disorder (ADHD) has been previously evaluated and demonstrated (14– 16). This review aimed to identify and summarize the body of published literature that evaluated the impact of sound environment on memory, specifically the use of white noise as an intervention.

METHODS Literature search The PubMed online database was searched for published studies that evaluated the impact of white noise on cognitive functions related to memory. Titles and abstracts were searched for combinations and iterations of the terms “white noise” and “memory” without restrictions on publication date, language, or location. Studies conducted on humans were considered. Published reviews were not restricted. Titles were screened for relevance to the research topic, and selected titles were further included for an abstract review. Studies that met the inclusion criteria based on abstract reviews were accessed and downloaded for full-text review.

Data extraction Data from relevant articles were extracted and entered into a data collection tool based in Microsoft Excel. Fields for extraction included the study title, author, journal of publication, publication date, study population, population size, year and location of the study, definition of white noise, experimental exposure groups, comparator group, metric or test used to evaluate memory, and effect size.

Definitions Criteria for white noise intervention was not specified. All studies that reported the use of white noise as an intervention method were included. Furthermore, the definitions used in each study were recorded along with the applied frequency and duration.

RESULTS Based on the refined search terms, 126 articles were identified. Title screening identified 15 potentially relevant studies. After abstract screening, 11 articles were selected for full-article screening, and all were included. Of the 11 studies, six and seven were conducted with adults and children or adolescents, respectively (Table 1). Furthermore, seven studies evaluated healthy individuals without any stated learning or cognitive disorders. These studies were conducted in a diverse range of countries across North America, Europe, and Asia. The earliest study was published in 1974; however, most others were conducted more recently. The number of participants in each study ranged from 20 to 160.

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Summary of the study outcomes The intensity of white noise evaluated in each study varied considerably. The lowest and highest intensity applied were 20 dB and 90 dB, respectively. Several studies included other auditory stimuli, such as music, normal and backward speech, machine and ambient noise, and single-ear stimuli. Only five studies included a control group with no noise. The method of cognitive evaluation also differed between the studies (Table 2). The tests ranged from verbal to visual and recall tasks. Several studies included multiple examinations for each group. In 10 of the 11 studies, researchers reported cognitive enhancement in at least one of the population sub-sets. Sub-group analysis showed that white noise either had no effect on or resulted in decreased cognitive performance in the normal or advanced cognition groups. Title

Year of publication

Background white noise and speech facilitate visual 2021 working memory (17)

First author

Population

Country

Participants included

Han S

Healthy adults, China 18–25 years

Chen IC

Boys, 6–10 years, ADHD Taiwan or Typical development (TD)

2021

Söderlund GBW

Children, 10– 13 years, children with Sweden reading disorder and good readers

Cognitive performance, creativity and stress levels of neurotypical young adults 2022 under different white noise levels (20)

Awada M

USC students, USA 18–64 years

Auditory white noise affects left/right visual working 2019 memory in an opposite pattern (21)

Wang R

Healthy adults, 18–30 years

The effects of background white noise on memory performance in inattentive school children (22)

2010

Söderlund GB

Secondary School Students, 11– 12 years

Effects of white noise on word recall performance and brain activity in healthy 2020 adolescents with normal and low auditory working memory (23)

Othman E

Men, 18–24 years

Listening to white noise improved verbal working memory in children with AttentionDeficit/Hyperactivity Disorder: A pilot study (18) Sensory white noise improves reading skills and memory recall in children with reading disability (19)

2022

192

Malaysia

Different effects of adding white noise on cognitive performance of sub-, normal 2014 and super-attentive school children (24)

Helps SK

Children, 8–10 USA

150

1974

Fenton TR

Children, 9–11 years, normal development USA and learning disabilities

Listen to the noise: noise is beneficial for cognitive performance in ADHD (26)

2007

Children, 9–13 years, Söderlund G diagnosed with ADHD

The effects of noise and speech on cognitive task performance (27)

1993

Baker MA

Effects of white noise on short-term memory of learning-disabled boys (25)

Psychology course students

USA

160

Table 1. Overview of the relevant studies

First author

Han S

Chen IC

Söderlund GBW

Awada M

White noise frequency

Exposure groups

Outcome measurement

Outcome

1) Background speech 2) White noise 3) Quite condition

Visual working memory task

Both background speech and white noise facilitated working memory performance.

78 dB

1) No sound 2) White noise 3) Music

Peabody Picture Vocabulary Test Nonverbal Intelligence Test Digital Span Test

White noise benefited verbal working memory in children with ADHD. However, external music did not.

80 dB

Single word reading Orthographical word recognition (word chains) Nonword reading (phonological decoding) 1) Auditory noise Single word reading and word 2) Visual noise recall task (verbal memory)

Visual and auditory white noise exposure improved some reading and memory capacities “on the fly” in children with RD and phonological decoding difficulties.

1) Ambient Noise 2) Low white noise 3) High white noise

Better cognitive performance and low stress levels when exposed to 45 dB. 65 dB white noise condition led to improved working memory; however, it increased stress levels.

55 dB

45 dB (low) 65 dB (high)

Continuous Performance Test Stroop Test Two-Back test Remote Associate Test Typing Performance Test

193

Wang R

Söderlund GB

Othman E

Helps SK

Fenton TR

1) Control 2-4) Right ear 65 dB condition Gaussian WN (20 Hz 5-7) Left ear to 20 kHz) condition

1) High noise condition 2) Auditory background noise (white noise) Verbal Episodic Recall Test

White noise improved performance for children who were inattentive and worsened performance for those who were attentive.

45 dB 50 dB 55 dB 60 dB

1) Level 1 2) Level 2 3) Level 3 4) Level 4

Auditory working memory was enhanced across all noise levels. Performance may differ depending on auditory working memory capacity of individuals.

65 dB 75 dB 85 dB

White noise worsened the performance of children who were super-attentive and improved performance in children who were sub-attentive. 1) Low white The performance of noise 2) Medium white Visuo-spatial working memory children with normal attentiveness was task noise unaffected by white noise The go/no-go task 3) High white exposure. Simple two choice RT task noise

22 dB (low) 72 dB (high)

1) Level 1 2) Level 2 3) Level 3 4) Level 4 5) Level 5 Short-term memory task 6) Control (quiet) (repeating 4-digit numbers)

White noise had a negative effect on written performance. The effect did not differ between children with disabilities and those without.

1) White noise 2) No noise

White noise improved performance in the ADHD group. However, it reduced performance in the control group.

78 dB

Söderlund G 81 dB

Baker MA

Visual color memory task

Left visual memory was improved with WN. Right visual memory showed reduced performance.

Backward recall task

Self-performed mini-task Verbal task

1) Quiet 2) White noise 3) Machine noise Simple card sorting 1) 55 dB Complex card sorting 4) Backward 2) 90 dB Anagrams speech 3) 90 dB Generation of random-letter 5) Normal 4) 85 dB sequences speech 5) 85 dB Table 2. Summary of the study details and results

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White noise enhanced performance on random generation; however, not for anagrams. The effect of a specific type of noise was related to the task demands. Interaction with other factors, such as sex and time of day, may be important.

DISCUSSION Overall, the review found that the presence of white noise improved performance across various cognitive tests. However, performance also decreased in several control groups. Evidence suggests that the impact of white noise varied based on the type of task and could also be influenced by other factors. A study reported a negative effect of white noise across all the groups (25). The positive effect of white noise was consistent in subgroups that had cognitive or developmental conditions, such as ADHD, which indicated that the baseline cognitive condition could be an important determinant of how individuals responded to white noise. A study examined various degrees of intensity of white noise and reported no strong evidence for different effect responses. This study has several important limitations that should be considered when interpreting the findings. First, the study did not insist on a standard definition of white noise exposure. Although white noise had a relatively clear and narrow description, variations in wavelength, duration of exposure, and amplitude of the intervention could have a measurable impact on its effects. However, the effect sizes across all the studies were similar, which suggested that minor variations in exposure did not modify the association between white noise and memory. Second, this analysis included study cohorts that ranged in age and baseline cognitive backgrounds. The diversity in the populations assessed limits the possibility of comparability between studies; however, the consistent findings across all evaluations strengthens the basis for the positive impact of white noise exposure on memory and learning. Third, the selected studies included various outcome measurement approaches. The cognitive tests were well described and suitable; however, there was a lack of standardization between the studies, which prevented meaningful cross-comparison. However, as the biological mechanism of white noise on cognitive function was presumably similar across diverse memory performance tasks, consistent outcomes across studies strengthened these findings. Fourth, only the PubMed online database was searched for relevant studies; other data sources, such as MEDLINE, Web of Science, and Google Scholar, could have contained additional studies that were not included. Finally, this study did not include a pooled meta-analysis of the retrieved studies. A meta-analysis could overcome the small sample size and limited statistical power of individual studies to develop an overall estimate of the effect size of white noise on cognitive function. As mentioned above, substantial heterogeneity, although not formally assessed, between the studies limits the interpretability of the aggregated results. Furthermore, this study did not extract the specific effect size of each intervention as the exposure and reference groups in each study were different. Despite these limitations, this study has several important strengths. First, a systematic approach was used to identify relevant research papers from peer-reviewed scientific journals. Inclusive and general search terminologies were used and provided a high probability to capture relevant studies. The search produced studies manageable to review and assess for relevance. Second, specific inclusion and exclusion criteria were set in advance to minimize the chance of bias in study selection. Third, studies were not excluded based on the population evaluated, characteristics of white noise administration, or outcome measurement method. This ensured a comprehensive and exhaustive list of potentially relevant studies. Soundscape is an environmental feature that can be controlled and adjusted in many settings. Modifying a sound environment to optimize cognitive function in individuals and groups is a potential tool that could be used to improve performance, memory, and learning opportunities, especially in populations with ADHD or other cognitive conditions. Considering its mixed results and even negative impact on children and adults without any disabilities, these interventions should be administered at an individual level. Fortunately, white noise can be introduced in a targeted way, such as via headphones; therefore, a customized approach can be used for diverse groups. Use of white noise to enhance performance in jobs that require an individual to frequently recall of information, similar to the cognitive tests evaluated in the included studies, may also be advantageous. Professions, such as call center operators or other dispatch services which may significant nonuniform background noise, may benefit from having white noise to act as a buffer.

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Additional studies are required to further characterize the impact of white noise in special populations and understand the potential interactions with other environmental factors that may impact its effect. Larger studies that assess the effects of repeated exposure to white noise and measure performance during more complex tasks should be conducted. It would be helpful to standardize the methods used in prospective studies to enable comparability. Finally, it would be informative to include measures of effect size to estimate the degree to which white noise or other sound interventions improved or impaired cognitive function. White noise may have important clinical applications for improving learning and cognitive function, especially in populations with impaired cognition. Systematic approaches should be adopted to investigate the optimal intervention for each individual. Furthermore, an individualized approach should be taken, similar to other applications of clinical therapy.

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Social Stigma on Electronically Monitored Offenders in South Korea Author 1

Full Name

Rhee, Sieeun

Branksome Hall Asia

(Last Name, First Name)

School Name

ABSTRACT: The pains of electronic monitoring for offenders has been explored in depth in various previous studies. Commonly, researchers have investigated the psychological impact or stress of being electronically monitored and identified that the struggles of electronic monitoring impact offenders’ social dynamics and community integration. It is also widely accepted that monitored offenders experience a high degree of stigmatization in society due to negative perceptions and stereotypes. However, the specific reasons why such stigmatization occurs to offenders was not examined in detail. This paper addresses this issue by investigating the association between electronic monitoring and social stigma specifically on offenders in South Korea. A recognized theoretical framework regarding the four components of stigma as developed by Link and Phelan (2001) is applied to the experiences of electronically monitored offenders and the unique Korean cultural context is considered when determining the correlation between electronic monitoring and social stigma. By conducting a detailed comparison of such factors with Link and Phelan’s proposed four components of stigma to identify whether corresponding elements exist, the study reveals that stigmatization of offenders occurs at various levels in society and has significant social consequences. The results of the study call attention to the ultimate purpose of the electronic monitoring program in Korea and questions whether the current policy, stigmatizing as it is, is suitable for achieving that purpose. Note that this paper is not a qualitative analysis, but rather an application of theory to a real-world context for examining a correlation between two social elements.

KEYWORDS: electronic monitoring, criminal justice, social stigma, theoretical application

198

Social Stigma on Electronically Monitored Offenders in South Korea Electronic monitoring as a criminal sanction is a system of keeping track of the locations of high-risk offenders using a monitoring device usually in the form of an ankle bracelet (Korean Ministry of Justice). It is a relatively new policy in the criminal justice system, first developed and implemented in the United States in the 1980s. Its primary aims were to reduce prison overcrowding, prison maintenance costs, the social fear of crime, and to discourage recidivism (Payne & Gainey, 2000). In South Korea, the legislation of the electronic monitoring act was passed in 2007, and enforced in 2008 (Korean Ministry of Justice). At the time, crimes subject to monitoring post-release was sexual assault only, but over the years several other crimes were added: child abduction, murder, and theft (Korean Ministry of Justice). Offenders receiving suspended sentences, conditional early release, and post-release were also later included in the conditions (Korean Ministry of Justice). In approximate numbers, there are currently around 4,500 to 5,000 electronically monitored offenders in Korea, and a division of numbers according to their crime types are shown in Table 1 below.

Table 1 Electronically Monitored Offenders in Korea by Crime Type Sexual assault

Abduction

Murder

Theft

Parole

Conditional Release

2,603

523

156

262

906

Total 4,459

Note. Numbers from the Korean Ministry of Criminal Justice, as acquired by a Korean news agency (NewsMin) through a request for information disclosure. The data was collected in October 2022, and does not account for changes in numbers that have happened since. The aim of this study is to investigate the association between electronic monitoring and social stigma on offenders in South Korea. This subject comes of interest owing to the fact that electronic monitoring is a relatively new system in Korea and thus its effects have not yet been thoroughly examined. In addition, the impact of the Korean cultural context is expected to act as a significant overarching factor due to the distinct natures and characteristics of Korean society. Over the years, the Korean criminal justice system has been repeatedly accused by its citizens of being overly lenient on offenders and protective of their rights, while being largely careless towards the welfare of victims and their families. Consequently, public attitude has turned extremely unfavorable towards offenders; as a result, contrary to the triumphant attitude that countries practicing punitive justice possess towards criminals and crime control, negative public perceptions about any and all criminal offenders have shaped Korean society to be especially unforgiving and stigmatizing. However, considering that the ultimate goal of the electronic monitoring program is not to stigmatize offenders but to discourage recidivism and enable them to lead a crime-free life, excessive stigmatization of offenders may induce the opposite of the desired goals of electronic monitoring. Therefore it is significant to investigate how social stigma is inflicted upon electronically monitored offenders in order to ensure the effectiveness of the electronic monitoring program in the long term. In this article, an examination of how electronic monitoring is related to social stigmatization of offenders will be conducted using the theoretical framework of Link and Phelan’s proposed four components of stigma. By conducting a detailed examination of theoretical factors, general real life trends, and the past experiences of electronically monitored offenders as reported in various scholarly articles, we aim to identify how the pains and characteristics of electronic monitoring converge with

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the components of stigma. While the focus of the study will be mainly on Korea, information and qualitative data from other countries will also be incorporated due to the limited number of Korean studies conducted on related subjects. A conclusion will be drawn as to determine the intensity of stigma associated with electronic monitoring, and the Korean context will be considered as an overarching factor in the analysis of each stigma component. The upcoming sections of this paper will explain the details on the effect of the Korean context on the investigation and the theoretical framework of social stigma before the theory is applied to a real-world context for examination.

The Korean Context It is significant to understand the background of Korean social norms and practices because of the impact they have on the social stigmatization of electronically monitored offenders. Korea, similar to many of its neighboring East Asian countries, has a distinctly unique culture owing to its ancient history, and therefore it is crucial to discuss the general characteristics of Korean society in order to fully understand stigma on monitored offenders. Being a highly collectivistic society, Koreans have a strong sense of long-term commitment to a member group. Thus, loyalty is especially important and overrules most other societal rules and regulations. Shaming and loss of face is common among those who commit offense in any way that is outside the boundaries of their group. This extremely powerful sense of community and strict social norms is one of the main reasons why the nation lacks demographic diversity and stigmatization is intense. In addition, Korea is highly conservative and uncertainty avoiding, intolerant of unorthodox behavior and ideas. People have the perception that the actions are restrained by social norms and are usually afraid of the consequences of going beyond such norms. Social interactions are impacted by hierarchies and social statuses, which oftentimes become the fuel for conflict. Considering such characteristics, criminal activity, without a doubt, is intolerable in Korean society, which explains why it is common for criminal activity to be highly publicized and offenders to be publicly shamed. The unusually negative public perception of crime and criminals derive from not only cultural factors, but also from past social practices. As mentioned previously, the Korean criminal justice system has been repeatedly accused of being overly lenient on criminals and protective of their rights while being inconsiderate about the wellbeing and recovery of victims. Thus a strong “us vs. them” mentality towards criminals was established. Also, the electronic monitoring program has not been greeted with much enthusiasm because of repeated occasions of offenders committing recidivism and fleeing after damaging the monitoring device. These unique cultural characteristics of Korean society are expected to be a major influencing factor when considering the social stigmatization of monitored offenders.

More on Social Stigma While investigating the association between electronic monitoring and social stigma, stigma is a concept that will be explored in depth in this article. As defined by Link and Phelan (2001), stigma is a process that occurs when “elements of labeling, stereotyping, separation, status loss, and discrimination cooccur together in a power situation that allows the components of stigma to unfold”. The dimensions of social stigma have been previously studied by many sociologists and psychologists. Stigma is a complex concept, for it is sometimes explicitly apparent but most other times it simply exists, manifested in many aspects of society. In recent years, the development of the electronic monitoring program has caused public views towards offenders to change, taking a more negative turn (Lee & Kim, 2013). Social stigma on offenders increasingly became an issue for many countries because psychology studies have revealed that the negative effects of social stigma can lead to higher recidivism rates and unsuccessful reintegration into society (Moore et al., 2016). Levels of stigma in a society can be divided into three main factors.

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First, at the structural level, are institutional barriers that marginalize certain groups or individuals through laws or policies (Link & Phelan, 2001). These barriers tend to evolve and permeate into norms and practices over time, and have the potential to control public perceptions and attitudes towards target groups or individuals in the long term (Link & Phelan, 2001), such as how racial discrimination still impacts the workforce or to this day, deriving from past societal practices. Second, at the social level, are stereotypes and acts of discrimination from community members (Link & Phelan, 2001). This level includes the public’s stigmatizing attitudes and discriminatory activity in individual human interactions (Link & Phelan, 2001). The social factor of stigma can have a great and lasting mental impact on the discriminated individual or group, which leads to the third factor, the individual level of stigma: the individual responses to the structural and social factors, including perceived and internalized stigma (Link & Phelan, 2001). The abovementioned constructs of stigma are confounded with each other, and thus it is often difficult to conclude how specific aspects of the stigma process affect human behavior (Link & Phelan, 2001). However, the general psychological effects of stigma are well-studied. Self-stigma, the ways in which individuals are affected by stigma, can be divided into three types: anticipated stigma, perceived stigma, and internalized stigma (Moore et al., 2016). Anticipated stigma is the expectation that one will personally experience discrimination or consequences due to having a stigmatized identity, and it can lead to defensive behavior, distress, fear, and the urge or actual avoidance of situations (Link & Phelan, 2001). It is theorized that anticipated stigma leads to increased criminal behavior upon release for offenders, though this has not been tested (Moore et al., 2016). Perceived stigma is the perception that society currently holds negative views of one’s group, which can negatively affect self-esteem, mental health, and behavior (Moore et al., 2016). Usually, perceived stigma tends to be more intense than the public’s actual attitudes, and often offenders with intense perceived stigma have poor social interactions, higher unemployment rates, or depression upon their release from prison (Moore et al., 2016). Perceived stigma can lead to internalized stigma, which is when individuals absorb negative messages or stereotypes about their group and come to believe that and apply them to themselves (Moore et al., 2016). Many studies suggest that behavior changes of individuals are closely related to anticipated stigma because of its relation to maladaptive behaviors and impaired functioning (LeBel, 2012; Vanhaelemeesch et al., 2013). However, there are other factors involved with social stigma such as personality traits and perceived social identities that can influence individuals’ behaviors (Vanhaelemeesch et al., 2013), which have not been studied in depth due to the difficulty of analyzing such abstract and unique characteristics.

Application of Theory The four components that will be used to analyze the correlation between the electronic monitoring program in South Korea and social stigma on monitored offenders is a theory widely accepted by the literary community, as originally proposed by Link and Phelan. Though the exact process of stigmatization cannot be explicitly defined, Link and Phelan (2001) divided stigma into four components and determined that stigma exists when these components converge. In the forthcoming sections, the components of stigma theory will be applied to the electronic monitoring experience of offenders in Korea. Component 1: Distinguishing and Labeling Differences Although we are moving forward to a world where the equality of all individuals is considered especially important, it is undeniable that certain differences set humans apart from each other. As such, the first component of stigma is the “distinguishing and labeling of differences”, which refers to the

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social selection of human differences that happen when it comes to identifying differences that will matter socially (Link & Phelan, 2001). This component merely refers to the recognition of differences that undoubtedly exist among different individuals (Link & Phelan, 2001). Such differences can include race, age, gender, health status, social status, etc. In general, the physically noticeable factor of electronic monitoring corresponds with this first component of stigma and sets monitored offenders apart from ordinary individuals. Similar to how race or gender are physical differences of individuals that can be recognized easily, monitored offenders are burdened by the physical attribute of having to wear the electronic device on their ankles (Payne & Gainey, 1998). While natural differences such as ethnicity are easily neglected, a man-made difference like an ankle device is highly noticeable and thus directly labels the wearer as “criminal”. Though this may be one of the unstated but intended purposes of the electronic monitoring program, there is no doubt that the physical factor is stigmatizing for monitored offenders. Especially in South Korea where there is hardly any racial diversity, characteristics that physically distinguish individuals from others stand out prominently. According to Payne and Gainey (1998), electronically monitored offenders have reported that not only does wearing the ankle device cause physical discomfort due to sweating, it also makes them feel shameful to be active in public and forces them to stay conscious of how people perceive them. Payne and Gainey’s study also revealed that monitored women were more concerned about how the device potentially affected their appearances (Payne & Gainey, 1998). Additionally, offenders reported that they wanted to conceal their devices or monitored status from other people, which had an impact on their social lives (Vanhaelemeesch et al., 2013). Specifically in Korea, offenders have voiced the inconvenience caused by wearing the device, reporting that it limits their job opportunities and negatively impacts their mental health (Yun & Bae, 2019). Like this, offenders’ past experiences illustrate how the physically conspicuous nature of electronic monitoring has a stigmatizing effect on wearers because of their noticeability. Wearing an electronic monitoring device allows people to automatically distinguish an offender among ordinary individuals. Evidence from past studies show that offenders are aware of this fact, and the resulting psychological pressure reduces the boundaries of their social lives. Component 2: On Associating Human Differences with Negative Attributes A development in stigmatization occurs when distinguished human differences are noticed by others, then recognized as a negative characteristic. Thus the second component of stigma is the “association of human differences with negative attributes”, which refers to the linking of labeled differences to certain stereotypes (Link & Phelan, 2001). This second component happens when a group is linked to a set of shared, specific, and undesirable characteristics that form the stereotype (Link & Phelan, 2001). These categories and stereotypes are often set automatically because they are made through split-second judgements and operate unconsciously in people’s minds (Link & Phelan, 2001). In order to identify how electronically monitored offenders have come to be associated with negative attributes, one must date back to the very origins of the program, when it was first implemented in Korea in 2008. Following the success of the program in the United States and in a few European countries, Koreans were expecting the implementation of the electronic monitoring program to cause a significant reduction in recidivism of sex offenders (Lee & Kim, 2013). The Korean government was overly confident about the effectiveness of electronic monitoring that when news of recidivism by monitored offenders were reported quite frequently, the reputation of the program itself deteriorated, and the public criticized the program as being too lenient (Lee & Kim, 2013). As a result, even though electronic monitoring did prove to reduce recidivism rates in the long term (Korean Ministry of Justice), monitored offenders were always negatively associated with violent crime, in addition to the already common hostility towards offenders.

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What intensifies the negative attributes associated with electronic monitoring is the fact that sexual assault on adult women has the worst public perception in South Korea, according to survey results (Lee & Kim, 2013). As mentioned previously, only sexual offenders were subject to electronic monitoring upon release during the initial years of the program in Korea (Korean Ministry of Justice). Consequently the public has come to automatically associate sexual assault with monitored offenders, which has strengthened the negative perception of monitored offenders in genera (Lee & Kim, 2013). Regardless of the individual characteristics and circumstances surrounding each offender, people associate the negative connotation of “crime” and “electronic monitoring” to them, resulting in stigmatization. Component 3: Separation of “Us” from “Them” The third component is the “separation of ‘us’ from ‘them’”, or the creation of the “us versus them” mentality (Link & Phelan, 2001). The rationale for this component is the second component, which convinces people to believe that negatively labeled persons are fundamentally different from those who don’t share the label (Link & Phelan, 2001). As a result, the “us versus them” mentality is created because people sense no harm in attributing all manners of bad characteristics to “them” (Link & Phelan, 2001). In certain extreme situations, the stigmatized group is thought to be completely separate or different from “us” to a level of dehumanization (Link & Phelan, 2001). An example of this would be the dehumanization of the Jews by the Nazis during their World War II regime. In the case of electronic monitoring, the separation of ‘us’ from ‘them’ is seen through the lack of offenders’ involvement in communal activity. However, it would be illogical to argue that social hostility is the only cause for this separation, since it is common for offenders to feel that they have low chances of successfully reintegrating into society upon their release. 64% of Korean offenders surveyed in Lee and Kim’s study answered that being monitored is extremely challenging and stressful due to the psychological pressure and shame of going public wearing the monitoring device, wary of how others will view them (Lee & Kim, 2013). 73.2% of surveyed offenders reported that they sensed hostility from their employers or coworkers at work due to their status, and 72.7% felt that their monitored status was as punitive to their family members as much as it was a punishment for themselves because of their separation from society (Kim, 2013, as cited in Yun & Bae, 2019). In addition, studies have illustrated a trend where offenders expecting to personally experience discrimination from community members will limit their abilities to function in the community (Moore et al., 2016). Such maladaptive behaviors have the potential to result in long-term unemployment and a dangerous lack of social interactions (Moore et al., 2016). In summary, negative social dynamics of monitored offenders serve as evidence that an “us versus them” mentality is created between ordinary people and offenders, which makes it difficult for monitored offenders to feel included in the community and ultimately lead to stigmatization. Component 4: Status Loss and Discrimination The fourth component is “status loss and discrimination” (Link & Phelan, 2001). The fact that a specific group is labeled, separated, and linked to undesirable characteristics will cause them status loss, the downward placement of a person in a hierarchy due to their label, and discrimination (Link & Phelan, 2001). Discrimination can happen at the individual or structural level, shown overtly or through accumulated institutional practices that work to the disadvantage of the stigmatized group, even in the absence of individual prejudice (Link & Phelan, 2001). Status loss and discrimination will inevitably bring forth negative consequences because if one believes that others will devalue and reject people of a certain group, one fears that the rejection will apply personally (Link & Phelan, 2001). Several structural practices indicate status loss of and discrimination against electronically monitored offenders in South Korea. The first is the Law Restricting Sex Offenders’ Employment, which prohibits monitored offenders who have previously committed sexual assault from working at educational

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institutions, healthcare institutions, or childcare centers for up to ten years (Yun & Bae, 2019). For some offenders, this restriction forbids them from returning to their work positions before they were imprisoned (Yun & Bae, 2019). General hostility and ostracization of offenders also prevent them from seeking high-paying office or commerce jobs (Yun & Bae, 2019). These forms of direct and indirect discrimination in the workforce against monitored offenders has been the center of debate in the past as it was pointed out that the law is an infringement on an offender’s freedom of choice (Yun & Bae, 2019). Despite the controversy, the public is still keen on expanding the restrictions on the job choices of offenders, leaving most offenders in poor jobs with inadequate working conditions (Yun & Bae, 2019). Another discriminatory law in Korea which illustrates the status loss of offenders is the disclosure of personal information of sex offenders. Offenders are required by law to report their address of residence, photo, and personal information to the police, which are disclosed to nearby residents for up to 5 years (Yun & Bae, 2019). Offenders have revealed that they were concerned about getting recognized by their coworkers or neighbors, and that the disclosure of their personal information was causing significantly more stress than being monitored due to the fear that the effects might reach their family members (Yun & Bae, 2019). Aside from the discriminatory structural practices that stigmatize offenders, indirect status loss and discrimination also occur for offenders and are apparent in certain social patterns. For example, the negative perception of offenders causes them difficulty in getting involved in community practices and extending their social networks through interactions at their workplaces (Yun & Bae, 2019). They are also usually rejected by their partners and denied as a family member, due to the shame of having a criminal in the family (Yun & Bae, 2019). Ostracization from families is especially intense in Korea due to the high level of value placed on social norms. In one study, a monitored offender reported that they are discouraged by the stigmatization and are frightened to make new social connections: “I feel small. It’s daunting, and it lowers my self-esteem… Meeting new people is just uncomfortable for me now” (Yun & Bae, 2019). Like so, the fact that the fourth component of stigma is evident in social practices in Korea illustrates that offenders are highly stigmatized and that they experience frequent status loss and discrimination in almost every aspect of life, from privacy infringement to limited freedom of choice.

Conclusion The electronic monitoring program in South Korea has been revealed to be a highly stigmatizing policy for offenders. The various qualitative factors of the electronic monitoring experience in Korea are directly associated with the four components of stigma as proposed by Link and Phelan (2001). The status loss of monitored offenders in Korean society is evident through common discriminatory practices both at the structural level and the social or individual level. The significance of these findings lies in the fact that the study of stigma on electronically monitored offenders is unprecedented in Korea. The unique cultural context provides a new perspective on the social implications of the electronic monitoring program. On one hand, the analysis from this study suggests that the electronic monitoring program, designed to prevent recidivism to help offenders lead a crime-free, positive life in the future, is failing to achieve its purpose. The electronic monitoring program aims to bring forth community benefits such as reducing the social fear of crime, but its primary goal is largely to enable offenders to reintegrate into society and thus reduce recidivism in the long term. The stigmatization of monitored offenders evokes just the opposite effect; evidence shows that electronic monitoring rather discourages offenders from attempting to rebuild their lives and reintegrate into their communities. Ultimately, the effectiveness of the electronic monitoring program in guiding offenders to a positive future must be called into question, considering the negative social consequences of stigmatization.

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On the other hand, it is important to recognize that the Korean national sentiment disagrees on the point that the social stigmatization of offenders is a negative social practice. The general public opinion in Korea is that offenders deserve stigmatization and that electronic monitoring should be more punitive in order to eliminate recidivism. Overall, Koreans are very invested in overseeing that ‘proper’ criminal justice is done to create a crime-free society. Thus, in their eagerness to increase the punitiveness of the sanctions on offenders, they are unaware that the stigmatization of offenders will ultimately and inevitably lead to increased recidivism, in increasingly violent forms. According to Yun and Bae (2019), the sense of isolation and loneliness felt by offenders during their social reintegration is the result of stigma and ostracization, and it is also what ultimately places offenders in an unending loop of exclusion from society and recidivism. Additionally, in Moore et al.'s (2016) study, it was found that prisoners’ perceived stigma led to high anticipated withdrawal from society as well as a high number of violent felony convictions during their EM sentence following their release. Therefore it is crucial for the Korean public to understand that electronic monitoring does not inflict overly intense stigma on offenders if it is to achieve its desired effects of reducing recidivism. While this research applies the theory of social stigmatization on the electronic monitoring program of South Korea, it does not empirically examine their relation. There is a lack of quantitative or qualitative data on the subject matter owing to the fact that electronic monitoring is a relatively recent development in the Korean criminal justice system and thus not enough academic research has been conducted to gather sufficient data. Future research should address this concern by observing the social effects of electronic monitoring more closely in context and gathering statistical data to identify trends of stigma evident on offenders. In summary, it is recommended that policymakers take into consideration that within the given unusual cultural circumstances of the Korean setting, the electronic monitoring program is an overly stigmatizing experience for most offenders, which may be the reason why offenders fail to effectively reintegrate into society and return to criminal activity instead.

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References Belur, J., Thornton, A., Tompson, L., Manning, M., Sidebottom, A., & Bowers, K. (2020). A Systematic Review of the Effectiveness of the Electronic Monitoring of Offenders. Journal of Criminal Justice, 68, Article 101686. Benson, M. L., Alarid, L. F., Burton, V. S., & Cullen, F. T. (2011). Reintegration or Stigmatization? Offenders’ Expectations of Community Re-Entry. Journal of Criminal Justice, 39(5), 385-393. Bos, A. E. R., Pryor, J. B., Reeder, G. D., & Stutterheim, S. E. (2013). Stigma: Advances in Theory and Research, Basic and Applied Social Psychology, 35(1), 1-9. Cho, Y. N. (2013). A Study on the Rehabilitation of Offenders under the GPS Electronic Monitoring. 俥潘碁咤灅͑ͩ͝(1), 411-435. Corrigan, P. W., Watson, A. C., & Barr, L. (2006). The Self-Stigma of Mental Illness: Implications for Self-Esteem and Self-Efficacy. Journal of Social and Clinical Psychology, 25, 875–884. Farkas, M. A., & Miller, G. (2007). Reentry and Reintegration: Challenges Faced by the Families of Convicted Sex Offenders. Federal Sentencing Reporter, 20(2), 88–92. Holman, J. E., & Quinn, J. F. (1992). Dysphoria and Electronically Monitored Home Confinement, Deviant Behavior, 13(1), 21-32. ͙͚ͥ͑ͻΒΟΘ͑͝Ͷ͑͟;͙͑ͣͣͣ͑͟͡͝͵ΖΔΖΞΓΖΣ͚͑ͣ͑͟欬檸彄漴͑潑槑͑泅伨摠χχχ伨摅彑͑檤彀揔徼χ欬檸怜摅͑ 嗀棜͑͟NewsMin. https://www.newsmin.co.kr/news/81752/ (2) Korean Ministry of Justice. Electronic Monitoring. https://www.moj.go.kr/moj/169/subview.do (7) LeBel, T. P. (2012). Invisible Stripes? Formerly Incarcerated Persons' Perceptions of Stigma, Deviant Behavior, 33(2), 89-107. (5) Lee, S.C. & Kim, C.S. (2013). A Study on the Stress and Suicide of Offenders Who Have Placed on GPS Electronic Monitoring. Korean Journal of Probation, 13(1), 227-282. (1) Link, B. G., & Phelan, J. C. (2001). Conceptualizing Stigma. Annual review of Sociology, 27(1), 363-385. Moore, K., Stuewig, J., & Tangney, J. (2013). Jail Inmates' Perceived and Anticipated Stigma: Implications for Post-Release Functioning. Self and Identity: The Journal of the International Society for Self and Identity, 12(5), 527–547. (6) Moore, K. E., Stuewig, J. B., & Tangney, J. P. (2016). The Effect of Stigma on Criminal Offenders’ Functioning: A Longitudinal Mediational Model. Deviant Behavior, 37(2), 196– 218. (9) Payne, B. K., & Gainey, R. R. (1998). A Qualitative Assessment of the Pains Experienced on Electronic Monitoring. International Journal of Offender Therapy and Comparative Criminology, 42(2), 149–163. (3) Payne, B. K., & Gainey, R.R. (2000). Electronic Monitoring, Journal of Offender Rehabilitation, 31(3-4), 93-111. Richter, M., Ryser, B., & Hostettler, U. (2021). Punitiveness of Electronic Monitoring: Perception and Experience of an Alternative Sanction. European Journal of Probation, 13(3), 262–281. (8) Vanhaelemeesch, D., Vander Beken, T., & Vandevelde, S. (2014). Punishment at Home: Offenders’ Experiences with Electronic Monitoring. European Journal of Criminology, 11(3), 273–287.

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Yun, E. J. (2017). Psychological Consideration on Electronic Monitoring - Focusing on ‘Gaze’. Korean Journal of Probation, 17(1), 210-229. (10) Yun, H. B., & Bae, I. H. (2019). A Study on the Social Reentry Experience of Sexual Assault Criminals with Electronic Anklets. Korean Journal of Probation, 19(2), 147-202.

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Predicting the Decline of Pronvincial Cities through Data Science Techniques Author 1

Full Name

Seo, Yeeun

Seoul Girl's High School

(Last Name, First Name)

School Name

ABSTRACT: The rapid increase in the elderly population aged 65 and above is not only a phenomenon observed in South Korea but also a global trend. In South Korea, the concentration of economic activity in the metropolitan area has led to accelerated aging and even urban decline in provincial cities. This urgent situation has prompted the need for action. This paper aims to analyze historical population distribution data from Japan's cities facing decline and apply it to specific cities in South Korea. Additionally, it seeks to address South Korea's aging population and population decline rates using Data Science Linear Regression Analysis techniques. Before delving into solutions for issues like aging, Preliminary working-age population, and Economically active population caused by the advancement of modern IT technologies like AI, this paper aims to cultivate a sense of crisis regarding the current aging problem. Rather than adopting a positive approach through estimation, the focus is on practical future predictions based on data. By doing so, the intention is to raise awareness about the aging issue and present solutions for regenerating cities facing decline, utilizing case studies as examples.

KEYWORDS: Data science, Linear Regression Analysis, Aging society, Extinction of Local Cities, Japan Yubari City, South Korea Seocheon-gun, Data prediction

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I. Introduction 1.1. Problem recognition and research objectives The trend of declining population, particularly in advanced countries, is spreading globally. Countries like South Korea and Japan are experiencing low birth rates, an aging population, and urban concentration, leading to the rapid disappearance of smaller rural towns and cities. According to the Local Extinction Risk Index announced by the Korea Employment Information Service in February 2023, out of the 194 towns and neighborhoods within Gangwon Province, 154 are classified as areas at high risk of extinction, with 4 municipalities that were categorized as 'entering extinction' now included in the 'high extinction risk' classification. The phenomenon of low birth rates and aging populations has emerged as a societal issue alongside global population distribution concerns, contributing to a growing disparity between population growth in metropolitan and major urban centers compared to surrounding rural and agricultural areas.

fig1.Korea Audit Office: A picture of the degree of extinction in Korea

In the case of Japan, the population of Yubari City in Hokkaido, which was close to 120,000 in the 1960s, has decreased to below 9,000 people as of 2018. Additionally, it's reported that the 20 villages within Yubari City have no inhabitants. According to research[1], this phenomenon is attributed to the post-bubble economy downturn in Japan, leading to a decline in tourism after the collapse of the bubble economy, followed by a financial crisis in the early 2000s. This crisis resulted in reductions in public officials, salary cuts, downsizing of city council members, consolidation and closure of public facilities, and the designation of a financial reconstruction body due to the inability to manage a debt exceeding 60 billion yen. In relation to this issue, Nordic countries in northern Europe are also facing a crisis where rural areas are shrinking due to urbanization-driven population migration and concentration of populations in major cities[2]. In other words, modern nations are confronted with a common challenge of not only population decline but also disparities in population and economic aspects between central and local areas, as well as between urban and rural regions. This study aims to analyze the population trends of Yubari City in Japan and Seocheon County in South Korea, both classified as regions at risk of local extinction, using predictive techniques from Data Science, with a focus on these challenges.

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1.2. Research methods and analysis tools

fig2. Study configuration phase graph (flow chart) In the first stage of data collection, population data for Yubari City was gathered from the Japanese government's statistical portal site (e-Stat) for the years 1980 to 2020. The data included the total population, population under 15 years old, population between 15 and 64 years old, and population aged 65 and above. Population data for Seocheon County in Chungcheongnam-do, South Korea, was collected from the KOSIS National Statistical Portal. The collected data files underwent a data cleansing process, during which the necessary data was extracted and other irrelevant data was organized. In the third stage, hypotheses were formulated and the population data was categorized into economic reserve population, economic population, and aging population. Subsequently, Python 3 programming language and the Jupyter Notebook tool were utilized to conduct a data analysis using Linear Regression Analysis techniques. For economic reserve population and economic population, predictive models were developed and analyzed. For aging population, the analysis focused on predicting the time of natural decline based on the average age.

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II. Main subject 2.1. Data Segmentation In the case of Japan, the analytical data classifies the population into three age groups: under 15 years old, 15 to 64 years old, and 65 years and older. However, in the case of South Korea, the data is categorized in 10-year intervals, resulting in similar criteria of under 20 years old, 20 to 60 years old, and 60 years and older.

fig3. Re-classification of population age group (Seocheon-gun, Chungcheongnam-do, Korea)

2.2. Liner Regression Analysis Linear Regression Analysis is a method used to discern the linear relationship between a single independent variable and a dependent variable.[3]. To conduct linear regression analysis, a linear regression model must be constructed. This model represents a mathematical function and signifies the correlation between one or more independent variables and the dependent variable[4]. In this context, the mentioned paper developed a Python program for the equation y=ax+b. This program aims to determine the trend line of the given data and, based on this trend line, predict the year when the age becomes 0.

fig4. python code n the given data, the year information was stored in a variable named 'year'. The data for the preliminary

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working-age population (Under 15, Under 20) and the economically active population (Age 15~64, Age 20~59) were defined in variables 'under_20_data' and '_20_60_data', respectively. Subsequently, the 'polyfit' method from the numpy module in Python was employed to calculate the Slope and Intercept. Using the calculated Slope and Intercept, a function was created to determine the year when the value becomes 0 according to the trend line. This function was then used to predict the year when the value becomes 0 based on the corresponding trend line.

2.3. Data Prediction During the process of reviewing the data, differences among generational categories were observed. The preliminary working-age population (Under 15, Under 20) and the economically active population (Age 15~64, Age 20~59) exhibited a continuous decline, whereas the elderly population showed either stability or partial growth. In this context, considering these distinct data trends, the preliminary working-age population (Under 15, Under 20) and the economically active population (Age 15~64, Age 20~59) are intended to be predicted for their extinction times using the Linear Regression Analysis approach. On the other hand, for the elderly population, the intention is to predict the extinction time based on the starting age determined as the minimum age, considering the average lifespan, up to the average lifespan.

2.3.1. Analysis of Yubari in Hokkaido, Japan and prediction of extinction period Prior to predicting the extinction times, a program was developed to analyze the population trends by age group on a yearly basis, and the results were verified by examining the graphs.

fig5. Trend of population age group (Yubari, Japan) Through the graphs, a clear trend of decrease was observed, confirming the distinct direction of decline. This process also validated the validity of the Linear Regression Analysis predictions. Next, a program was developed to predict the extinction time (in years) for the preliminary workingage population (Under 15) and the economically active population (Age 15~64) using the Linear Regression Analysis technique. The results were then verified through this program.

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fig6. Prediction of population age group trends based on the previous period (Yubari, Japan) The predicted results indicated extinction times for each generation in the years 2014 and 2019. Upon analyzing the trend lines based on data from the initial period to 2020, it was observed that the slope of the trend relating to the initial sharp decline had a significant impact on the overall data. It was deemed necessary to predict the trend excluding the initial sharp decline data. To address these findings, an adjustment was made by shifting the representation of the trend line to focus on recent data. Subsequently, a new program was developed to predict the extinction times.

fig7. Recent Population Age Trend Forecast (Yubari, Japan) Using recent data as the basis, trend lines were drawn, and slopes and intercepts were determined. The prediction was then conducted by identifying the point where each generational group becomes 0

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according to the calculated trend lines. The predicted results indicate extinction times of 2028 and 2031 for different generational groups. Moving on to the prediction of the extinction of the elderly population, considering the final data point of 3,828 individuals in 2020, and a life expectancy of 88 years (based on 2021 data from the Japanese Ministry of Health, Labour and Welfare), the objective was to predict the extinction time. The prediction was based on the assumption that all individuals above 65 years old in 2020 would survive until the average life expectancy of 88 years. In other words, the aim was to find the year when the individuals aged 65 in 2020 would turn 88. The prediction results indicate that the extinction time for the elderly population is 2043. For the city of Yubari in Hokkaido, Japan, the predicted results for extinction are as follows: for the preliminary working-age population (Under 15), 2028, for the economically active population (Age 15~64), 2031, and for the elderly population, 2043. This means that the city is predicted to face extinction by 2043.

2.3.2. Data Analysis and Prediction of Extinction Time in Seocheon-gun, Chungcheongnamdo, Korea Utilizing the predictive model based on Yubari, Japan, the population of Seocheon County in Chungcheongnam-do, South Korea was categorized into preliminary working-age population (Under 20), economically active population (Age 20 ~ 59), and elderly population (Over 60). Prior to making predictions based on the given population data, an analysis was conducted.

fig8. Trend of population age group (Seocheon-gun, Chungcheongnam-do, Korea) The analysis results revealed a similar trend in Seocheon County, South Korea, as in Yubari, Japan. The preliminary working-age population (Under 20) and the economically active population (Age 20 ~ 59) showed a decrease, while the elderly population increased. Unlike Japan, however, the initial population decline in Korea was not steep; instead, it exhibited a gradual decrease followed by a more rapid decline in recent times. After 2018, there was a notable decrease in the economically active population and an increase in the

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elderly population in Korea. This indicates a shift in age groups and a rapid aging of the population. For the preliminary working-age population (Under 20) and the economically active population (Age 20 ~ 59), a program was developed using the Linear Regression Analysis technique to predict the extinction time (in years), similar to the model based on Yubari, Japan. The predictions were made using the trend line based on recent data.

fig9. Recent Population Age Trend Forecast (Seocheon-gun, Chungcheongnam-do, Korea) The predicted results are as follows: Preliminary working-age population (Under 20): Estimated extinction time in 2036. Economically active population (Age 20 ~ 59): Estimated extinction time in 2039. For the elderly population, considering the final data point of 25,280 individuals in 2022, and a life expectancy of 87 years (based on 2021 data from the Korean Statistical Information Service), the predicted extinction time is 2049. For Seocheon County in Chungcheongnam-do, South Korea, the predicted results for extinction are as follows: for the preliminary working-age population (Under 20), 2036; for the economically active population (Age 20~59), 2039; and for the elderly population, 2049. This means that the city is predicted to face extinction by 2049.

2.4. Data Prediction Results Comparison The preliminary working-age population and the economically active population for both Yubari, Japan, and Seocheon County, South Korea, showed a consistent trend of continuous decline according to the trend lines. However, a notable difference was observed in the elderly population. In Korea, there was a rapid increase in the elderly population, whereas in Japan, the elderly population was maintained rather than showing a significant increase.

III. Conclusion 3.1. Research Findings

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Population decline is an undeniable phenomenon. However, it is believed that without actively addressing the sharp decrease in the economically active population and the preliminary working-age population, or without focusing on the influx and retention of these population segments within the overall population composition, preventing urban extinction will remain a challenging endeavor. A city's survival isn't solely dependent on numeric population growth but also on the inflow of economically active individuals who contribute to the city's economic activities. The increase in real population can only be defined by the presence of economically active individuals within the city. Rather than approaching the issue purely through numerical population growth, efforts should be concentrated on securing the infrastructure to attract and sustain economically active individuals, as predicted. Through a balanced population composition, local administrations need to focus on preventing the extinction of regional cities and maintaining their sustainability. The case of Cheongju, Chungcheongnam-do, reflects the sustained inflow of young population. The introduction of secondary battery infrastructure in the Cheongju/Osong area has led to an increase in the economically active population, and the rise in the preliminary working-age population moving alongside the economically active population serves as an example of this dynamic.

3.2. Sweden's successful case

fig10. Number of persons per locality(Statistics Sweden) European countries are experiencing a deepening urban concentration similar to that of South Korea. However, they are also showing an overall trend of population growth, and they have managed to reduce the population disparity between central and regional areas compared to the past. Among them, Sweden's efforts in population inflow and regional innovation through regional policies are notable. European Union (EU) member states, including these European countries, are significantly influenced by EU cohesion policies on both national and regional levels. According to [2], since the establishment of the EU, the organization has been working to bridge regional disparities and promote balanced development among its member countries.

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Active immigration policies, universal welfare and gender equality, policies supporting the reconciliation of work and family life leading to increased birth rates, and comprehensive regional policies have contributed to these European countries addressing the threat of regional decline caused by population imbalances. These nations have established comprehensive regional policies by combining centrally-led social security policies and population policies, decentralization and empowerment, and utilizing EU cohesion policies. These measures aim to provide housing and job opportunities in areas facing the risk of regional extinction.

3.3 Proposed solution for Seocheon-gun, Korea 1) Revitialization of local culture and welfare - Visiting movie theater (town hall, senior citizen center): Operate by changing to a long-term event rather than a one-time event - Expansion of Seocheon-gun Comprehensive Welfare Center for the Disabled - Securing residential facilities for foreign workers 2) Development of regional representative tourist attractions and specialties - Planning a beach in Seocheon area as a tourist destination and using the geographical characteristics of the west coast such as the sale of seafood products - Although the first aviation security equipment test and certification center in Korea was recently built, a large budget was executed, which could be a case like Yubari City, so it seems necessary to distribute the appropriate budget. 3) Attracting preliminary economic population and economic population - Policies to revitalize market-linked life services, such as youth-centered, after-school education, and educational care - Expanding direct participation by residents and reflecting residents' opinions (Like the example of Spain and Sweden) - Operation of Youth Smart Farm Training Center

Reference [1] Gil Jong-baek and Ha Jeong-bong. (2020). The strategy and policy implications of overcoming extinction in Yubari, Japan. Journal of comparative government in Korea, 24 (2), 1-28.

[2] Jang Seon-hwa. (2023).The crisis of Nordic regional extinction and policy response: focusing on the Swedish case.European studies, 41(2), 177-208.

[3] Lim Hee-sung, Yoon Jin-sik, and Lee Kyo-beom. (2022).Estimation of the condition of lithium iron phosphate batteries using linear regression analysis.Journal of the biographical society, 71(2), 366-372.

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[4] Oh Young-hwan. (2020). Prediction of the ERA of high school baseball pitchers using multiple linear regression analysis techniques. Journal of the Korean Society of Knowledge and Information Technology, 15(4), 497-506.

[5]

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[6] 䮕㓳㳃(2020). 㐄䊔䨉愊盼壡瀌ꇺ澮崽壋睨戡鯸 උ൝ඣ࣮ࢩࢵࣉሗ࿌᭩

[7] Japan Yubaricity data csv: https://www.e-stat.go.jp/en/regional-statistics/ssdsview/municipality [8] Korea Seocheon-gun data csv: https://kosis.kr/index/index.do [9] SCB, “Pooulation expwcted to increase most in large cunties,”https://www.scb.se/en/findingstatistics/statistics-by-subject-area/population/population-projections/population-projections/pong/statistical-news/the-thefuture-population-in-sweden-2021-2040—counties-and-municipalities/

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Speak Big and Carry a Soft Stick: China as a Superpower of 21st Century Author 1

Full Name

Shin, Gun

Saint Paul Preparatory Seoul

(Last Name, First Name)

School Name

: : : :

ABSTRACT: In 1974, Deng Xiaoping stated that China would never be an imperialist superpower and denounced the United States and the Soviet Union as international exploiters and oppressors. However, the Chinese people now believe that their nation is positioned to act as the leading country in this new era. In 2017, President Xi Jinping proclaimed that the upcoming years will be an era where China moves closer to center stage and makes greater contributions to mankind. Despite Deng's denial of China's ambition to become a superpower fifty years ago, China is indisputably striving to become one. This essay explores the history of Chinese hegemony and major works of political philosophy in international politics, focusing on the requirements for the people of China and the rest of the world to live in a world without violent confrontation.

KEYWORDS: Superpower, China, Chinese Communist Party

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“China is not a superpower, nor will she ever seek to be one.”1 At the 1974 Special Session of the U.N. General Assembly, Deng Xiaoping promised the world that China will never be an imperialist superpower. At the same time, he denounced the two superpowers, the United States and the Soviet Union, as “the biggest international exploiters and oppressors” whose contention for world hegemony brought the world into turmoil.2 Not many people would believe that Deng’s words ring true to this day. In fact, the growing consensus of the Chinese people is that their nation is now “posed to act as the leading country in this new era.”3 Such a statement by Professor Shen Dingli, a prominent scholar of international relations at Fudan University, foreshadows the impending Chinese activism in reshaping the world order. China as the leading superpower is no longer a remote, hypothetical future. To understand what the world led by China will look like, this essay will explore the history of Chinese hegemony and some of the major works of political philosophy in international politics. Namely, it will focus on what is required of the people of China and the rest of the world to live in such a world without violent confrontation. The term superpower originates from William T. R. Fox’s 1944 book, The Super-Powers: The United States, Britain, and the Soviet Union—Their Responsibility for Peace. Fox characterized a superpower as a state that possesses “great power plus great mobility of power.”4 In his 1980 review of his own book, Fox also mentions the concept of a superpower as understood by other scholars. According to Fox, Hedley Bull described superpowers as “[states] possessing comparable military strength ‘in the first rank’ and recognized as having ‘certain special rights and duties.’”5 In addition to Bull’s definition, Fox notes Hans Morgenthau’s contribution to the understanding of the term superpower. Morgenthau saw a superpower as “a Great Power which has no rival capable of preventing it from imposing its will upon small Powers.”6 A superpower as we understand it today, then, can be said to have all three elements of mobility, prestige, and hegemony from Fox, Bull, and Morgenthau’s definitions, respectively. It is a state that can project its power outside of the regional sphere, carries international privileges as well as responsibilities, and is capable of forcing its will on others. In today’s world, only the United States properly fits into the definition of a superpower as described by Fox. The United States projects its military power around the world either directly through its aircraft carrier fleets or indirectly through its allies in other continents. It also enjoys special rights as the sole superpower, such as the role of the American dollar as a global reserve currency. As former French finance minister Giscard d’Estaing once called, the unparalleled status of the dollar in the global markets is the “exorbitant privilege” of the United States.4 And although some may argue that the United States cannot always force its will on other sovereign nations, its hegemony among liberal democracies of the world has never been questioned since the end of the Second World War. But a world in which China is the leading superpower is not at all a novel idea. It is in fact an ancient one. Starting as one of the oldest river valley civilizations, China reigned as the most powerful nation in the world until its defeat to the British Empire in the Opium Wars. Michael Schuman, the author of the book Superpower Interrupted: The Chinese History of the World, notes that China’s regional hegemony was uninterrupted for centuries. He maintains, “Unlike Europe, where states of roughly similar muscle contended for territory, trade, and influence, China had no real rivals…its neighbors accepted Chinese dominance and followed its rules of engagement.”8 China had been a hegemonic power in Asia long before the industrial revolution gave the chance for the Western nations to become great powers. While the lack of global communication and network prevented China of the past from becoming a superpower in a modern sense—in terms of mobility, prestige, and hegemony—China may be much more experienced in world governance as a superpower than what the rest of the world might imagine. But the past ways of maintaining the Chinese hegemony in the region were not always peaceful. As the history of the Sui, Tang, Ming, and Qing dynasty teaches, China as a regional power maintained its dominance over the neighboring countries through wars, regulations, and coercion. Schuman warns that “[the Chinese] world order, its rules and norms, was based on the principle of Chinese superiority, and the acceptance of that superiority by all others.”9 From this perspective, a world with China as the

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leading superpower will see the resurgence of high-handed diplomacy. The surrounding nations will be forced to recognize China’s superiority and accept its policy. Assuming that China replaces the United States as the leading superpower in the near future, one cannot help but think about the words of Francis Fukuyama—and how awfully wrong he was in 1989. That year, Fukuyama wrote the article The End of History and argued that humanity was witnessing “the end point of mankind’s ideological evolution and the universalization of Western liberal democracy as the final form of human government.”10 In other words, he declared the ultimate Hegelian victory of liberal, capitalist democracy over all other forms of society. The serial demise of absolutism, fascism, and bolshevism from the First World War to the fall of the Soviet Union gave enough grounds for him to make such a bold claim; however, Fukuyama’s conclusion would be premature considering how distant China is from becoming a liberal democracy. He believed that China was in the process of moving towards liberal reform and even stated that “Chinese competitiveness and expansionism on the world scene have virtually disappeared.”11 More than 30 years have passed since, but China remains an authoritarian communist state. If China becomes a leading superpower, liberal democracies of the world will have to accept that their system and philosophy of government are no longer the golden standards. The rise of China challenges the previous dominance of Western liberal democracies and poses a new model of governance based on Confucian values and authoritarianism. In speculating the unfolding of the relationship between China and the rest of the world, one may find it useful to revisit Samuel P. Huntington’s The Clash of Civilizations? As Fukuyama’s mentor, he suggested a different theory of international politics in response to The End of History. Huntington argued that the post-Cold War international conflict would be cultural, not ideological or economic.12 Despite rapid globalization, world civilizations have yet to overcome the fundamental differences: people within each civilization have different worldviews on “rights and responsibilities, liberty and authority, equality and hierarchy.”13 The concepts of rights, liberty, and equality that Western democracies hold dear might have an entirely different meaning to the people in China. This is not to say that the Western understanding of human nature is inherently better than the Confucian-rooted Chinese understanding of human nature. It only suggests that both sides should understand how the people on the other side think. To avoid potential clashes between Western and non-Western civilizations stemming from cultural misunderstandings, Huntington warns that the West will require “to develop a more profound understanding of the basic religious and philosophical assumptions underlying other civilizations.”14 Without it, a world where China is the leading superpower would be filled with violent conflicts stemming from cultural differences among nations. China in the past often resorted to coercive actions to force its will on neighboring countries as Schuman had noted. Before the era of mechanized warfare, a nation’s military power was measured by the number of soldiers it can mobilize. For centuries, the large scale of the Chinese population allowed China to maintain its military advantage over its neighbors. But the old methods of military action may not be as effective in modern days. Joseph S. Nye, one of the most influential scholars of international relations, wrote about the decline of military force as a measure of national power after the Cold War. In his article Soft Power, Nye asserted that “intangible power resources such as culture, ideology, and institutions” are becoming more important than coercive powers such as military and economic threats.15 The implication of Nye’s assertion is that a modern superpower cannot simply rule by brute force. As transnational, non-state actors expand their presence and the nature of warfare shifts away from conventional battles, the cost of coercive military actions increases. While a strong military and economy are necessary conditions to become a superpower, they alone are no longer sufficient. The cultural values represented by China and the Chinese people will be critical to the maintenance of its hegemony. The people of China should cultivate soft power to appeal to the rest of the world rather than resorting to aggressive military expansion—as in the South China Sea, for instance. Most importantly, the Chinese people will have to make decisions between the conflicting values of Confucian-traditionalist, Marxist-Leninist, and liberal-capitalist worldviews.

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For the people living outside of China, they must prepare themselves for a world where the dominant culture is no longer Western or liberal. At the same time, they must consistently try not to view China through the Western, liberal lens. Winston Churchill once called the actions of the Soviet Union “a riddle, wrapped in a mystery, inside an enigma.”16 Perhaps the same words could be used to describe China today. What the West Gets Wrong About China, an article published in the Harvard Business Review, mentions several misunderstandings of the West on China. One of them is that political reform in China does not necessarily mean “liberal reform.”17 The Chinese way of reaching political and social consensus may not seem rational to the West, but, in some ways, it brought China closer to becoming the next leading superpower. If Western countries, particularly the United States, continue to misread China and its intentions, cultural and military conflicts will inevitably ensue. In a speech delivered at the 19th National Congress of the Communist Party of China in 2017, Chinese President Xi Jinping proclaimed that the upcoming years will be “an era that sees China moving closer to center stage and making greater contributions to mankind.”18 Despite Deng’s denial of the Chinese ambition to become a superpower fifty years ago, China today is indisputably striving to become one. But as if he had foreseen this coming, Deng closed his remarks at the U.N. General Assembly with a piece of advice for the people of China and the world: “If one day China should change her colour and turn into a superpower…the people of the world should identify her as social-imperialism, expose it, oppose it and work together with the Chinese people to overthrow it.”19 Deng warned that China cannot reign as an imperialist superpower ruling with blood and iron. The words of Deng, Huntington, and Nye all suggest that it is essential for China to demonstrate magnanimity and cultivate soft power if China were to become a superpower. All things considered, whether China can become a leading superpower capable of peaceful world governance is a question that needs to be answered by the people of China.

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Notes 1.

Xiaoping Deng, “Speech By Chairman of the Delegation of the People’s Republic of China, Deng Xiaoping, At the Special Session of the U.N. General Assembly,” (speech, U.N., April 10, 1974), Deng Xiaoping Internet Archive, https://www.marxists.org/reference/archive/dengxiaoping/1974/04/10.htm

Deng, “Speech By Chairman.”

Dingli Shen, “Why China is New Pillar of the World,” Global Times, June 20, 2019, https://www.globaltimes.cn/content/1155110.shtml

William T. R. Fox, “The Super-Powers Then and Now,” International Journal 35, no. 3 (1980): 417.

Fox, “The Super-Powers,” 419.

Fox, “The Super-Powers,” 420.

“The Dollar: The World’s Currency,” Council on Foreign Relations, last modified September 29, 2020, https://www.cfr.org/backgrounder/dollar-worlds-currency

Michael Schuman, “What Happens When China Leads the World,” The Atlantic, October 5, 2020. https://www.theatlantic.com/international/archive/2020/10/what-kind-superpower-willchina-be/616580/

Schuman, “What Happens.”

10. Francis Fukuyama, “The End of History?” The National Interest, no. 16 (1989): 4. 11. Fukuyama, “The End of History?” 17. 12.

Samuel P. Huntington, “The Clash of Civilizations?” Foreign Affairs 72, no. 3 (1993): 22.

13. Huntington, “The Clash,” 25. 14. Huntington, “The Clash,” 49. 15. Joseph S. Nye, “Soft Power.” Foreign Policy, no. 80 (1990): 167. 16.

Alan Cowell, “Churchill's Definition of Russia Still Rings True,” The New York Times, August 1, 2008, https://www.nytimes.com/2008/08/01/world/europe/01iht-letter.1.14939466.html.

17.

Rana Mitter and Elsbeth Johnson, “What the West Gets Wrong About China,” Harvard Business Review, May, 2021, https://hbr.org/2021/05/what-the-west-gets-wrong-about-china.

18.

Jinping Xi, “Secure a Decisive Victory in Building a Moderately Prosperous Society in All Respects and Strive for the Great Success of Socialism with Chinese Characteristics for a New Era,” (speech, Beijing, October 18, 2017), Xinhua News Agency, http://www.xinhuanet.com/english/download/Xi_Jinping's_report_at_19th_CPC_National_Cong ress.pdf

19.

Deng, “Speech By Chairman.”

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Bibliography Cowell, Alan. "Churchill's Definition of Russia Still Rings True." The New York Times, Aug 1, 2008. https://www.nytimes.com/2008/08/01/world/europe/01iht-letter.1.14939466.html. Deng, Xiaoping. “Speech By Chairman of the Delegation of the People’s Republic of China, Deng Xiaoping, At the Special Session of the U.N. General Assembly.” Speech, U.N., April 10, 1974. Deng Xiaoping Internet Archive. https://www.marxists.org/reference/archive/dengxiaoping/1974/04/10.htm. Fox, William T. R. "The Super-Powers then and Now." International Journal 35, no. 3 (1980): 417436. doi:10.2307/40201883. http://www.jstor.org/stable/40201883. Fukuyama, Francis. "The End of History?" The National Interest no. 16 (1989): 3-18. http://www.jstor.org/stable/24027184. Huntington, Samuel P. "The Clash of Civilizations?" Foreign Affairs 72, no. 3 (1993): 22-49. doi:10.2307/20045621. http://www.jstor.org/stable/20045621. Mitter, Rana and Elsbeth Johnson. "What the West Gets Wrong about China." Harvard Business Review, May, 2021. https://hbr.org/2021/05/what-the-west-gets-wrong-about-china. Nye, Joseph S. "Soft Power." Foreign Policy no. 80 (1990): 153-171. doi:10.2307/1148580. http://www.jstor.org/stable/1148580. Schuman, Michael. "What Happens when China Leads the World." The Atlantic, Oct 5, 2020. https://www.theatlantic.com/international/archive/2020/10/what-kind-superpower-willchina-be/616580/. Shen, Dingli. “Why China is New Pillar of the World.” Global Times, June 20, 2019. https://www.globaltimes.cn/content/1155110.shtml. Siripurapu, Anshu. Council on Foreign Relations, Last modified September 29, 2020, https://www.cfr.org/backgrounder/dollar-worlds-currency. Xi, Jinping. “Secure a Decisive Victory in Building a Moderately Prosperous Society in All Respects and Strive for the Great Success of Socialism with Chinese Characteristics for a New Era.” Speech, Beijing, October 18, 2017. Xinhua News Agency. http://www.xinhuanet.com/english/download/Xi_Jinping's_report_at_19th_CPC_National_C ongress.pdf.

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Is Language an Indicator of Inclusion and/or Exclusion? A Historical Investigation Using Idioms of Catalan and Castilian Culture Author 1

Full Name

Shin, Irene Su Yeon

Seoul Foreign School

(Last Name, First Name)

School Name

ABSTRACT: The Spanish language is one of the most widely used languages in the world, not to mention that it also represents a source of great cultural heritage. There have been many disputes, however, regarding the inclusion and exclusion of the two distinctive Spanish languages, Catalán and Castilian. These two seem to show lots of differences in terms of inclusion and exclusion within their own culture. In the soccer industry, a rivalry match between two clubs FC Barcelona and Real Madrid called El Clásico illustrates this phenomenon; through fans’ extensive love for their respective club(s), the differences in the way in which these two languages indicate inclusion and exclusion can evidently be seen through the fan chants that they sing. The Catalan language, in fact, consists of extensive inclusive elements, which can mainly be seen through its use of pronouns in written forms of the language, while the Castilian language embeds both an inclusive and exclusive use of pronouns illustrated by the “Inclusive Language Controversy.” To understand the role of language, however, this paper will first detail regional conflicts in Spain in terms of the nation's history and then observe the inclusive and exclusive nature of the Catalan language both through language and linguistic differences and through various idioms of culture, notably soccer fan chants. As a passionate enthusiast of Spanish and its culture, I've observed that language not only is an indicator of inclusion and exclusion, but also that in such a modern world in which changes rapidly occur, it only comes down as a matter of time that a country will lose its significance in the international community if one country tries to undermine the languages that another country uses and increases conflict as means of including and/or excluding one another.

KEYWORDS: Inclusion, Exclusion, Language, Catalan, Castilian, Chants

225

,QWURGXFWLRQ “I Am Spanish… I Am Spanish!” One group of fans shout as loud as they can to the group of fans on the other side of the stadium. “We hate the Whites… We are from Barça until our death!” Another group of fans shout back with their own version of a proper counter-attack. As implied by the two names mentioned above, these are examples of fan chants by two of the most famous La Liga teams: FC Barcelona and Real Madrid. They are most well-known for their intense rivalry, known as “El Clásico.” The first group of fans are the Madridistas, fans of Real Madrid, singing “I Am Spanish” out loud to show their heartfelt nationalism towards the country. The second group of fans are FC Barcelona fans, singing “We hate the Whites”. As one of the main colors of the club is White, Barça fans are using this fan chant as a means of a response to the previous Real Madrid chant of “I am Spanish” by saying that Barça fans hate them, aggravating the rivalry. With fan chants as an example, the rivalry between the fans of the two teams is clearly more than just football fanaticism; it’s a representation of Spanish history and regional clashes. While there is no explicit cause that triggered the rivalry, it is plausible to say that the rivalry started because of their differences in symbolic characteristics. FC Barcelona has always been a symbol of Catalan nationalism, while Real Madrid has been the symbol of Spanish imperialism. More importantly, it is also helpful to look at the rivalry from a historical perspective: following the Spanish Civil War that occurred in 1920, Catalonia has been seen as a symbol of the ultimate “resistance” against the government, while Real Madrid was seen as a symbol of the actual government. In particular, General Francisco Franco’s role after the war was also a key factor in the creation of the rivalry. Following Madrid’s capture around the end of the Civil War, General Franco started to bring the nation together as a whole. During that process, Catalonia was the state that resisted against the republicans and maintained their Catalonian pride of being a state of their own, causing Franco’s hate towards them. As he started to use soccer as a means of propaganda for his new regime, the General started to interrupt all means of factors that could help Barça succeed and supported Real Madrid instead. Since he hated one team and loved the other, the difference in attitudes toward these two prominent teams from such an influential individual surely might have deepened the ongoing rivalry.

Objective As an avid Spanish geek from Korea, I’ve built my curiosity about the inclusion and exclusion of the Spanish language through extensive exposure to soccer fan chants while watching this eternal rivalry match, El Clásico. During this experience, I’ve noticed that the two teams use two different known Spanish languages that seem to factor in the differences in conveying messages of inclusion and exclusion to a great extent: Catalán and Castilian. This essay will place its focus on the Spanish language. To understand the role of language, however, it will first detail regional conflicts (ones resembles that of El Clásico) in Spain in terms of the nation’s history and observe the inclusive and exclusive nature of Catalán and Castilian Spanish both through language and linguistic differences and through various idioms of culture, or cultural artifacts.

Definitions of Inclusion and Exclusion Before approaching an answer to the prompt, it is important to arrive at a reasonable consensus with regards to how the 2 keywords inclusion and exclusion are defined. This essay will define the terms as follows: inclusion refers to “the state in which all types of people are included and are 226

WUHDWHG ZLWK HTXLW\ ZLWKRXW DQ\ PHDQV RI GLVFULPLQDWLRQ ´ DQG H[FOXVLRQ UHIHUV WR WKH ³VWDWH LQ ZKLFK FHUWDLQ JRRGV or rights are only given or only apply to a specific group of people.”

Regional Conflict in Spain The conflict between Central Spain and Catalonia first started after the Succession War ended in the eighteenth century, due to the disparity between political and economic power in the country. The discrepancy was that Castille had political and military power, but peripheral regions like Catalonia held economic power. Since Castille lacked economic power, it couldn’t assimilate cultures of former peripheral nations. Meanwhile, Catalonia emerged as an independent, powerful region armed with its strength, termed “Catalanism.” Catalonia mainly aimed to achieve self-government and wanted it to be considered a separate nation from Spain. In terms of politics, the democratic Constitution created in 1978 played a big role in aggravating the conflict between the two regions in some way. It first sought to create the “State of Autonomies” with the creation of an intermediate level of government with political power. It also distinguished nationalities and regions, as well as the two types of Autonomies, which led Catalonia to establish its own “Statute of Autonomy”, ultimately granting itself an autonomous government with a large budget and economic power, as well as a Parliament. In other words, the Constitution that was intended to end the problem of integration between the two regions worsened the conflict in a manner. Regional conflict in Spain is still an ongoing, controversial topic. Just like how cultural events such as the soccer fan chants above highlight, the forms of language between regions undergoing conflict play a significant role in the conflict, showing age-old divides that pull along so much history to it.

Castilian Spanish To provide more context about the language, as a starting point, Castilian is the more common Spanish language used by central and northern Spain as well as many countries from Latin America. It dates back to the Middle Ages when the kingdoms of Castile had been dominating Spain, allowing Castilian to become the primary language of the nation. For 700 years of its rule sharing the Iberian Peninsula with other Catholic kingdoms along with Islamic forces, the Castile kingdom brought many Basque soldiers, whose linguistic habits influenced the modern day Castilian Spanish. An example of such behavior would be silencing the pronunciation of the consonant “f”, turning words like fare, forno, and fungo to hacer, horno, and hongo. Following the unification of Spain in 1492, the Castilian language defeated Aragon, Galic, and Catalan, becoming the original source of the modern official Spanish language. When Christopher Columbus discovered the new continent in 1492, a significant number of Andalucian residents from Spain relocated to the new continent, America. And those who moved from Spain to America directly created the original pattern of modern Spanish official language even more. For example, residents from Andalucia influenced the tendency of pronouncing sounds such as “s”, “z”, “ce”, and “ci” all like “s”.

The “Inclusive Language” Controversy in Castilian Spanish Linguistically, the inclusivity and exclusivity of Castilian Spanish can be primarily seen through its use of pronouns in written forms of the language. The so-called “Inclusive Language” controversy surrounding the language sheds light on the use of masculine pronouns such as “nosotros” (“we”) instead of the feminine counterpart “nosotras”. The problem with this common use was that even in a group with 10 girls and 1 boy, for example, the plural form of “we” of the group will be called “nosotros”, even though there is only one boy and 10 girls in contrast. 227

Non-binary groups or LGBTQ+ advocacy groups are affected by this grammatical rule, too, not just women. Recently, those groups have proposed the replacement of the conventional masculine plural “os” with “-es” in spoken language and the symbol “@” or “x” in written language, which are all gender neutral. While the application of these symbols are becoming increasingly common, it is inevitable that the masculine plural dominates these alternative forms when naming the “we” form of a group with girls, boys, and non-binary individuals. The use of the masculine plural of the “we” form was originally adopted with an inclusive intention to include both genders, but a natural consequence of such wish was the discrimination of women and even non-binary individuals as well. The “Inclusive Language” controversy, therefore, is an example that shows both the inclusive and exclusive nature of the Castilian Spanish language, as the masculine plural ending “-os” originally is intended to be inclusive but inevitably is exclusive towards certain groups of people.

Real-Life Example: Real Madrid Chants One idiom of culture that shows the inclusive and exclusive nature of Castilian Spanish is soccer fan chants, which is a reasonable indicator of inclusion and exclusion through the form of spoken language. As soccer is one of the most popular sources of entertainment for Spaniards, football stadiums often get heated due to the tension between the opposing two teams and the fans’ aggressiveness towards certain behavior. Fan chants are a powerful way to unite all the fans of the club, and Real Madrid’s fan chants illustrate inclusion. One chant, titled “Que Viva España” that translates to “Long Live Spain”, is a core example of the inclusive nature that the Madridistas (Real Madrid fans) show. By referencing “Spain” instead of Madrid, which is the region the club is based, Madridistas show the intention of expressing their deep nationalism for the country they live in, not just Madrid, the capital. Adding on, another chant by the Madridistas show the exclusive nature of the club through their lexical choices. A chant titled “Yo Soy Español” illustrates such behavior, targeting fans of FC Barcelona and Catalan Nationalists in general. Following its independence, as Catalonia is its own state apart from the bigger nation of Spain, Madridistas are saying “Yo Soy Español”, which translates to “I am Spanish”, to express their heartfelt gratitude for Spain and to deliver the implied hatred towards Catalan nationalists, who are independent from Spain as a country and therefore someone who cannot be included in this chant of Spanish nationalism. More importantly, the chant “Yo Soy Español” carries a profound cultural significance. As Castilian Spanish is used in most regions in Spain such as its capital Madrid where Real Madrid is based (though other languages like Galician and Basque are still spoken in other regions), the language Madridistas use is naturally very exclusive, as it carries a sense of superiority in that they are from a region where Castilian Spanish, perhaps the most valuable language in Spain, is spoken at its finest. It is also held true that more prestigious universities in most regions of Spain use Castilian than any other language, which adds to the Madridistas’ pride and sense of superiority.

Catalán Spanish By contrast, Catalán is a language that started being used anytime between the eighth and tenth centuries primarily in Catalonia, a region of Spain. It also bears great resemblance to French spoken by the nearby country, as it was descended from the Vulgar Latin dialects, rendering languages such as French and Spanish (including Catalan) types of Romance languages. Today, both Castilian and Catalan Spanish are used in the region of Catalonia, which is known for its citizens’ extensive nationalism; the word

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“Catalanism” encapsulates this tendency. More importantly, the term includes a sense of “separatism”, which implies the exclusive nature of Catalan nationalists.

Inclusion in the Catalan Language: Pronoun Usage However, contrary to what Castilian Spanish has shown, the Catalan language, in fact, consists of extensive inclusive elements, which can mainly be seen through its use of pronouns. While Castilian Spanish kept its use of the masculine plural “-os” that posed a problem when dealing a group with lots of girls and one boy, Catalan uses the respective endings “-x” and “-i” when referring to a group of large people (that is, to include non-binary groups). These two usages of gender-inclusive pronouns have originally been proposed in Castilian Spanish as well, but haven’t been necessarily fixed into the language formally. An example of usage of such pronouns would be referring to a large group of people as “they”. In written language, Catalans use the ending “-x” more, so “they” would turn out to be “ellx” instead of Castilian “ellos”. Similarly, in spoken language, Catalans would refer to “they” as “elli”. The incorporation of these “-x” and “-i” endings was proposed by individuals from the non-binary group, and it renders the language much more inclusive as non-binary groups as well as women could all be included in the naming of “elli” and “ellx” in spoken and written language respectively.

Real-Life Example: FC Barcelona Chants Similar to the Madridistas’ fan chants, the Culés’ (name for Barça fans) fan chants actually demonstrate more exclusion of their own than inclusion in opposition to the inclusion shown by the use of pronouns. A chant titled “Isla Cataluña” illustrates this phenomenon: the lyrics of the chant are “Isla Barça, Isla Cataluña” (with “Isla” translating to “Island”), which are repeated several times. Here, the Catalonian pride is evidently shown through implementation of the word “Isla”, which signifies isolation from all the other regions of Spain. It is true that inclusion is shown here amongst the Catalan residents, especially since Catalonia is now a region in which both Catalan and Castilian Spanish are spoken and the residents take a lot of pride in that the region in which they live is the only region in Spain that speaks these 2 languages. However, the inclusive nature amongst the Catalans in fact makes the language in the chant more exclusive, since it is only themselves that can rejoice the lyrics of the chant with pride. Another chant titled “Lo Lo Espanyol” is yet another illustration of Catalonian exclusion as the lyrics “P*ta Espanyol” (“F**k the Spanish”) show. This Barça chant is both an indication of Catalonian pride, which mainly comes from the fact that Catalan is a language of its own that signifies uniqueness, and an offense to the Madridistas’ chant “Yo Soy Español”. By insulting the Madridistas’ Spanish pride directly through language, the Culés are implying that Catalan is of as equal importance as Castilian Spanish, and are pointing out Real Madrid’s exaggerated sense of superiority that they are “Spanish” speaking the language (Castilian) that is spoken most frequently in the nation.

Is language a powerful indicator of inclusion and exclusion? Indeed, language is a powerful indicator of inclusion and/or exclusion, especially because language is used on an everyday basis and is inevitably essential for daily communication. Adding on, language is evidently more objective than images, artworks, or any other cultural artifacts that come with various interpretations that differ between individuals. It is true that in some cases visual forms of representation can provoke a more profound sense of inclusion and exclusion, but it is not as direct as the impression spoken (and even written) language gives, like the straightforward, insulting diction that the two groups of soccer club fans show above through an essential idiom of culture: soccer fan chants.

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Conclusion Following my personal experience after traveling to cities in Spain like Madrid, Barcelona, Seville, Cádiz, and Gibraltar, I came to gradually realize the diversity of Spanish history each visit. The distinctiveness of each region gave me the feeling that I was in a different country every time, reminding me of the strong significance of the usage of different languages. As a passionate enthusiast of Spanish and its culture, I’ve observed that in such a modern world in which changes rapidly occur, it only comes down as a matter of time that a country will lose its significance in the international community if one country tries to undermine the languages that another country uses and increases conflict as a means of including and/or excluding one another. Rather than the tendency to exclude one another as a result of distinct regional and cultural characteristics, it would be desirable if countries could embrace and respect the uniqueness that comes with those differences, which can continue futuristic developments in history.

References 1) RAMANI, SRINIVASAN. "El Clasico: The Battle of Contrasts: The Eternal Rivalry between Football Clubs FC Barcelona and Real Madrid Is Gripping." Economic and Political Weekly, vol. 48, no. 42, 2013, pp. 87–88. JSTOR, http://www.jstor.org/stable/23528585. Accessed 17 June 2023. 2) Castells, Antoni. « Catalonia and Spain: Political and Fiscal conflict », Pôle Sud, vol. 40, no. 1, 2014, pp. 59-80. 3) “Castilian of Spain.” Encyclopædia Britannica, www.britannica.com/place/Spain/Castilian. Accessed 24 July 2023 4) “Spanish History of Literature.” Naver Blog | m.blog.naver.com/PostView.naver?isHttpsRedirect=true&amp;blogId=franca1997&amp;logN o=221483109488. Accessed 24 July 2023. 5) Staff, MND. “Inclusive Language a Controversial Issue among Linguists.” Mexico News Daily, 4 Sept. 2021, mexiconewsdaily.com/news/inclusive-language-a-controversial-issue-among-linguists/. 6) Cho, Hyejin (2009). “The Catalonian Policy for Language Unification and the Changes of Sociolinguistic Aspects.” Europe Research Journal, 15 August 2009. 7)

Duarte, J. (2022). Catalan. Gender in Language Project. www.genderinlanguage.com/catalan

8) “‘Isla Cataluña’ - Barcelona Fanchants.” FanChants, www.fanchants.com/football-songs/barcelona-chants/island/. Accessed 26 July 2023. 9) “‘Lo Lo Espanyol’ - Barcelona Fanchants.” FanChants, www.fanchants.com/football-songs/barcelona-chants/lo-lo-espanyol/. Accessed 26 July 2023.

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A Case Study on the Conflict of International Trade between U.S. and China: Focusing on the Advanced Technology Author 1

Full Name

Shin, Phil Gyu

HPrep Academy

(Last Name, First Name)

School Name

ABSTRACT This research is focused on the conflict in international trade between the U.S. and China (Huawei) due to advanced technology. The conflict between the state and China started because of National security and Technical standard issues. To specify, we focused on the famous IT innovation company Huawei to examine its relationship with the U.S. On July 18, 2018, the United States began to attack China by imposing 25% retaliatory tariffs on 818 Chinese imports worth $34 billion. This eventually caused China to attack the U.S. by imposing 25% retaliatory tariffs on American agricultural, automotive, and marine products imported into China. This began the trade war, and over the next couple of years, many cases between the U.S. and China still affect our current world. This study used case studies to gather relevant data on U.S. policy toward China, which was listed from the oldest to the most recent dates.

KEYWORDS: High Technology, Huawei, Conflict, Trading, Legal Issues, U.S. Department of Commerce

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პ ,QWURGXFWLRQ Advanced technology, or modern technology, is a developing IT innovation that promises to provide the future and improve human life. The U.S. and China have a growing impact on the global economic relationship. With advancements come more products, resulting in higher sales rates. Proving this logistical benefit is the purpose of the research paper by creating economic benefits on both sides of the country. However, such agreements do not only create benefits; they can also create disruptions in trade relations. According to imf.org, Trade tensions between the United States and China have negatively affected consumers and manufacturers in both countries. With such issues, it is predicted that trade conflict between the U.S. and China may hold severe consequences, as proven by the research at ssrn.com, which declared that the 2018 outbreak of the rapidly escalating trade war between the United States and China was a watershed event that was reshaping the global economic and political order. Specifically, Huawei, a famous IT company, has an international trade conflict with the U.S. over technical standards. This eventually led to U.S. sanctions on China, preventing them from doing business. Therefore, we must conduct a professional case study to discover the components that most affect the trade relationship between the U.S. and China. The purpose of this research will be to determine the main components of the technological sphere that have caused the U.S.-China trade conflict. For this type of research, it would be most appropriate to use the case study method because it will collect relative data on the effects of Huawei on the U.S.

ჟ 'LVFXVVLRQ %DFNJURXQG RU /LWHUDWXUH 5HYLHZ 1. Discussion Background On July 6, 2018, the United States began to attack China by imposing 25% retaliatory tariffs on 818 Chinese imports worth $34 billion. In response, China began imposing 25% retaliatory tariffs on American agricultural, automotive, and marine products imported into China. As the trade war progresses, China's damage gets worse. The move comes as Donald Trump accepts the Peter Navarro National Trade Commission's "Trade Security Theory." Trade security theory is the logic that views a country as an enemy of a country that sees a trade deficit if one country continues to create a trade surplus in another country. The logic is that if a particular country continues to create a trade surplus in another country, it will economically invade a country with a trade deficit. Putting this logic in the case of the United States, it is natural that the United States would respond to such economic aggression because countries with a trade surplus with the United States become enemies of the United States. A trade war is one in which the United States is determined to weaken public opinion on the international stage and reduce its economic power before China develops further. The reason China responded to the U.S. for not backing down was that if it did, it would have to accept all the terms of market opening offered by the U.S, which would mean the failure of the Chinese dream, the agenda of the Xi Jinping regime, and the end of the Xi Jinping regime. - Chinese Communist Party dictatorship. The trade war that subsided after the G20 summit flared again on August 5, 2019, when the US announced its intention to retaliate with additional tariffs. Stock markets worldwide, including the KOSPI, Nikkei, Dow, and Shanghai, plunged on the same day. A business in China by the name of Huawei is well-known as a top supplier of ICT infrastructure and intelligent products on a global scale. The U.S. government's sanctions on Huawei, which began in May 2019, are gradually increasing its intensity. As a result, the supply chain of major related industries such as global semiconductors, smartphones, and displays is changing, and the resulting risks are becoming a reality, so we will examine the contents of additional sanctions measures that took effect recently and their market impact—the U.S. Commerce Department's sanctions against Huawei. The first round of dates for the announcement of the sanctions was April 15, 2019. When supplying semiconductors produced in the U.S. to Huawei, it is required to obtain approval from the U.S. government. The second

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round was on May 15, 2020. Even semiconductors produced in third countries are commissioned to produce products ordered and designed by Huawei. If U.S. equipment, design, and software technology are used to produce the products, they will be approved by the U.S. government. The third round was on August 17, 2020. If all semiconductors use U.S. equipment, design, and software technology are supplied to Huawei and its affiliates, they will be approved by the U.S. government. The first sanctions imposed in 2019 required that U.S. companies that supply semiconductors to Huawei obtain permission from U.S. authorities. As a result, Google, Intel, Qualcomm, ARM, Micron, and Facebook announced the suspension of transactions with Huawei, and Huawei's parts suppliers changed as follows. However, even after the first sanctions, the second ones were announced in May 2020 following the analysis that the sanctions were ineffective because only products produced in the U.S. were imposed, with Huawei's total sales increasing by 19.1% year-on-year in 2019. It is known that Huawei has been focusing on securing semiconductor inventory before September 15, 2020, facing the crisis of blocking the semiconductor supply and demand source. However, it cannot be ruled out that Huawei's smartphone and communication equipment businesses will be suspended if all the semiconductor supplies secured are exhausted. Unless Huawei makes semiconductors with Chinese technologies and equipment without U.S. technology, it will be difficult to avoid the sanctions, and the semiconductor sector will not be able to stand on its own in a short period, as it needs to spend a lot of time and money on technology development. "Unless the U.S. takes separate easing measures, there are few areas in the semiconductor field that do not include U.S. original technology or intellectual property rights, so Huawei's global position will weaken significantly," said an engineer at a U.S. semiconductor company (Yonhap News, 2022).

2. Literature Review In studying the technology war between the United States and China, the United States considers itself highly ethical in the existing international order. It intends to force China to abandon its policies in these industries. High technology transfer from foreign companies to maintain its global supremacy. With a zero-sum mentality, by studying the technology war between the United States and China, the United States finds itself highly ethical in the existing international order. He intends to force China to abandon its policies in these industries. High technology is a transfer from foreign enterprises to maintain global hegemony. With a zero-sum mentality, the Trump administration is leveraging advanced science and technology to maximize the benefits for the United States in trade with China. Technology war efforts against China mainly include trade sanctions, investment controls, export controls, and restrictions on exchanging technology personnel. These measures will further harm the security relations and scientific and technological cooperation between China and the United States and jeopardize the regional situation and global governance of science and technology. To promote sustainable global development and strategic stability, the two sides need to establish a balanced and mutually beneficial relationship in high-tech industries and expand the space for cooperation in science and technology governance and global technology. More effective efforts to manage their strategic competition and build more (Haiyong Sun, 2019). This report analyzes the growing technology war between the United States and China and its impact on the global semiconductor industry. To answer questions about government interventions and protectionist policies and their impact and influence on behaviors in the semiconductor value chain. The author defines and expands on an emerging story to contextualize the US-China tech war. "Technical Nationalism." The United States and China are in the early stages of a historic technology war or an era of technical nationalism. Technocratic nationalism is a new trend in mercantilism that directly links technological innovation with a country's economic prosperity, social stability, and national security policies. In this sense, market intervention by the government is seen as a defense against opportunistic or adversarial non-state players and governments. In 2018, global sales of semiconductors and related technologies exceeded $468 billion. The Chinese semiconductor market is

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by far the largest importer in the world. Semiconductor-related technologies are China's top import, even surpassing oil imports. As this study will reveal, China almost entirely depends on US and foreign companies to meet its IC needs, either as imports or as foreign manufacturers outside China's domestic market (Alex Capri, 2020).

რ &DVH 6WXG\ 8 6 96 +XDZHL Discussion

Figure 1: Time Series of the conflict between the U.S. and China

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October 2012 ‘Raising potential security threats ZLWK +XDZHL ¶ June 2017 ‘Enforces National LQWHOOLJHQFH ODZ ¶

August 2018 ‘Defense $XWKRUL]DWLRQ $FW¶ January 2019 ‘Stop using ZTE HTXLSPHQW ¶ May 15, 2019 ‘Permission from U.S. authorities

May 15, 2020 ‘Stop trading with +XDZHL ¶

Huawei's information leakage and security threats surfaced in the wake of the publication of a report by the U.S. Congress that Huawei's communication equipment was used for spying by the Chinese government in 2012.

Since then, the Chinese government has enacted the "National Intelligence Act," which allows it to monitor individuals or organizations in its own country and abroad, further spreading information security concerns worldwide. Under the bill, Chinese intelligence agencies could install wiretapping and surveillance devices on vehicles, communication equipment, and buildings owned by individuals and organizations or search for information without command. In other words, this means that even if Huawei hides back doors in equipment supplied to overseas telecommunications companies or government offices and intercepts them by Chinese intelligence agencies, it will not be a problem under the "National Intelligence Act." The president, Donald Trump, signs the Defense Authorization Act, Banning Huawei and ZTE Equipment. By passing the National Defense Authorization Act, public institutions banned the use of products such as Huawei and ZTE to expand it to private companies. In addition, it strongly urges the EU to exclude Huawei equipment from the 5G network construction project. The U.S. House of Representatives has proposed a bill with Huawei to stop using ZTE equipment. The U.S. federal prosecutor is conducting a criminal investigation into Huawei over alleged technology theft. President Donald Trump signed an executive order banning Chinese telecom equipment manufacturers from using it. To supply semiconductors produced in the U.S. to Huawei, it is required to obtain approval from the U.S. government. The first sanctions imposed in 2019 required that U.S. companies that supply semiconductors to Huawei obtain permission from U.S. authorities. As a result, Google, Intel, Qualcomm, ARM, Micron, and Facebook announced the suspension of transactions with Huawei, and Huawei's parts suppliers changed as follows. The second round of sanctions was announced in May 2020 following the analysis that the sanctions were ineffective because only products produced in the U.S. were imposed, with Huawei's total sales increasing 19.1% yearon-year in 2019. The second sanction aimed to remove the link between Taiwan's TSMC and Huawei, the world's largest semiconductor foundry company, separating TSMC from China's supply chain and incorporating it only into the US supply chain. TSMC's semiconductor manufacturing process requires products from Applied Materials, a U.S. semiconductor equipment manufacturer. As a result of the measure, TSMC announced that it would stop trading with Huawei and build a state-of-the-art semiconductor plant in Arizona, the U.S., actively responding to the Trump administration's supply chain de-Chineseization policy. Huawei has independently developed smartphone computing devices (APs) and semiconductors exclusively for 5G base stations through its subsidiary HiSilicon. Still, manufacturing has relied entirely on TSMC, so it is expected to be struck by the measures.

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August 17, 2020 ‘Ordered and designed by +XDZHL ¶

All semiconductors using U.S. equipment, design, and software technology are supplied to Huawei and its affiliates and will be approved by the U.S. government. The condition "ordered and designed by Huawei" was deleted in the third round of sanctions. In other words, even if Huawei was not designed, U.S. technology should only be used in some semiconductors supplied to Huawei. In the process of semiconductor development, EDA is essential. U.S. companies such as Cadence Design Systems and Synopsys have leading technologies in this field. U.S. companies' share of semiconductor manufacturing equipment such as Applied Materials, ASML, and Ram Research is overwhelming. Experts say the U.S. has shown its willingness to fundamentally block transactions of all system semiconductors, including bypass supply, after Huawei was in charge of semiconductor design and development through fabless companies MediaTek and Unisoc in Taiwan. )LJXUH 7LPH VHULHV RQ 8 6 SROLF\ WRZDUG +XDZHL

Bloomberg reported that Huawei, China's largest telecommunications equipment company, which the US government has sanctioned because of national security threats, is trying to circumvent regulations related to the US government's relationship using an unspecified startup. The sources added that the company plans to start semiconductor production in the first half of next year and will supply nearly all of its products to Huawei. PXW's website shows it plans to increase its production capacity of semiconductors such as cars and smartphones by 20,000 wafers by 2025. If such a plan goes smoothly, Huawei can circumvent US government regulations effectively. PXW will not be able to have the same production capacity as Taiwan's TSMC, the world's largest foundry (semiconductor trust manufacturing) company that once supplied Huawei with semiconductors, but it will help Huawei get out of the United States rules in the field of smartphones and servers. However, it has been confirmed that the US Department of Commerce's Bureau of Industrial Security (BIS) has noticed the recent actions of Huawei and PXW. The BIS is an organization that regulates exports and re-exports to organizations and individuals that raise reasonable suspicions that they are contrary to the national security and foreign policy of the United States. The BRI said it is aware of suspicions that PXW and Huawei are related to Bloomberg and will take administrative and legal action to remedy sanctions violations if necessary. Meanwhile, the Joe Biden administration will announce new restrictions targeting China. Among them, it is expected to affect cases like PXW as it includes further tightening regulations for semiconductor technology that can be exported to China. However, if US technology is included in the new regulations, it is known that exports could be prevented. The US Commerce Department has proposed new regulations allowing cooperation on "technical standards" between Huawei and sanctioned US companies. Reuters reported on the 6th that the Commerce Department had prepared regulations allowing US companies to participate in technology standards organizations related to Huawei as members and are in the review stage. In May 2020, the Trump administration blacklisted Huawei for national security reasons, requiring American companies to get permission first to make transactions like exports. As a result, American companies need more certainty about whether they can share technology and information with Huawei. The US company has stopped contacting Huawei about 5G technology standards. American companies have pointed out that the sanctions against Huawei have disadvantaged the US regarding 5G technology standards. Six senators, including Representative Mark Rubio, sent letters to the Commerce Department, State Department, Defense Department, and Energy Department last month calling for sanctions against Huawei and others, not limited to Huawei, to restrict their participation in US 5G technology standards.

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ს ([SHFWDWLRQV The expectations for future U.S. and China relations will not be positive because, according to BBC.com, the US government has ceased accepting licenses for American businesses to sell most of their goods to the Chinese technology giant Huawei. It happens as the Biden administration keeps tightening the laws governing US technology exports to China. This recent article shows the current relationship between the U.S. and China, in which Biden is strengthening the laws to stop trade because of technical standards and national security issues. If this conflict continues, it is likely for the Huawei company to have a more difficult time than the U.S. Due to the country's more developed modern technology. There’s a high possibility of the state surviving the conflict in the future rather than Huawei.

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References Analysis Team FX. "The U.S. Department of Commerce, U.S. companies..."Technology can be disclosed to Huawei to develop international technology standards." Nanum Trading, 16 June 2020, www.nanumtrading.com/%EB%AF%B8-%EC%83%81%EB%AC%B4%EB%B6%80-%EB%AF%B 8%EA%B5%AD-%EA%B8%B0%EC%97%85-%EA%B5%AD%EC%A0%9C%EC%A0%81-%EA %B8%B0%EC%88%A0-%ED%91%9C%EC%A4%80-%EA%B0%9C%EB%B0%9C-%EC%9C%8 4%ED%95%B4-%ED%99%94/. Accessed 3 Aug. 2023. BBC News. “Huawei Sues US Government over Product Ban.” BBC News, 7 Mar. 2019, www.bbc.com/news/business-47478587. Accessed 3 Aug. 2023. Berman, Noah, et al. “Is China’s Huawei a Threat to U.S. National Security?” Council on Foreign Relations, 8 Feb. 2023, www.cfr.org/backgrounder/chinas-huawei-threat-us-national-security. He was accessed on 3 Aug. 2023. Ciuriak, Dan. “The US-China Trade War: Technological Roots and WTO Responses.” SSRN, Global Solutions Journal 4, 24 Feb. 2019, papers.ssrn.com/sol3/papers.cfm?abstract_id=3330392. Accessed 3 Aug. 2023. "Huawei/Controversy - Namuwiki."Namu.wiki, name.wiki/w/%ED%99%94%EC%9B%A8%EC%9D%B4/%EB%85%BC%EB%9E%80. Accessed 3 Aug. 2023. International banker. “Have the Huawei Bans Achieved the US’ Intended Goals?” International Banker, 7 Sept. 2022, internationalbanker.com/technology/have-the-huawei-bans-achieved-the-usintended-goals/. Accessed 3 Aug. 2023. Kapustina, Larisa, et al. “US-China Trade War: Causes and Outcomes.” US-China Trade War: Causes and Outcomes, vol. 73, 2020, www.shsconferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01012.pdf, https://doi.org/10.1051/shsconf. Keane, Sean. “Huawei Ban Timeline: Detained CFO makes a deal with US Justice Department.” CNET, 30 Sept. 2021, www.cnet.com/news/privacy/huawei-ban-timeline-detained-cfo-makes-dealwith-us-justice-department/. Accessed 3 Aug. 2023. KOTRA. "Trade and Regulation - KOTRA Overseas Market News." Trade and Regulation - KOTRA Overseas Market News, 12 Oct. 2020, dream.kotra.or.kr/kotranews/cms/news/actionKotraBoardDetail.do?SITE_NO=3& NU_ID=90&CONTENTS_NO=1&bbsGbn=244&bbsSn=244&pNttSn=185142. Accessed 3 Aug. 2023. Miller, Monica. “Tech War: Biden Moves to Halt US Exports to Huawei, Reports Say.” BBC News, 31 Jan. 2023, www.bbc.com/news/business-64461877. Accessed 3 Aug. 2023. Sangbae Kim. "The Huawei Crisis and the Competition for U.S.-China Technology Hegemony." International Regional Studies Vol. 28, No. 3, Professor of Political Science, Seoul National University, 5 Aug. 2019, www.sangkim.net/huawei.pdf. Accessed 3 Aug. 2023. Steinbock, Dan. “U.S.-China Trade War and Its Global Impacts.” China Quarterly of International Strategic Studies, vol. 04, no. 04, Jan. 2018, pp. 515–542. Worldscientific,

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www.worldscientific.com/doi/pdf/10.1142/S2377740018500318, https://doi.org/10.1142/s2377740018500318. "[S&T GPS] Major global countries' moves around Huawei, the center of security controversy." Now.k2base.re.kr, 10 Feb. 2019, now.k2base.re.kr/portal/trend/mainTrend/view.do?poliTrndId=TRND000000 000035684&menuNo=200004. Accessed 3 Aug. 2023. Thrush, Glenn, and David McCabe. “Justice Dept. Charges 2 Chinese Citizens with Spying for Huawei.” The New York Times, 24 Oct. 2022, www.nytimes.com/2022/10/24/us/politics/justice-depthuawei.html. Accessed 3 Aug. 2023. www.etnews.com. "[International] U.S. Considers Allowing 5G "Technical Standards" Cooperation With Huawei." Newspapers Looking Into the Future - Electronic Newspapers, 7 May 2020, www.etnews.com/20200507000286. Accessed 3 Aug. 2023. Yonhap News. "China Huawei attempts to bypass U.S. semiconductor regulations using unknown startups" - trade news." Korea International Trade Association, 7 Oct. 2022, www.kita.net/cmmrcInfo/cmmrcNews/cmercNews/cmercNewsDetail.do?pageIndex=1&nIndex=1827 333. Accessed 3 Aug. 2023.

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Relationships between Different Types of Childhood Neglect and Personality Characteristics

Author 1

Full Name

Sim, Yeji

United World College South East Asia East campus

(Last Name, First Name)

School Name

ABSTRACT: Childhood neglect, a form of child abuse, has developmental impacts even in adulthood. This study investigated whether childhood neglect led to different personality characteristics in young adults. An online survey was conducted with 39 young adults to measure the extent of their childhood neglect experiences. They retrospectively responded to 100 neglect scenarios, which indicated one of five neglect types (emotional, inadequate supervision, physical, educational, and medical neglect). To examine respondents’ personality characteristics, the MBTI (Myers-Briggs Type Indicator) test results were obtained. Correlation analyses were conducted on the level of neglect experiences and relative strengths of the MBTI personality characteristics (Extraversion (E) vs. Introversion (I), Intuition (N) vs. Sensing (S), Thinking (T) vs. Feeling (F), Judging (J) vs. Perceiving (P), and Assertive (A) vs. Turbulent (T)). People who reported higher levels of neglect in childhood showed higher percentages of “S” than “N, ” “P” than “J,” and “A” than “T” characteristics. The E/I and T/F characteristics showed no correlation with neglect. Emotional neglect and inadequate supervision showed the strongest correlations with the strength of personality characteristics. This study provides insights into personality aspects that may be influenced by parental neglect. Stronger formation of personality characteristics was examined in some personality characteristics, which depicted “reliance on reality-based sensing,” “able to make impromptu judgements and less planned,” and “self-assertive, independent, and less turbulent to external stimuli.”

KEYWORDS: Child Abuse, Childhood Neglect, Personality

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INTRODUCTION Parental neglect, a form of child abuse, is defined as a failure in providing basic needs for a child. Basic needs provided by a caregiver includes food, shelter, healthcare, and emotional support. While parental neglect is often overshadowed by more visible acts of violence, child neglect was the most prevalent form of child abuse since its boundaries and types are under-recognized. The Children’s Bureau of the U.S. Department of Health and Human Services categorized neglect into five basic categories: emotional (lack of words and acts of affection or exposing a child to domestic violence), inadequate supervision (lack of appropriate care, guidance, and protection), physical (failing to care for hygiene, clothing, nutrition, or shelter), educational (failing to provide educational needs or not enrolled in or skipping school), and medical (denying or delaying necessary or recommended medical treatment). Parental neglect in childhood led to profound physical, emotional, and cognitive consequences that influenced the child, even till adulthood. Erickson et al.(Erickson & Egeland, 2002; Erickson et al., (1989) demonstrated that children with emotional neglect were socially withdrawn and showed an inability to adequately cope with challenging interpersonal situations. Such cognitive influences were also reported years later (Herrenkohl et al., 1991). Recent studies suggested that childhood neglect also impacted the formation of personality traits. Ajake et al. (2009) examined the relationship between child neglect and introversion-extroversion and found that students exposed to neglect were more likely to be introverted than those who did not experience abuse. The negative impacts of childhood neglect have been widely studied. However, the effects of such maltreatment on the formation of personality traits opened a new discussion, since personality characteristics cannot be determined to be “positive” or “negative.” This study focused on the impact on personality development and examined the relationship between different categories of neglect and different personality characteristics. Importantly, unlike previous studies that allocated categories by all-or-none determinations, this study examined the correlation in greater depth based on a linear quantification of the degree of childhood neglect experiences and relative strengths of personality characteristics. Furthermore, considering the broadness and complexity of neglect circumstances, this study measured the level of neglect in five different categories. Moreover, this study expanded the variety of personality traits measured and adapted those defined by the Myers-Briggs Type indicator (MBTI; Briggs-Myers & Briggs, 1985) test. The MBTI categories examined introversion (I)/extroversion (E) and four other competing pairs: intuition (N)/sensing (S), thinking (T)/feeling (F), judging (J)/perceiving (P), and assertive (A)/turbulent (T). The MBTI test defined the paired characteristics as competing, and thus measured the relative strengths of the characteristics in percentages (e.g., 73% of E and 27% of I characteristics). The I-E dimension reflected whether one’s attitude towards the world was actively oriented outward toward other persons and objects (E) or internally oriented (I) (Sipps & Alexander, 1987). The S-N dimension reflected attending to real information based on sensory stimuli (S) or a detached analysis of events from associations and possibilities (N). The T-F dimension measured logical reasoning and objective decisions (T) versus subjective and interpersonal approaches based on human values and motives (F). The J-P dimension dissociated from preferring planned and organized disclosures (J) or spontaneous and adaptable open options (P). Finally, the A-T dimension measured the relationship between being self-assured and resistant to turbulence (A) and success-driven and anxious (T). This study exploited the categories of the MBTI test results to examine the degree to which each characteristic is shown in each individual. In this study, the level of neglect experience in the five neglect categories and strengths of the five personality characteristics were collected through an online survey. Responses were converted into quantified scores based on the six neglect scores (Emotional Neglect, Inadequate Supervision, Physical Neglect, Educational Neglect, Medical Neglect, and Total Neglect scores) and five personality characteristics scores (E-to-I, N-to-S, T-to-F, J-to-P, and A-to-T scores). Correlation analyses were

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conducted between neglect and personality characteristic scores to investigate the relationship between childhood parental neglect and personality traits.

METHODS Participants. Participants aged 18–25 years, classified as young adults, were recruited. In total, 39 (M = 22.62; female = 29) completed the survey. All participants were informed of the data collection and usage and voluntarily provided consent to participate. Participation was anonymous. Stimuli. An online survey was conducted. The survey consisted of two parts: “Neglect” and “MBTI” sections. The Neglect section comprised 100 statements that measured each participant’s experience of neglect during childhood. Each statement indicated an experience (scenario) of childhood neglect, or the opposite. As the range and indicators of child neglect were broad, the questionnaires of neglect were organized into five different domains: “Emotional,” “Inadequate Supervision,” “Physical,” “Educational,” and “Medical Neglect.” These were based on a prior study that provided a conceptual model of child neglect (Dubowitz et al., 2005). The five domains were measured in an independent section of the survey that consisted of 20 questions each. Some exemplary questions for neglect were: Ř

Emotional: “I often felt lonely even in situations where my caretaker was present”

Inadequate Supervision: “My caregivers were always within reach when I went outdoors”

Physical: “My caregiver cared about my daily nutrition”

Educational: “My caregiver seemed uninterested in my learning progress”

Medical: “I felt my caregivers often brushed off my medical needs and did not take them seriously”

The MBTI section collected five personality characteristics. The section included a link for a “16personalities” test (https://www.16personalities.com/free-personality-test), a simplified online version of the MBTI (Myers-Briggs Type Indicator) personality test. The five personality characteristics were Introversion vs. Extroversion, Intuition vs. Sensing, Feeling vs. Thinking, Perceiving vs. Judging, and Assertive vs. Turbulent, as categorized by the Official MBTI. “E-to-I,” “N-to-S,” “T-to-F,” “J-to-P,” and “A-to-T” scores were calculated as a means to examine how strong one characteristic was in competence with the other (e.g., E-to-I score 25% means 25% Extrovert and 75% Introvert). Procedure. The survey first presented a short overview of the research and its purposes and reiterated the ethical considerations. After the participants clicked on the informed consent to participate, anonymous responses were collected regarding the participants’ age and gender. After this section was completed, the participants completed the survey questionnaires, First, the Neglect section comprised 20 statements per subsection, which was 100 statements in total. Participants clicked the answer that resonated with them the most within the six indicator bar provided underneath each question. These measured how well participants agreed with the provided statement. The farthest ends of the indicator bars were “strongly disagree” (left) and “strongly agree” (right). All questions had to be answered in order to proceed to the next section. After the neglect questionnaire were completed, the MBTI section was presented. First, instructions were presented and guided participants on how to screenshot and attach the MBTI results. A guideline image was provided along with the instructions. Subsequently, the test link for the modified MBTI test (16 personalities) was provided. After the MBTI test was completed, participants had to screenshot the result images. In total, participants had to submit six screenshots. Each included the “main result page (e.g. INFJ-T),” “E vs. I,” “N vs. S,” “T vs. F,” “J vs. P,” and “A vs. T percentages.”

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Data Analyses. All 39 participants successfully completed the survey and were included. Since the statements in the neglect section included both the indication of neglect and non-neglect, each response (1-strongly disagree to 6-strongly agree) for the 100 statements was adjusted to the same polarity so that a higher response score (e.g., 6) indicated a higher level of neglect experience. Subsequently, the neglect scores were calculated for each participant after the adjusted response scores were added. Accordingly, the total score was 120 for each of the five categories of neglect. Total Neglect Score was calculated for each participant after five neglect scores were added, with the total score of 600. For the MBTI personality characteristic scores, the percentage numbers for each characteristic were recorded from the participants’ screenshot images. Therefore, five personality characteristic scores, Eto-I, N-to-S, T-to-F, J-to-P, and A-to-T scores, were collected for each participant. To examine any correlation between the level of childhood neglect experiences and personality characteristics, correlation analyses were conducted between the neglect scores (Emotional, Inadequate Supervision, Physical, Education, Medical, and Total Neglect Score) and personality characteristic scores (E-to-I, N-to-S, T-to-F, J-to-P, and A-to-T scores). Consequently, 30 correlation analyses were conducted.

RESULTS Total Neglect Scores The Mean Total Neglect score of the 39 participants was 119 out of 600, with a minimum and maximum score of 23 and 344, respectively. The standard deviation was 81. The Total Neglect score demonstrated significant correlations with N-to-S, J-to-P, and A-to-T scores. Participants with higher total Neglect scores depicted personality characteristics of S more than N (r = -0.267, p = 0.05), P more than J (r = -0.296, p = 0.034), and T more than A (r = -0.25, p = 0.05). The E-to-I and T-to-F scores showed no correlation with the Total Neglect score (p > 0.5). N-to-S Scores The N-to-S score showed a negative correlation (r = -0.374, p = 0.011) with the Emotional Neglect score, which showed a higher percentage of S-characteristics than N-characteristics when the extent of emotional neglect during childhood was severe. Additionally, the N-to-S score also showed a negative correlation (r=-0.296, p = 0.033) with the Inadequate Supervision Score, which showed that S characteristics were more apparent than N characteristics as there was an increase in emotional neglect score. The N-to-S score did not show a significant correlation with Physical Neglect, Educational Neglect, and Medical Neglect scores (p > 0.112).

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Graph 1. N-to-S Scores J-to-P Scores The J-to-P score was significantly correlated with Emotional Neglect, Inadequate Supervision, and Physical Neglect scores. Lower J-to-P scores were found in participants with higher levels of such neglect. This suggested that participants who experienced more emotional (r = -0.307, p = 0.028), supervisional (r = -0.323, p = 0.022), and physical (r = -0.258, p = 0.05) neglects in childhood showed more P characteristics than J characteristics. The J-to-P score was also marginally significantly correlated with Educational (r = -0.206, p = 0.104) and Medical Neglect (r = -0.238, p = 0.072), which showed more P characteristics when participants reported higher levels of educational and medical neglect in childhood.

Graph 2. J-to-P Scores A-to-T Scores The A-to-T score demonstrated significant correlations with Emotional Neglect and Medical Neglect scores. The A-to-T score decreased, which indicated stronger T characteristics as the level of reported emotional neglect increased (r = -0.374, p = 0.015). The Medical Neglect score also showed a negative correlation (r = -0.283, p = 0.041), which showed more T characteristics than A characteristics when the level of medical neglect was high. Inadequate Supervision and Physical Neglect scores showed

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marginal correlations with A-to-T scores, with more T-characteristics when higher levels of inadequate supervision (r = -0.223, p = 0.086) and physical neglect (r = -0.21, p = 0.1) were reported. There was no correlation with Educational Neglect scores (p = 0.346).

Graph 3. A-to-T Scores Other Personality Characteristic Scores The E-to-I and T-to-F scores showed no significant correlation with the five childhood neglect experiences (p < 0.323 and < 0.945, respectively).

DISCUSSION This study investigated whether childhood neglect affected the strength of personality characteristics in young adults. Degree of neglect experience was measured through five neglect scores. In addition personality characteristics were obtained using five categories of the MBTI test results. The N/S, J/P, and A/T characteristics were significantly correlated with the amount of parental neglect experienced during childhood. Furthermore, the S (sensing), P (perceiving), and A (assertive) characteristics were relatively apparent than the N (intuition), J (judging), and T (turbulent) characteristics. However, the I (introversion)/ E (extraversion) and T (thinking)/ F (feeling) characteristics were not correlated with neglect experiences. This study suggested that childhood neglect influenced personality formation, which impacted development constrained in the short-term; however, it could also last till adulthood. Moreover, by separating the different types of parental neglect instead of diagnosing neglect as a whole, this study offers valuable insights into the types of neglect related to certain personality characteristics. Among the different types, emotional neglect and inadequate supervision had the strongest correlations with personality characteristics. Such neglect covered most emotional and psychological domains of children’s needs, which led them to be influential variables in the development of certain patterns of personality characteristics. Only reasons for the specificity of the personality characteristics related to neglected experiences can be inferred. The development of certain personality characteristics over others could be part of a child’s defensive mechanism, which made it easier for the child to cope with external contexts. By responding

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to the outside world, which included the caregivers’ words and acts, a child could feel less neglected or resolve a neglected situation. The accumulation of such endeavors could solidify an individual’s disposition, which could lead to the formation of long-term influences, such as personality characteristics. In such scenarios, “reliance on reality-based sensing (S),” “able to make impromptu judgements and less planned (P),” and “self-assertive, independent, and less turbulent to external stimuli (A)” might have been strategical in coping with the world. Since this study was conducted with a relatively small variance of neglect scores and lacked scores from 200 and higher (up to 600), we believe that future studies should explore the degrees of neglect and strengths of personality traits by including further extreme cases of childhood neglect and a larger diversity of personality characteristics.

REFERENCES 1. Erickson, M. F., & Egeland, B. (2002). Child neglect. In J. E. B. Myers, L. Berliner, J. Briere, C. T. Hendrix, C. Jenny, & T. A. Reid (Eds.), The APSAC handbook on child maltreatment (pp. 3–20). Thousand Oaks: Sage Publications, Inc. 2. Erickson, M. F., Egeland, B., & Pianta, R. (1989). The effects of maltreatment on the development of young children. In S. Cicchetti (Ed.), Child maltreatment (pp. 647–684). New York: Cambridge University Press. 3. Herrenkohl, R. C., Herrenkohl, E. C., Egolf, B. P., & Wu, P. (1991). The developmental consequences of child abuse: The Lehigh longitudinal study. In R. H. Starr, Jr. & D. A. Wolfe

4. 5. 6. 7.

(Eds.), The effects of child abuse and neglect: Issues and research (pp. 57ė81). New York: Guilford Press. Ajake, U. E., Bisong, N. N., & Jamabo, A. (2009). Relationship between child abuse and the trait of introversion-extroversion among senior secondary students in Cross River State, Nigeria. Annals of Modern Education, 1(1), 122–127. Briggs-Myers, I., & Briggs, K.C. (1985). Myers-Briggs Type Indicator (MBTI). Palo Alto, CA: Consulting Psychologists Press. Myers, I.B. (1962). Manual: The Myers-Briggs Type Indicator. Princeton, NJ: Educational Testing Service. Sipps, G.J., & Alexander, R.A. (1987). The multifactorial nature of extraversion-introversion in the Myers-Briggs Type Indicator and Eysenck Personality Inventory. Educational and

Psychological Measurement, 47(3), 543ė552. 8. Dubowitz, H., Newton, R. R., Litrownik, A. J., Lewis, T., Briggs, E. C., Thompson, R., English, D., Lee, L. C., & Feerick, M. M. (2005). Examination of a conceptual model of child neglect. Child maltreatment, 10(2), 173–189. https://doi.org/10.1177/1077559505275014

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Koreans’ Perception of China in Social Media (Using Social Network Analysis) Author 1

Full Name

Sohn, Olivia Chaeri

HPrep Academy

(Last Name, First Name)

School Name

ABSTRACT In today’s globally interconnected society, China plays a crucial role in an expanding economy by being a leading exporter and a key contributor to international demands. However, this interdependence is vulnerable to outside influences, making it crucial to assess the dynamics of China’s global epithet. This study adopts an innovative approach to gauge the current relationship status with China by analyzing sentiments expressed by Korean influencers on social media, mainly focusing on platforms like TikTok and Twitter. By collecting data on the online activities of Koreans that disparage or belittle China, this research aims to explore the Korean perspective and perceptions of China. To succeed in this research, social network analysis methods will be employed to determine whether Korean netizens express an antagonistic stance toward China. A theme dictionary, particularly on nouns and adjectives, and a graph will be constructed to facilitate the visualization of word connections and reveal patterns in the sentiment of China.

KEYWORDS: SNA(Social Network, Analysis), China, Perception, Image, Social Media

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პ ,QWURGXFWLRQ These days, China has become one of the most integral countries in the world, as the nation is one of the leading exporters. According to the Observatory of Economic Complexity (OEC), China is the leading export market, and its expanding economy is a pivotal contributor to global demand. Many countries’ economies, politics, and societies depend on their relationship with China. However, this isn’t to say that this dependent relationship will always last forever, as outside factors affect the relationship between China and other countries. One way to check China’s current relationship status is by analyzing social media platforms inside and outside China. Social media is used worldwide to communicate and share opinions with others from different or similar backgrounds. On social media, most people are free to express their personal views on whatever topic they wish to discuss with their audience. With such capabilities, some people use social media to express their frustrations with the world, which commonly targets China. Therefore, social media will be an excellent source for collecting data and seeing whether or not the number of people who express their dissatisfaction with China has an effect on the overall global trade going on with China. This leads to the research being conducted, where online activities that belittle or disparage China will be collected in specific periods, alongside the corresponding amount of global trade that went on in that year with China and other countries. In addition, this research will employ the text analysis method to determine if a person’s online post shows a negative perspective toward China. This research will build a noun and adjective-oriented theme dictionary and illustrate it through word connections. At a time when China’s influence is rapidly growing, this research more closely examines how people from other countries look at China through extensive online data and provides a starting point for establishing policies against China.

,, 'LVFXVVLRQ %DFNJURXQG RU /LWHUDWXUH 5HYLHZ To better understand how China’s economic growth has shaped Korean perceptions of China on social media, there is a need to review existing literature to identify fundamental causes of the tension between China and Korea arising from China’s rise. Various studies have been conducted on internet users’ sentiments toward China since 2021. Research related to this topic is a common interest for students studying International Relations, which has been conducted mainly through social media posts. The results of several of these studies focusing on keywords or phrases are as follows. This article written by Wang (2021) claims that Koreans’ perception of China is complex. They looked through thousands of social media posts that showed them the unique cultural conflicts between China and South Korea. This research offers new insights into the effects of these popular narratives on China’s policy-making by highlighting the complexity of China-Korea ties through the lens of social media. It is still impossible to predict how the generally unfavorable perception of Chinese and Koreans toward one another will change over time or whether the proportion of people who hold more favorable views will rise. In any event, the heated debate on social media serves as a crucial benchmark and a sobering reminder that China and South Korea’s governments must adopt measures that support stable bilateral ties to ensure peace within the Asia Pacific region. As noted by Wang, based on a review of thousands of social media posts, a generally unfavorable perception of Chinese and Koreans may change over time, as reflected by the heated debate on social media. This has been exacerbated by China’s economic growth, which has led to rising Chinese nationalism, growth in Chinese media (including those depicting Korean characters), and increasing population and health issues originating from China. A review of existing literature demonstrates that

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there are four pivotal causes of Chinese-Korean tensions on social media: reactions to the Hallyu phenomenon, responses to the historical representation of Korean characters, reactions to Tiktok and other Chinese products, and reactions to environment and health issues such as COVID and yellow dust storms. Regarding reactions to Tiktok and other Chinese products, Tiktok has been an influential product that has led to significant anti-Chinese sentiment in Korea. As demonstrated by Abidin and Lee, Tiktok was initially perceived negatively as a ‘vulgar Chinese application’ but eventually found mainstream success after the launch of its K-pop linked event series ‘TikTok Stage,’ to fill the gap in the K-pop market arising from the COVID-19 pandemic. Hence, TikTok is an influential platform, but reactions to it among Koreans are mixed. Nonetheless, as discussed by Miao et al. (2021), TikTok’s operations have become politicized due to geopolitical conflicts between China and other nations, and state governments have expressed significant security concerns over the security of TikTok as a platform. This has led to a rise in anti-TikTok sentiment globally, including in Korea. The article by Snyder and Byun (2021) discusses the conflicts and controversies between South Korean and Chinese netizens on social media platforms, highlighting the emotions and sensitivities between the two communities. Various incidents of cultural and nationalist anger over product placement in Korean TV dramas led to intense criticisms from both sides. Additionally, problems in historical dramas worsened tensions. Social media played a significant role in increasing these controversies and inspiring nationalism. An example is the increasing negative opinions towards China in South Korea. Public opinion polls show a growing negative view of China in South Korea, with many believing China to be a threat. Negative public opinion in South Korea, and the Moon Jae In administration’s attempts to make China happy, became a big issue in the next presidential election. While conflicts between the two countries persist, their dislike for Japan is something they have in common. Japanese wartime history and colonial aggression have gathered support from Chinese and South Korean netizens on social media platforms. In conclusion, social media’s influence on public opinion and causing nationalist beliefs have worsened conflicts between South Korea and China. Both countries need to carefully prevent further problems and maintain stability in the region because they are close neighbors. A portion of Kim’s (2021) article examines, through the lens of social media, the cancellation of the Korean historical drama “Joseon Exorcist” due to accusations of seeing history through “Chinese” aesthetics, which has led to anti-Chinese opinions in South Korea. According to some Koreans, this trend has been worsened by China’s “cultural imperialism,” which includes attempts to misrepresent Korean culture and historical figures. Social media has significantly heightened the reaction against China’s cultural influence in South Korea. The Pew Research Center reports a rise in negative sentiments toward China among South Koreans, with problems such as the COVID-19 outbreak and Beijing’s “wolf warrior diplomacy” contributing to this change. Also, the memories of China’s economic retaliation during the THAAD missile defense system installation have increased antiChinese opinions among South Koreans. Social media platforms have worsened nationalism and increased the spread of information on problematic issues, influencing public views of China. The cultural tension between South Korea and China may cause problems in their diplomatic relations, potentially turning South Korea’s China policy into an issue that divides its citizens. Reactions to the historical representation of Korean characters in Chinese media have been adverse on social media. Kim (2021) examines, through the lens of social media, the cancellation of the Korean historical drama “Joseon Exorcist” due to accusations of seeing history through “Chinese” aesthetics, which has led to anti-Chinese opinions in South Korea. According to some Koreans, this trend has been worsened by China’s “cultural imperialism,” which includes attempts to misrepresent Korean culture

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and historical figures. Social media platforms have worsened nationalism and increased the spread of information on problematic issues, influencing public views of China. This article, written by Jang, explores the dynamics of the Korea-China relationship in the context of the Hallyu (Korean Wave) phenomenon, which refers to the global popularity of Korean pop culture. It discusses how Hallyu can promote connectivity between the two nations and lead to misunderstandings. The anti-Hallyu movement, expressed through critical voices on social media, reflects the opinions of national pride within both China and South Korea. While anti-Hallyu opinion changes, it often occurs during periods of tension between the two nations. An example of this is how social media energizes the anti-Hallyu movement by criticizing Korean cultural products and pop stars. Some netizens focus on the repetitive and stereotypical nature of Korean TV dramas, while others raise concerns about the negative effects of Hallyu on Chinese audiences, especially the youth. But the issues go beyond popular culture and Hallyu, which worsen nationalistic opinions. Events like registering a Korean festival on the UNESCO cultural heritage list caused nationalistic and negative reactions in China to Korean pop culture. As the Korean and Chinese cultural industries continue to compete and cooperate, the people of both nations say Hallyu improves communication and cultural exchange. Still, they say it is also necessary to remain cautious about cultural exchanges via Hallyu. Overall, the article discusses how problems will persist within and outside popular culture. It calls for efforts to prevent disagreements from spreading, control nationalism that can cause harm, and seek mutual opportunities that benefit both South Korea and China. Social media’s role in creating public opinion and worsening tensions between the two countries highlights the need for cautious but beneficial awareness of cultural exchanges. Given the popularity of K-pop groups in both countries, Hallyu has the potential to promote connectivity between the two nations. However, there have been anti-Hallyu reactions driven by nationalism in China, which has led to significant resentment and discontent on Korean social media.

რ 'DWD DQG 0HWKRGV 1. Data In light of the advancements in social networking services (SNS), this study employs web crawling to gain insights into Korea's perceptions of China. The analysis focuses on a significant period when China's global influence as a superpower was widely recognized due to the impact of COVID-19. The data collection spans 2017 to June 2023, capturing critical events and shifts in international relations. The choice of this timeframe is based on the escalation of trade disputes between South Korea and the United States until 2017 and the emergence of China's responsibility as the origin of the Coronavirus in the global community from 2020 to 2022. Additionally, the data extends until June 2023, coinciding with the resumption of travel and international/cultural exchanges as COVID-19 became a part of daily life worldwide. This comprehensive data collection covers approximately five and a half years, enabling a thorough examination of Korea's evolving perceptions towards China.

Furthermore, the research's data sources were carefully selected. The authorities focus on blogs, online communication channels, and websites that showcase the most prevalent opinions of Korean netizens concerning China. The primary emphasis was on social media platforms and search engines with substantial internet traffic, such as 'Tiktok,' 'Facebook,' 'Twitter,' 'WeChat,' 'Instagram,' 'Naver,' and 'Youtube.' These platforms serve as major avenues for netizens to share information and express their sentiments, attitudes, opinions, and underlying rationales. Notably, the inclusion of 'Naver' as a portal site was driven by its popularity among Koreans, surpassing Google usage, and its distinct sections

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dedicated to Chinese-related comments. The selected platforms offer a conducive environment for free and open discussions and opinions, detached from formal decision-making processes, with relatively stringent restrictions, ensuring a potential reduction in biases and acquiring more accurate information. Data collection involved extracting comments and posts, applying scripts for Youtube analysis, and enabling a comprehensive understanding of netizens' perspectives.

2. Method In this research, social network analysis was conducted to examine the connections among nouns and adjectives related to Koreans’ perception of China and its effects. Social network analysis is a methodology that derives various attributes that appear in a particular social phenomenon and organizes the relationships between them as a connection network. In a network, components are represented as nodes, and connections between them are represented as edges (Song Taemin & Song Juyoung, 2016). In particular, the recent emergence of online social network services such as Twitter and Facebook, along with personal blogs and social network analysis targeting them, has received significant attention (LaValle et al., 2011). The advantage of this method is that it is not limited in scope and can derive the main factors that constitute complex and diverse social phenomena that are invisible to the eye and visualize them intuitively (Cross, Borgatti, and Parker, 2002).

In this study, social network analysis methodology was applied to visually identify the relationships between large amounts of words derived from web crawling. Specifically, the connections between the 110 words with the highest number of mentions in all seven years (2017, 2018, 2019, 2020, 2021, 2022, and 2023) were identified. The size of the nodes was represented by the frequency of mentions of each word, and the edges were set to 1 if the words were mentioned on the same page in the previous web crawling and 0 if they were not mentioned together and were represented as an undirected network (binary matrix) to examine the connections intuitively. In addition, the node colors of the words detected in the social network analysis were differentiated by region to show the share of each of the four areas in the overall network and their connections to other issues.

Later, based on the data results, this research would like to look at Korea's perception of China through SNS, compared with the pre-built "theme dictionary." The examination of complex and diversified online opinions through social network analysis is to identify the rough trends rather than the exact causes and results, and the results are based on the researcher's subjective interpretation. However, to reduce logical errors in interpreting the results, we would like to examine various documents and consider whether the interpretation is valid.

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Noun

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Neutral ZRUGV ĺ

- Cool - Delicious - Economic Cooperation - Familiar - Friend - Friendship - Growth - Mutual respect - Panda - Sublime - Unity - Voluntary Agency Network of Korea (VANK)

- Intellectual -Account Property - America - Intimate - Audition - Instagram - BTS - Makeup - Confucian Products Culture - Minority - Cultural - Mukbang Exchange - Netflix - Cultural - One to one greatness - Real estate - Crossed - Soft power - Contents - Dependency - Taiwan - Tiktok - Drama - University - Economic Development - WeChat - YouTube - Facebook - Hegemonism

- Agitation - Boycott - Chinese - Chinese Food - Chinese Idol - Chinese Netizens - Chinkey - Communism - Copycat - CoronaVirus - Derim-dong - Dictatorship - Drugs - Economic Retaliation - Fine dust - Game Company - Great Power - History Problems - Hostility - Human Rights Issue - Illegal Sites - Interception - Kimchi - KoreanChinese

- Multicultural

- Noisy - Anxiety - Authoritative - Sarcastic - Scary - Deceitful - Suppression - Delinquent - Tat - Dirty - Threatening - Disorderly - Undemocratic - Eerie - Unfavorable - Emotional - Unpleasant - Envious - Misunderstood

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252

- KoreanChinese Couple - Korean Limitation Order - Made in China - Manipulation - Northeast Project of the Chinese Academy of Social Science - North Korea - Pride - Red Guards - Regulate - Rich Chinese Men - Security Issues - Territorial Dispute - THAAD Development - Thievery - Wealth gap - Xiaomi - Xi Jinping - Yellow dust

ს $QDO\WLF 5HVXOWV In this study, data was collected using the Python code. First, this study entered the words "China," "recognized," and "image," which were exposed online, and then saved the sentences (line) included on the Web page in the form of CSV files. Subsequently, using the SQL program, we have derived the most frequently mentioned words among all the words said. This research is connected between nodes if the derived words are mentioned in the same document and disconnected if they are not. This was then expressed as a picture using the Gephi 10.0 program. The results of the social network analysis above can be shown as follows.

>)LJXUH 7KH UHVXOW RI 6RFLDO 1HWZRUN $QDO\VLV@

1. Culture According to the graph, 37.61 percent of the words are related to culture, which is the biggest portion among the four categories. This shows that the intensity of Korean perception of Chinese culture is stronger than other ones. My understanding of culture is neutral since it includes both positive and negative words. Panda and BTS are compelling evidence for the positive side. ‘Panda’ is connected to positive keywords like friend, friendship, and intimacy. Recently, one of the posts of a Chinese panda, “Fu Bao,” in Everland Zoo became viral on TikTok, which led her to gain fame and love. This also contributed to making the panda’s image positive. Moreover, ‘BTS,’ one of the most famous K-pop bands worldwide, is connected to positive words and social media platforms. On the other hand, culture is also negative as Chinatown and Chinese food are linked to dirt, meaning Koreans do not favor Chinese culture.

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2. Society My understanding of society is negative. Unlike cultures, this category includes negative adjectives such as unpleasant, unfavorable, noisy, and deceitful, which shows that Korea's view of Chinese society is pessimistic.

3. Politics My understanding of politics is also negative. For instance, as shown in the graph, ‘Xi Jinping’ was not mentioned much, but most of the words connected to Xi Jinping are negative, which illustrates that most Koreans do not like him. This feeling might have gotten bigger due to social media and news posts discussing his communist actions and the miserable results. Additionally, the Northeast Project and the Chinese government system (communism and undemocratic) are connected to hostility, showing that Koreans disagree with how Xi Jinping rules the country.

4. Economics My understanding of economics is negative as well. People do not favor products ‘made in China,’ such as Chinese food and Xiaomi, since they are connected to pessimistic words: tat, dirty, unfavorable, and copycat.

9 &RQFOXVLRQ This study reveals significant tension in the China-South Korean relationship, emphasizing the need for cautious internet usage by citizens in both nations. The two nations are close neighbors, and thus, they should always seek mutual respect even when their citizens post content online. We should acknowledge ordinary citizens' power in preserving peace between the two nations because politicians will react kindly to what people demonstrate online. Social network analysis efficiently processes diverse and unfiltered opinions, benefiting from abundant virtual spaces and data sources. According to the result, 15% of the words were positive, 28% were neutral, and 57% were negative. This demonstrates that the Korean sentiment toward China is negative. However, there are a number of limitations to this research paper. Foremost, there is a need to expand the use of data sources in this paper and include more reliable sources to corroborate opinions found on social media. Secondly, the results are not statistically significant, given the limited quantity of data that could be used for social network analysis. Thirdly, organizing the 'Theme Dictionary' presented challenges due to varying interpretations of positive, neutral, or negative words, especially in culture and society categories. Expanding this study with more reliable data sources and sentiment analysis tools will increase the validity of the results.

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References 1. Amedie, Jacob. “The Impact of Social Media on Society.” Scholar Commons, 3 Sept. 2015, https://scholarcommons.scu.edu/engl_176/2/. Accessed 29 July. 2023. 2. Abidin, Crystal, and Jin Lee. “K-pop TikTok: TikTok’s Expansion Into South Korea, TikTok Stage, and Platformed Glocalization.” Sage Journals, 12 July 2023, https://journals.sagepub.com/doi/full/10.1177/1329878X231186445. Accessed 3 Aug. 2023. 3. Carr, Caleb, and Rebecca Hayes. “Social Media: Defining, Developing, and Divining.” Taylor & Francis Online, 6 Feb. 2015, https://www.tandfonline.com/doi/abs/10.1080/15456870.2015.972282. Accessed 1 Aug. 2023. 4. Jang, Soo Hyun. The Korean Wave and Its Implications for the Korea-China Relationship. https://s-space.snu.ac.kr/bitstream/10371/96546/1/7.The-Korean-Wave-and-ItsImplications-for-the-Korea-China-Relationship_Soo-Hyun-Jang.pdf. Accessed 1 Aug. 2023. 5. Kim, Dongwoo. “The Politics of South Korea’s ‘China Threat.’” The Diplomat, 5 Apr. 2021, https://thediplomat.com/2021/04/the-politics-of-south-koreas-china-threat/. Accessed 1 Aug. 2023. 6. LaValle, Steve, et al. “Big Data, Analytics and the Path From Insights to Value.” MIT Sloan Management Review, 21 Dec. 2010, https://sloanreview.mit.edu/article/big-data-analytics-and-thepath-from-insights-to-value/. Accessed 1 Aug. 2023. 7. Miao, Weishan, et al. “More Than Business: The De-politicisation and Re-politicisation of TikTok in the Media Discourses of China, America, and India (2017–2020).” Sage Journals, 20 May 2021, https://journals.sagepub.com/doi/abs/10.1177/1329878X211013919. Accessed 29 June 2023. 8. Pulido, Cristina, et al. “Social Impact in Social Media: A New Method to Evaluate the Social Impact of Research.” PLOS ONE, 29 Aug. 2018, https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0203117. Accessed 29 July 2023. 9. Snyder, Scott, and See-Won Byun. “China-Korea Relations Poised for Recovery Despite Intensified Conflict on Social Media.” Comparative Connections, May 2021, https://cc.pacforum.org/2021/05/china-korea-relations-poised-for-recovery-despite-intensifiedconflict-on-social-media/. Accessed 1 Aug. 2023. 10. Song, Taemin, and Juyoung Song. Social big data research methodology using R. Hannarae, 2016. Accessed 1 Aug. 2023. 11. Wang, Roselyn. Online Cultural Contention and China-Korea Relations: Interpreting Netizens’ Narratives on Social Media. 21 May 2021, https://repository.usfca.edu/cgi/viewcontent.cgi?article=2408&context=capstone. Accessed 26 July 2023.

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RESEARCH PAPERS

- STEM

Medical Data Clustering Algorithm with Improved Weighted Calculation Author 1

Full Nam

Cha, Igyeong

Seoul Science High School

(Last Name, First Name)

School Name

ABSTRACT: This research is to apply additional weights to the similarity calculation of spectrum clustering algorithms to make them more flexible to respond to density differences between clusters, which were weaknesses of existing algorithms. This innovative algorithmic idea performs more accurate clustering in allergen medical data. Effective clustering can help us live healthier and greener lives. The goal is to help allergy sufferers and their surroundings by analyzing data with a new clustering algorithm. A method of multiplying each similarity matrix by the power of the density of the surrounding area was used. The weighting method was subdivided into 25 categories according to the calculation radius of density, the density value used, and the calculation method of weight. Each segmentation method is applied to two dimensional scatter data and evaluated with a Rand index and visualization. As a result, it effectively detected low-density clusters without degrading the existing accuracy. Calculating the density within a long radius and using a higher density gave the highest accuracy. Also found that using positive n worked well to separate low-density clusters. The highest performance was achieved using the case of n=1 and Eps=1. The significance of this research is that it addresses the weaknesses of existing algorithms without compromising the accuracy of existing methods. Evaluated the results by considering various variables and succeeded in presenting a new algorithm. This algorithm can effectively manage and analyze medical data of allergy patients. It is an innovative way to make our lives healthier and greener, including various marginalized groups.

KEYWORDS: Clustering, medical data mining, DBSCAN, weight calculation, similarity matrix

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1. INTRODUCTION AND GOAL 1.1. Necessity and Purpose Allergies are a significant health problem that affects approximately 250 million of the world's population and is increasing worldwide. The U.S. Centers for Disease Control and Prevention reports that the prevalence of allergies in children under the age of 18 in the U.S. increased from 3.4% to 5.1% in the 2010s. Anaphylaxis, a form of systemic shock caused by allergies, sends 29,000 people to emergency rooms in the U.S. each year, resulting in more than 150 deaths. These allergies are closely linked to the environment. Environmental pollution, such as the concentration of air pollutants (ozone, nitrogen dioxide, dust, etc.), house dust, and environmental hormones, can be correlated with allergies. In this paper, we present an innovative process for algorithmically classifying medical data of allergies and allergens (substances that cause allergies) related to these environments. Among them, we will present an improved clustering algorithm that can effectively analyze allergen data considering its characteristics. Clustering refers to the process of dividing individuals into several subclusters (clusters) when they are given. At this time, the purpose is to minimize the distance between members inside the cluster and to maximize the distance between members outside the cluster. These clustering algorithms are of great importance in real life and computer science, typically clustering in document data and utilization in medical data mining. Representatively, two methods of clustering are DBSCAN and spectral clustering, both of which have disadvantages of being vulnerable to density differences between clusters. This is because DBSCAN creates a cluster tree based on the density of data as a classification criterion, clusters it, or draws a graph that connects similar data samples and clusters it, and spectral clustering uses the distance between points as a criterion of similarity. Accordingly, in order to correct the density difference between clusters, this may be improved in consideration of the surrounding density. Therefore, this study aims to study an algorithm that sets graph weights by additionally considering the ambient data density in the algorithm of spectrum clustering. Its effectiveness is verified by comparing existing algorithms with rand index evaluation indicators and visualization results. In addition, through this, this study tends to propose an efficient clustering method in various industries such as medical data. In particular, we expect to see significant improvements for data where the density of important clusters is significantly smaller, such as allergen medical data, which is the objective of this research.

1.2. Previous studies and related theories 1.2.1. Clustering Clustering is a type of unsupervised learning, an algorithm that creates clusters between similar objects by considering the characteristics of the data when there is no criterion for classifying them. In this case, the goal is to find representation by minimizing the distance between individuals in the cluster and maximizing the distance between other clusters. It aims to discover new groups hidden in a functional sense, give new meaning to the group through analysis and understanding of data values within the new cluster, and interpret the entire data from various angles.

1.2.2. Hierarchical Clustering Hierarchical clustering is also called agglomerative clustering as a method of reducing the number of clusters by selecting two clusters with the most similarity among several clusters, i.e., two clusters with close distances, and combining them into one. Initially, clusters exist as many as the number of data since all clusters have only one data, but as a result, only a few clusters remain. To this end, the process of measuring the distance between all clusters must be preceded, which can be explained by dividing

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into a hierarchical measurement method based on the assumption that the clusters were merged in a hierarchical method in the previous step and a non-hierarchical measurement method that does not depend on it.

1.2.2.1. Non-hierarchical distance measurement method It is a distance measurement method used in all situations, and representative examples include centroid distance, single distance, complete distance, and average distance. However, there is a disadvantage that the amount of calculation is higher than that of the hierarchical distance measurement method.

1.2.2.2. Hierarchical distance measurement method This method is used assuming that two random clusters have been combined in the previous step, and it is efficient because the amount of calculation is less than that of the non-hierarchical distance measurement method. The median method defines the distance at the center point of the cluster as the distance between clusters. The difference can be found in the method of calculating the center point, where the cluster u is made by combining clusters s and t, the center point of cluster u is calculated quickly using the mean of the center point of the original two clusters. The weighted method selects the distance average between the two original clusters and the new clusters that made up the distance between the created and other clusters, and the Ward method is a variant of the above method, which makes the distance to the new cluster more distant if the original two clusters are too close.

1.2.3. Partitioning Clustering Partitioning Clustering proceeds by including the objects closest to the center of the cluster one by one while the number of clusters is set. In this case, K-means based on the center and DBSCAN based on density can be representatively classified.

1.2.3.1. K-means This is a center-based clustering method that starts with the assumption that similar data are distributed on a centroid basis. Grouping is carried out by minimizing and updating the distance within each group from N data and k centroids, and process is as follows. First, k is defined as the center point and the same as the number of clusters to be grouped, and the initial point is set. Accordingly, the distance between k center points and individual data is measured, and the data is divided around the nearest center point to give a cluster. The process of updating the new Centroid with the average value of the allocated data and optimizing it until there is no change is repeated.

Fig 1. K-means process

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In conclusion, the final goal is to minimize the following objective functions. At this time, since the combination optimization was obtained approximately, there is a problem that it is vulnerable to the initialization stage setting value by converging to the regional optimum value rather than converging to the entire optimum value. Also, the center point of the initial cluster is randomly selected. However, there is a disadvantage that it is greatly affected by outliers.

Fig 2. K-means objective function formula 1.2.3.2. DBSCAN DBSCAN is an algorithmic method of clustering by creating a cluster tree based on the density of data, starting with the assumption that similar data will be distributed in close proximity to each other. The difference from K-means is that it automatically finds the optimal number of clusters without initially determining the number of clusters. First, if there are at least four points in the radius around one point, it is classified into one cluster and the point is set as Core point. If there are three points in the radius, it is not set as Core, but it is set as Border point as the point included in the cluster of Core1. If there are more than four points in the radius, set it as Core, and if Core1 is included in the radius, connect the clusters and group them into one cluster. The cluster can spread by repeating the above method and optimal number of clusters can be found in this process. Individuals between clusters are not mixed only within the minimum radius, and there is an advantage that outliers can be detected with the concept of noise.

Fig 3, 4. Visualization of DBSCAN process and clustering results 1.2.4. Spectral Clustering Spectral clustering is a clustering method of drawing and dividing graphs that connect similar data samples. Types of similarity graphs include ߳-neighbor graphs that connect samples with closer distances and k-NN graphs that connect each sample with the closest k samples. For each line, the similarities of the samples are expressed as adjacent matrices, the similarities between the samples connected by the lines are expressed as matrices, and the data are divided into k clusters so that the similarities between the separated clusters are minimized (minimum cut).

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It does not make strong assumptions about the distribution of data, and is a relatively easy-to implement and good way to produce results. It also has the advantage of being able to calculate at a sufficiently reasonable rate for thousands of sparse data. However, since it uses other clustering algorithms such as K-means in the final step, it does not always guarantee the same results and requires significant calculation for large data. In addition, as the difference in results can be confirmed depending on how many clusters are divided and classified, it should be applied according to the size and characteristics of the data.

1.2.5. Evaluation Indicators As an evaluation index of clustering, a rand index that evaluates with a future predetermined answer may be used. The rand index is performed by dividing the number of pairs that are correct by the total number of pairs, and the equation is as follows. RI =

ܽ+ܾ ܰ‫ܥ‬ଶ

Equation 1. Rand index formula In this case, is the number of pairs that are the same cluster in the correct answer and the same cluster in the labeling result. On the other hand, b is the number of pairs that are different clusters in the correct answer and different clusters in the labeling result.

1.3. Precedent study Existing works include 'Multiclass Spectral Clustering,' which clarifies the role of eigenvectors through orthogonal transformation and solves the discrete clustering problems closest to continuous optimization through eigen decomposition, and 'Spectral Clustering with Graph Neural Networks for Graph Pooling,' which trains GNNs to solve the minCUT problem in spectral clustering.

1.3.1. Multiclass Spectral Clustering Given the clustering discrete clustering formula, the continuous optimization problem is solved with eigen decomposition. Subsequently, orthogonal transformation clarifies the role of eigenvectors in all optimization problems and finds a discrete solution closest to continuous optimization. In this case, the discrete calculation is repeatedly performed through decomposition and suppression of outliers.

Fig 5. Multiclass Spectral Clustering algorithm

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1.3.2. Spectral Clustering with Graph Neural Networks for Graph Pooling Spectral clustering can be used to implement Pooling tasks in graph neural network (GNN) by aggregating nodes belonging to the same cluster. In this case, it is improved to formulate the relaxation of the normalized minCUT problem and calculate cluster allocation that minimizes the goal. It is a study that is differentiable and is designed to learn functions so that decomposition in spectral clustering can be quickly evaluated on a graph. However, even in the case of this study, there is still a problem that clustering considering importance cannot be performed because data with low surrounding density are classified into one cluster in the entire data. Existing studies have taken methods such as decomposing eigenvalues or learning GNN when utilizing spectral clustering, but essentially do not take into account differences in density between surrounding data. On the other hand, the difference in this work is that the density of the region can be considered by multiplying the existing k-NN graph by an additional weight dependent on density. Using this, it will be possible to solve the problem of clustering by ignoring low-density data. In addition, it will be practically effective in data with low density of a specific cluster (cancer patient data).

2. RESEARCH METHODS 2.1. Tools and materials ASUS ROG laptop (with CPU i5-10300, GPU GTX 1650 Ti) and anaconda navigator (jupyter notebook) were used, and data was built using numpy modules. Clustering was carried out in Google Colab. GPU computation was carried out using CUDA, a software for speeding up. Items

Description Processor

Intel(R) Core(TM) ig-10300H CPU

RAM

16GB

Graphic Card

NVIDIA GeForce GTX1050T

Operating System

Window 10 home, 64b

Programming Language

Python 3.6

Learning Framework

TensorFlow 1.13

H/W

S/W Table 1. Research environment

2.2. Suggesting method In this study, the similarity matrix used in spectral clustering algorithms is weighted to decrease with higher density, so that characteristic clusters of lower density can be better detected. To this end, after generating two-dimensional distributed data for clustering, several different weighting methods are devised and applied to the data to calculate the similarity matrix. The similarity matrix generated by each method is then applied to the algorithm to compare the rand index and visual representations of the results to explore the most suitable weighting method for data with density differences between clusters. In the experiment of this study, the clustering algorithm can be further supplemented from its features after finding the best way to extract low-density clusters from the various weighting methods devised. The approximate mechanism of the experiment is as follows.

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Fig 6. Generated sample data 1) Generating similarity matrices from the generated data and the weighted method devised 2) Creating and visualizing cluster labels using similarity matrices 3) Comparing visual features and rand index of clustering results 4) Exploring the weighting method for best performance

2.3. Creating data The allergen medical data are changed into a two-dimensional scattered data form for use as data for the application and visualization of clustering. The data consists of several small groups, each of which follows a two-dimensional normal distribution. The small group, the unit that generated the data, is used as a groundtruth cluster of the corrected rand index in the evaluation process. Among them, the lowdensity cluster to be detected more effectively in this study is set as the target cluster. In this study, three different data are generated and used.

2.4. Exploring clustering methods 2.4.1. Selecting density Since there are two points for each pair, there are also two available density values. Methods of selecting the density value to be used include D-max selecting the high side, D-low selecting the low side, and D-avg selecting the average. The lower the density to be considered, the higher the weight is applied to the similarity, which increases the probability of increasing the cluster.

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2.4.2. Weight calculation method The method of calculating the weight to be multiplied using the density value is to multiply the original similarity by ‫ܦ‬௡ . n (order of density) determines how much and in what direction the density of the region in clustering will contribute. If n is negative, the similarity of low-density clusters increases relatively and increases, and if n is positive, the high-density cluster increases. The n values used for the measurement are -2, -1, 1, and 2. (For n=0, it is a control group that does not take density into account.)

2.4.3. Eps setting Eps(ࣅ) is the radius of the region that counts the number of data when considering the density. The density is calculated by counting the number of data in the area within the Eps distance from the point where the density is to be obtained, which is used to calculate the weight. The larger the Eps, the more the density to the distant region is considered in the weight calculation. The Eps values used for measurement are 0.5 and 1.

2.5. Application and evaluation of weights Spectral clustering is performed by multiplying the similarity matrix k-NN graph by the obtained weight. Among the clusters detected through spectral clustering, the cluster with the highest precision for the target cluster of data is set as a representative. Thereafter, n is changed in units of 0.1 in the range of -3 to 3, and the precision and reproducibility of the target cluster of the representative cluster are evaluated. In addition, the most appropriate weighting method is derived using the rand index of the result for n of integer values in the range of -2 to 2 and the visualization of the clustering results when n=0, n=3 as evaluation indicators, and the difference from existing algorithms is analyzed.

3. RESULTS 3.1. Hypothesis As for the selection method, D-max was expected to show the best performance that meets the purpose most. This is because high-density clusters can merge small clusters to prevent small clusters from being ignored, and usually allow the density of the cluster itself to be considered. On the other hand, in the case of D-min, the density of non-critical outliers is greatly affected, and the weight increases, which

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may result in excessive cluster size. In the case of weight calculation, it was expected that the case of n = -1 would show the highest accuracy. This is because when n is negative, the weight of the low-density area increases, increasing the degree considered in clustering. However, it is expected that the accuracy will be highest at n = -1, as dense clusters could be ignored if n is too small below ė2. Eps is expected to be advantageous to use a high value. The purpose of this study is to consider pairs with higher similarity than ambient density, and it is necessary to consider the overall density of the surroundings rather than the density of local regions. Therefore, it is judged that it would be more advantageous to consider the density of a wide surrounding area by setting Eps relatively high.

3.2. Results 3.2.1. Comparison of rand index The average rand index for three data was used for the land index comparison. The following is a result of calculating the rand index according to Eps and n based on the D-max density selection method.

The following is a result of calculating the density selection method and the rand index according to n when Eps=1.

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3.2.2 Visualization of final results For each data, the clustering results visualized for D-max, Eps=1, and n=0, 3 are as follows.

3.2.3 Precision and reproducibility of target clusters Based on Eps = 1 and D-max, the results of visualizing the precision and reproducibility of the land index and target cluster according to n in the range of -3 to 3 are as follows.

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4. DISCUSSION 4.1. Consideration 4.1.1. Density selection method For the three density selection methods, there was little difference for all methods. This is because the k-NN graph was used as the base similarity matrix in this work, since only a few nearest points are connected, there is virtually no difference in density between the points on both sides of the line. For n=1 with the highest rand index, D-max was slightly the highest, but this seems to be a negligible difference.

4.1.2. Weight calculation method As a result of the experiment on N, unlike the hypothesis, the accuracy when n=1 was the highest, and it was found that it was slightly higher than that of the control group. In addition, from the results of the precision analysis experiment for the target cluster, it can be seen that the precision for the target cluster increases significantly when n>0. For the rand index and reproducibility, it decreases at n>0, but does not show a significant decrease in the range of 0<n<1.5. This shows that using an appropriate n between 0 and 1.5 allows precise detection of low-density clusters without significantly lowering the overall accuracy of existing algorithms. In addition, by visual comparison, when large n is used, such as n=3, it can be seen that small clusters are separated preferentially and instead large clusters are merged with each other, unlike the control group in which small clusters are merged into large clusters are merged with each other instead. The reason for this phenomenon lies in the mechanism of spectral clustering. Spectral clustering separates the graph so that the sum of the similarities to be separated is minimal, so it tends to preferentially separate the outlier with low similarity with other points. Therefore, spectral clustering tends to be an 'outlier cluster' in which one of the derived clusters consists of an outlier. When the positive number n is used, the dense cluster increases, so that the outer cluster becomes smaller around the small cluster included therein, so that the small cluster is better separated. Conversely, in the case of large clusters, the internal similarity becomes very large, making it difficult to separate from each other. As a result, when n=1 is used, it is possible to preferentially separate small clusters while maintaining or improving the existing accuracy (rand index).

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4.1.3. Eps setting Most of the cases where Eps=0.5 and Eps=1 did not show much difference, but in the case where the rand index was the highest derived n=1 weight, the case of Eps=1 was dominant. Therefore, it may be said that using the case of n=1 and Eps=1 shows the highest performance. By comparing the Rand index values and visuals for each variable with a "control cluster" using a traditional clustering method, the algorithm was able to verify more effective detection.

4.2. Suggestion First, the purpose of this study, 'effective detection of small clusters,' was achieved in a somewhat bypassed way, reducing the size of the outlier cluster to which the undetected cluster belongs, so that it is concentrated in the cluster area. This is fundamentally because the process of research has been applied to spectral clustering, a non-hierarchical clustering method. Since non-hierarchical clustering has a fixed number of clusters, the process of detecting a certain area must be achieved by actually manipulating the size of the cluster. In order to determine the ability to 'detect' clusters, it is necessary to apply the proposed methodology to non-hierarchical clustering in which the number of clusters is not set. Second, in this study, directly generated data were used, and to facilitate evaluation, data were organized into small clusters following a two-dimensional normal distribution and used as groundtruth. This is because the 'silhouette coefficient,' an evaluation index mainly used when there is no true value, is judged to be inappropriate for this study to correct the density difference between clusters because it uses the distance between points. This can be solved by modifying the silhouette coefficient to present an evaluation index that is not affected by the density of the cluster. In addition, instead of directly generated data, data from cancer patients and data from developed and developing countries can be utilized to increase the reliability of verification. In addition to presenting clustering evaluation indicators that are not affected by density differences and allergens, further refinement of algorithms such as application to actual data and refinement of formulas may be in the future. Through this, I will develop the research into correlating allergies with the surrounding environment using data and finding solutions. I would like to apply the methodology to better performance clustering algorithms such as Graph Neural Network to solve the chronic problem of clustering algorithms and present clustering algorithms that do not lose performance even for data with very large density differences.

5. CONCLUSIONS 5.1. Conclusion The significance of this study is that it solved the vulnerability of existing clustering algorithms such as DBSCAN to the density difference between clusters without degrading the accuracy of existing methods. Considering a wide variety of variables such as Eps, density calculation method, and weight calculation method, clustering results were evaluated and visualized for various data, and it succeeded in presenting a new algorithm that shows a significant difference in tendency from existing algorithms. Contrary to our hypothesis, we found that the results were not significantly affected by the density selection method, but rather by the n of the weighting method. In addition, by reducing the size of the outlier clusters to which the undetected clusters belonged, they were concentrated in the cluster area, thus achieving 'detection of small-density clusters'. This algorithm can effectively manage and analyze medical data of allergy patients, which is an innovative process that can help various socially vulnerable people and make our lives healthier and more environmentally friendly. In this research, both density and weight using it were calculated as a very simple form of equation. If

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this is improved in more detail, the problem of density difference between clusters can be solved by considering the density of data in a more rigorous form. This algorithm, which can effectively detect small-density clusters, can make it easier to work on high-priority and low-density clusters, such as data on cancer patients, and further develop a framework to fully solve the problem of chronic density differences in existing algorithms.

6. References [1] JIA, Hongjie, et al. The latest research progress on spectral clustering. Neural Computing and Applications, 2014, 24.7: 1477-1486. [2] ÜNLÜ, Ramazan; XANTHOPOULOS, Petros. Estimating the number of clusters in a dataset via consensus clustering. Expert Systems with Applications, 2019, 125: 33-39. [3] BIANCHI, Filippo Maria; GRATTAROLA, Daniele; ALIPPI, Cesare. Spectral clustering with graph neural networks for graph pooling. In: International Conference on Machine Learning. PMLR, 2020. p. 874-883. [4] VON LUXBURG, Ulrike. A tutorial on spectral clustering. Statistics and computing, 2007, 17.4: 395-416. [5] LIU, Jialu; HAN, Jiawei. Spectral clustering. In: Data clustering. Chapman and Hall/CRC, 2018. p. 177-200. [6] STELLA, X. Yu; SHI, Jianbo. Multiclass spectral clustering. In: Computer Vision, IEEE International Conference on. IEEE Computer Society, 2003. p. 313-313. [7] JIANG, Wenhao; CHUNG, Fu-lai. Transfer spectral clustering. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, Berlin, Heidelberg, 2012. p. 789803. [8] SCHUBERT, Erich, et al. DBSCAN revisited, revisited: why and how you should (still) use DBSCAN. ACM Transactions on Database Systems (TODS), 2017, 42.3: 1-21. [9] ALI, Tariq; ASGHAR, Sohail; SAJID, Naseer Ahmed. Critical analysis of DBSCAN variations. In: 2010 international conference on information and emerging technologies. IEEE, 2010. p. 1-6. [10] PHAM, Duc Truong; DIMOV, Stefan S.; NGUYEN, Chi D. Selection of K in K-means clustering. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2005, 219.1: 103-119.

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EGCG's Protective Role Against Brain Cell Death in 3D Human Glial Cell Model of Alzheimer's Disease Author 1

Full Name

Cho, Hyunseo

Seoul Scholars International

(Last Name, First Name)

School Name

ABSTRACT: Epigallocatechin gallate (EGCG) is a natural green tea substance known for its anti-ROS (reactive oxygen species) properties. This study aimed to investigate the protective effect of EGCG against Scopolamine hydrobromide (SH)-induced cell death and intracellular ROS levels in a human glial cell lines model of Alzheimer's Disease. Our findings indicate that 50 M SH effectively induced cell death in A172 human glial cells, providing a reliable model for mimicking Alzheimer's disease pathology. However, post-treatment with EGCG significantly protected against SH-induced cell death, as evidenced by enhanced cell viability. Additionally, EGCG treatment effectively reduced intracellular ROS levels, as shown by the decreased green fluorescence intensity in the fluorescence microscopy images. The quantification of intracellular ROS levels further supported the effectiveness of EGCG in mitigating SH-induced oxidative stress. Also, cells subjected to 50 M SH followed by EGCG treatment demonstrate the protection of A172 cells within the 3D culture model. These results highlight the potential of EGCG as a neuroprotective agent in Alzheimer's disease, as it promotes cell viability and reduces intracellular ROS levels. The ability of EGCG to modulate these crucial factors suggests its potential as a therapeutic intervention for protecting glial cells and combating the progression of Alzheimer's pathology.

KEYWORDS: EGCG, Alzheimer’s disease, Cell death, ROS

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INTRODUCTION Alzheimer's Disease (AD) is a neurodegenerative disorder with the progressive loss of neurons in the brain. [1] AD causes cognitive decline and impaired memory function. [2] It affects many individuals worldwide and poses a growing public health challenge. [3] Approximately 50 million people live with AD globally, and the number of patients will drastically increase in 2050. [3] Despite extensive research, the underlying causes and effective treatments for Alzheimer's Disease remain inconclusive. [4] One potential contributing factor to the pathogenesis of Alzheimer's is oxidative stress, which leads to neuronal damage and cell death. Epigallocatechin gallate (EGCG), a polyphenol found in green tea, has emerged as a promising compound with potential neuroprotective properties in the context of Alzheimer's Disease. [5] Previous studies have indicated that EGCG exhibits antioxidant and anti-inflammatory effects, crucial factors in neuroprotection. [6] These studies have provided evidence supporting the potential therapeutic intervention of EGCG in Alzheimer's Disease. [7,8] However, the mechanisms underlying EGCG's protective effects against neuronal damage and cell death remain unclear. [9] This study explored the EGCG's effect on the AD model's glial cells. We used scopolamine hydrobromide (SH) to mimic the AD model in glial cells and induced cell death. Next, we treated EGCG to analyze the protective effect against SH-dependent cell death. Finally, we quantified the intracellular H2O2 level and checked whether EGCG decreased the H2O2 level in human glial cells.

RESEARCH METHODS A172 cell culture RPMI1640 media supplemented with FBS and Penstrep was used to culture A172 human glia cell line. A172 cell line was purchased from Korea Cell Line Bank. The cells were cultured at 37°C in CO2 incubator. The cells were maintained healthy with 2-3 days of subculture. Cell viability test LUNA-FL automatic cell counter device was used to quantify the cell viability of the A172 cells. After staining with the PI/AO staining solution, the cells were incubated for five minutes, then loaded onto the imaging slide. The fluorescence image was taken, and red cells were analyzed as live cells. Cell imaging Before imaging, the cells were seeded onto glass coverslips, placed in culture dishes, and allowed to adhere and grow to the desired confluency. A fluorescence microscope was used to capture the image of the cells. The bright field and fluorescence images were captured when taking the images. Quantification of Intracellular ROS level The microscope was equipped with a high-resolution camera for image acquisition. Before imaging, the microscope was calibrated using appropriate calibration standards to ensure accurate measurements and image quality. The cells were observed under bright field illumination to obtain an overall structural view. For fluorescence imaging, the cells were stained with a specific fluorescent dye targeting ROS. The staining protocol followed the manufacturer's recommendations. Each image was acquired with a consistent exposure time and gain settings to maintain uniformity and enable reliable comparisons between images.

272

RESULT AND DISCUSSION

Figure 1. The image of A172 cell lines that cellular morphology changes in response to Scopolamine hydrobromide (SH) treatment resembles the Alzheimer's disease phenotype. After A172 cells were treated with 0, 5, 10, 20, 35, and 50 M for seven days, cell images were taken. In this study, we used A172 human glial cells to investigate the effect of SH on A172 cell morphology and density. We analyzed the six conditions with different concentrations of SH (0, 5, 10, 20, 35, 50 M) and incubated with A172 cells for seven days. We found that cell morphology changes with spindle shape as the SH concentration increases. Also, compared to the 0 M control sample, 50 M SH treated samples showed the lowest cell density. This result indicates that SH changes the cell morphology and decreases the cell density of A172 glial cells.

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Figure 2. Recovery of Scopolamine hydrobromide-induced cell death by EGCG treatment. A172 cells were initially treated with 50 M Scopolamine hydrobromide for seven days, followed by a 24-hour treatment with EGCG. Cell images were captured after the EGCG treatment. The obtained cell images revealed a noticeable reversal in the detrimental effects of Scopolamine hydrobromide-induced cell death upon EGCG treatment. The cells treated solely with Scopolamine hydrobromide exhibited significant morphological alterations and signs of cellular damage, including reduced cell density, irregular cell shape, and increased presence of cell debris. However, upon the administration of EGCG following the Scopolamine hydrobromide treatment, a remarkable recovery in cell viability and morphology was observed. The EGCG treatment led to a notable increase in cell density, restoration of regular cell shape, and decreased cell debris. These findings suggest that EGCG treatment effectively mitigates the detrimental effects of Scopolamine hydrobromide-induced cell death in A172 cells. The recovery of cell viability and morphology observed in Figure 2 provides compelling evidence for the potential therapeutic benefits of EGCG in countering the adverse effects of Scopolamine hydrobromide-induced cell death. Table 1. EGCG-mediated protection of A172 glial cells with increased cell viability. Total cell counts, live cell counts, and dead cell counts were determined using an automated cell counter after treatment. Cell viability was calculated based on the number of cells in each category. Name

Total Cell

Live Cell

Dead Cell

Viability

No treatment

1.34E+06

1.19E+06

1.50E+05

88.90%

50 M SH

1.27E+06

1.64E+05

1.11E+06

12.90%

50 M SH + 1 M EGCG

8.47E+05

1.09E+05

7.39E+05

12.80%

50 M SH + 36 M EGCG

8.45E+05

1.46E+05

7.00E+05

17.20%

50 M SH + 72 M EGCG

6.34E+05

6.03E+05

3.08E+04

95.10%

50 M SH + 100 M EGCG

9.54E+05

9.52E+05

1.91E+03

99.80%

To validate the qualitative observations presented in Figure 2, we quantitatively assessed cell viability. The cell viability of A172 cells subjected to a single treatment of SH alone decreased significantly to 12.90% compared to the untreated control cells. However, a dose-dependent recovery in cell viability was observed when A172 cells were treated with different concentrations of EGCG following the SH treatment. The treatment with 36 M EGCG led to an increase in cell viability to 17.20%, indicating a partial rescue of cell viability compared to the SH treatment alone. Moreover, a substantial improvement in cell viability was achieved with higher concentrations of EGCG. Treatment with 72 M EGCG resulted in a remarkable increase in cell viability to 95.10%. Furthermore, when A172 cells were treated with 100 M EGCG, the cell viability reached an impressive recovery rate of 99.80%, almost comparable to the viability of the untreated control cells. The quantification of cell viability provides robust evidence supporting the potential therapeutic benefits of EGCG in rescuing cell viability and counteracting the toxic effects of SH.

274

Figure 3. The strong correlation between EGCG concentration and A172 glial cell viability (r² = 0.8774). A linear regression model analyzed the correlation between EGCG concentration and A172 glial cell viability. Figure 3 illustrates a strong correlation between the concentration of EGCG and A172 glial cell viability, as evidenced by a high coefficient of determination (r² = 0.8774). A linear regression model analyzed the correlation between the EGCG concentration and A172 glial cell viability. The linear regression analysis revealed a significant positive relationship between the EGCG concentration and A172 glial cell viability. As the concentration of EGCG increased, there was a corresponding increase in the viability of A172 glial cells. The coefficient of determination (r² = 0.8774) indicates that approximately 87.74% of the variation in A172 glial cell viability can be attributed to the concentration of EGCG. These findings support the hypothesis that increasing the concentration of EGCG has a beneficial effect on A172 glial cell viability. The strong positive correlation observed in Figure 3 suggests that higher concentrations of EGCG are associated with higher cell viability in A172 glial cells.

Figure 4. Reduction of intracellular ROS levels by EGCG treatment following Scopolamine hydrobromide (SH) induction. (A) Representative cell images showing bright field and green fluorescence (indicating ROS levels). (B) Quantification of intracellular ROS levels in untreated cells, 50 M SH-treated cells, and 50 M SH-treated cells with EGCG.

275

In Figure 4A, representative cell images display the cellular morphology under bright field illumination, along with the corresponding green fluorescence, which indicates ROS levels. The images reveal variations in ROS levels among different experimental groups, providing a visual representation of the impact of SH induction and subsequent EGCG treatment on intracellular ROS levels. Figure 4B quantifies intracellular ROS levels in three experimental groups: untreated cells, cells treated with 50 M SH alone, and cells treated with 50 M SH followed by EGCG treatment. The quantification results demonstrate a significant increase in intracellular ROS levels in cells treated with 50 M SH compared to the untreated cells. This observation suggests that the induction of SH leads to an elevation in intracellular ROS production. However, when cells treated with 50 M SH were subsequently treated with EGCG, a notable reduction in intracellular ROS levels was observed. The EGCG treatment effectively mitigates the elevated ROS levels induced by SH, indicating its potential antioxidant properties.

Figure 5. Recovery of Scopolamine hydrobromide-induced cell death by EGCG treatment in 3D culture model. A172 cells were initially treated with 50 M Scopolamine hydrobromide for seven days, followed by a 24-hour treatment with EGCG. Cell images were captured after the EGCG treatment. Figure 5 presents a 3D culture model using A172 cells, which was tested under three conditions. The first condition involved untreated cells, while the second and third conditions involved cells treated with 50 M SH alone and cells treated with 50 M SH followed by EGCG treatment, respectively. In the image of the untreated cells, the 3D structure of the human glial cells appears intact. However, cells treated with 50 M SH alone showed a pattern of dispersed cell growth, indicating that most cells were induced to undergo cell death. Interestingly, cells treated with 50 M SH followed by EGCG treatment exhibited protection of the A172 cells in the 3D culture model. In this case, most cells retained a healthy 3D structure, similar to the untreated samples.

CONCLUSION In conclusion, this study demonstrates the protective effect of Epigallocatechin gallate (EGCG), a natural substance found in green tea, against Scopolamine hydrobromide (SH)-induced cell death and intracellular reactive oxygen species (ROS) levels in a human glial cell lines model of Alzheimer's Disease. The results of this study confirm that SH effectively induces cell death in A172 human glial cells, providing a reliable model for mimicking Alzheimer's disease pathology. [10] However, post-treatment with EGCG significantly protects against SH-induced cell death, as evidenced by enhanced cell viability.

276

This finding suggests that EGCG exerts a neuroprotective effect, promoting the survival of glial cells under conditions of SH-induced cytotoxicity. Furthermore, EGCG treatment effectively reduces intracellular ROS levels, as demonstrated by the decreased green fluorescence intensity in the fluorescence microscopy images. The quantification of intracellular ROS levels further supports the effectiveness of EGCG in mitigating SH-induced oxidative stress. The ability of EGCG to decrease intracellular ROS levels suggests its potential as an antioxidant agent, countering the detrimental effects of oxidative stress in Alzheimer's disease. [11] The findings of this study highlight the potential of EGCG as a neuroprotective agent in Alzheimer's disease. The ability of EGCG to promote cell viability and reduce intracellular ROS levels underscores its therapeutic potential for protecting glial cells and combating the progression of Alzheimer's pathology. Overall, the results suggest that EGCG may serve as a promising therapeutic intervention in the context of Alzheimer's disease, offering neuroprotection and antioxidative effects. Further research and clinical investigations are warranted to explore the precise mechanisms of action, optimal dosage, and potential synergistic effects with other treatments to fully harness the therapeutic benefits of EGCG in Alzheimer's disease.

277

REFERENCE (1) Brem, A.-K.; Kuruppu, S.; de Boer, C.; Muurling, M.; Diaz-Ponce, A.; Gove, D.; Curcic, J.; Pilotto, A.; Ng, W.-F.; Cummins, N.; Malzbender, K.; Nies, V. J. M.; Erdemli, G.; Graeber, J.; Narayan, V. A.; Rochester, L.; Maetzler, W.; Aarsland, D. Digital Endpoints in Clinical Trials of Alzheimer’s Disease and Other Neurodegenerative Diseases: Challenges and Opportunities. Front. Neurol. 2023, 14, 1210974. DOI: 10.3389/fneur.2023.1210974. (2) Inoue, Y.; Shue, F.; Bu, G.; Kanekiyo, T. Pathophysiology and Probable Etiology of Cerebral Small Vessel Disease in Vascular Dementia and Alzheimer’s Disease. Mol. Neurodegener. 2023, 18 (1), 46. DOI: 10.1186/s13024-023-00640-5. (3) Alzheimer’s Association. 2023 Alzheimer’s Disease Facts and Figures. Alzheimers Dement 2023, 19 (4), 1598–1695. DOI: 10.1002/alz.13016. (4) García-García, A.; Rojas, S.; Rodríguez-Diéguez, A. Therapy and Diagnosis of Alzheimer’s Disease: From Discrete Metal Complexes to Metal-Organic Frameworks. J. Mater. Chem. B Mater. Biol. Med. 2023. DOI: 10.1039/d3tb00427a. (5) Secker, C.; Motzny, A. Y.; Kostova, S.; Buntru, A.; Helmecke, L.; Reus, L.; Steinfort, R.; Brusendorf, L.; Boeddrich, A.; Neuendorf, N.; Diez, L.; Schmieder, P.; Schulz, A.; Czekelius, C.; Wanker, E. E. The Polyphenol EGCG Directly Targets Intracellular Amyloid-ȕ Aggregates and Promotes Their Lysosomal Degradation. J. Neurochem. 2023. DOI: 10.1111/jnc.15842. (6) Wijeweera, G.; Wijekoon, N.; Gonawala, L.; Imran, Y.; Mohan, C.; De Silva, K. R. D. Therapeutic Implications of Some Natural Products for Neuroimmune Diseases: A Narrative of Clinical Studies Review. Evid. Based Complement. Alternate. Med. 2023, 2023, 5583996. DOI: 10.1155/2023/5583996. (7) Rezai-Zadeh, K.; Shytle, D.; Sun, N.; Mori, T.; Hou, H.; Jeanniton, D.; Ehrhart, J.; Townsend, K.; Zeng, J.; Morgan, D.; Hardy, J.; Town, T.; Tan, J. Green Tea Epigallocatechin-3Gallate (EGCG) Modulates Amyloid Precursor Protein Cleavage and Reduces Cerebral Amyloidosis in Alzheimer Transgenic Mice. J. Neurosci. 2005, 25 (38), 8807–8814. DOI: 10.1523/JNEUROSCI.1521-05.2005. (8) Kim, J.; Lee, H. J.; Lee, K. W. Naturally Occurring Phytochemicals for the Prevention of Alzheimer’s Disease. J. Neurochem. 2010, 112 (6), 1415–1430. DOI: 10.1111/j.14714159.2009.06562.x. (9) Kepp, K. P.; Robakis, N. K.; Høilund-Carlsen, P. F.; Sensi, S. L.; Vissel, B. The Amyloid Cascade Hypothesis: An Updated Critical Review. Brain 2023. DOI: 10.1093/brain/awad159. (10) Chen, W. N.; Yeong, K. Y. Scopolamine, a Toxin-Induced Experimental Model, Used for Research in Alzheimer’s Disease. CNS Neurol. Disord. Drug Targets 2020, 19 (2), 85–93. DOI: 10.2174/1871527319666200214104331. (11) 6UHEUR = :LOLĔVNL % 6XUD 3 >2[LGDWLYH 6WUHVV LQ $O]KHLPHU¶V 'LVHDVH@ )ROLD 0HG Cracov. 2000, 41 (3–4), 165–170.

278

How Does the Frequency of the Touch Stimulation Affect Plant Growth? Author 1

Full Name

Chung, Sehwan

Chadwick International

(Last Name, First Name)

School Name

ABSTRACT: Thigmomorphogenesis has been extensively studied by botanists and bioengineers to observe plants’ development in the condition of frequently being touched. This process, known as ‘thigmomorphogenesis’, refers to how plants alter their shape and adjust themselves to be more resilient to external forces. Given the rising interest in thigmomorphogenesis within the scientific community, this research aims to investigate whether the frequency of touch stimulation affects plant growth. To study this topic, a 5-week experiment was conducted in a lab to observe and contrast the changes in Kale and Cornflower that were touched and untouched. To do this, plants were mechanically stimulated by using the Arduino Servo Motor to apply stress and pressure to the plants. Specifically, two sets of data on touched and untouched plants were gathered to assess the impact of thigmomorphogenesis on plant growth. The experiment results showed that a high frequency of thigmomorphogenesis leads to slower growth rates during the thigmomorphogenesis process and higher growth rates after the thigmomorphogenesis process is completed.

Aim

Observe the growth pattern of the plants in a stimulated condition and compare the growth of the touched and the untouched plant to see the effect of frequency.

KEYWORDS: Thigmomorphogenesis, Mechanically stimulated, Touch stimulation, Cornflower, Kale

279

პ ,QWURGXFWLRQ Kales and Cornflowers are valued in healthcare and pharmacology as they benefit people exposed to chronic diseases. [1], [2] However, in their natural environment, Kale and Cornflowers face several external stimuli, such as wind, air pressure, and adverse weather conditions. This may have an impact on their growth.

To better understand the impact of such mechanical cues, it is useful to stimulate these two plants in a controlled environment, possibly indoors, to observe how such external stimuli impact their growth. [3] The effects of thigmomorphogenesis can be observed by mechanically touching these plants frequently. If the plants grow more quickly under exposure to thigmomorphogenesis, it will support the growth of plants used to cure illness. This research will provide a better insight into thigmomorphogenesis affected by touch stimulation, especially by its frequency.

How thigmomorphogenesis is affected by mechanical stimulation is astounding. Regarding Jennet Braam and E. Wassim Chehab’s research essay "Thigmomorphogenesis" (2017), plants evolve more resiliently so that they do not get affected anymore by the same factor. This indicates and proves that plants develop themselves and use protective mechanisms, such as the "wind-response pathway." For example, a tremendous amount of strong wind affects the plant stems by bending them. However, they evolve their protective mechanisms to prevent themselves from further deteriorating. [6] In addition, this stimulation will improve the anchorage strength of roots and delay morphological changes and flowering, initializing thigmomorphogenesis in plants. When plants go through this process, they will gain resilience and be able to recover from their destroyed morphology. [7]

Thigmomorphogenesis studies how the morphology of plants changes in response to external forces. Jennet Braam and E. Wassim Chehab quoted in their research paper that thigmomorphogenesis is identified by physiological and morphological changes that occur with mechanical stimulation: touch, wind, etc. [4] In addition, according to Félix P. Hartmann et al. and Zhengguang Liu et al., plants are very sensitive to touch stimulations, and they may be exposed to these external stresses. These external stresses affect the epidermis, the outermost layer of the plant cell. Félix and his fellow researchers stated that “The stress pattern is not just based on tissue shapes, but predominantly on the anisotropic (a term used to describe that the growth rate is unequal to one another) growth of the inner tissues, which pulls the epidermis in the longitudinal direction.” [18]

While these changes are apparent, what happens inside at a molecular level is more astonishing. According to Washington State University (2023), plants are affected by the calcium flow and pressure caused by mechanical interaction. During this interaction, there are two findings that scientists have recently noticed: first, a slow rate of calcium will be released inside the plant when it first encounters direct touch, and second, a faster rate of calcium wave is released due to the pressure caused by the stimulation. [8] The pressure decreases the O2 and CO2 rates from respiration in and out of the plant. If these reactants are lacking, there should be fewer products, such as glucose and ATP, essential for plants' sufficient growth. This would periodically halt the process of growing. [9] Fortunately, their ability to cope with these factors by enhancing their resilience would prevent them from leisurely growing after the touch stimulation stops. [7] These changes in cellular responses alter cell wall modification and defense, which could increase the strength of plants on a micro-scale. These cellular changes would be significant for processes including turgor regulation, cellular expansion, and morphogenesis, which all elongate the surface area of the cell wall. [3]

280

Additionally, when external stimuli affect the plants, mechanotransduction is likely to occur due to calcium signaling, which is when calcium ions (Ca2+), the second messenger molecules of plants, are used to communicate and drive intracellular procedures that organize organelles and other substances in the cytoplasm of the cell. Calcium is essential in plants as they can grow and recover tissues. The external forces, including mechanical stimulations, will be converted into chemical responses. In addition, using cellular calcium allows plants to develop their defensive mechanism against various stresses. Consequently, when the plants are left untouched for a few days, they will grow taller as they will likely have enhanced strength on their stem and leaves. [9]

The “calcium memory” findings indicate that calcium remembers past experiences and prevents them from happening again, possibly affecting plants' morphology. For example, a plant known as Mimosa Pudica is sensitive to external stimuli. When touched, they immediately change their morphology by pointing their leaves downwards, which is an excellent example of thigmotropism. [10], [11]

This is an amazing finding as State University emphasizes that Ca2+ is important since, without any calcium, it is likely that the plants are going to lose their liveliness. This means if the calcium is constantly used and there is a deficient amount of calcium given to the plant, there will be a lower chance of the plant growing properly. [12]

To examine these changes in plants caused by thigmomorphogenesis, research was conducted for five weeks to examine the effectiveness of these simulations. During the experiment, data was gathered on how the dependent variables, the vertical length of Kale and Cornflower in centimeters, were affected during and after the touch and how non-stimulated plants were likely to grow. The correlation between these plants, untouched and touched (ones that are eventually not touched for the last two weeks of the experiment), was found to see how these factors will affect the plant's growth and under which conditions the plants can grow fittingly.

Touch stimulation is essential to perform thigmomorphogenesis in plants. According to Rithesh Ghosh et al. (2021), the interval of touches is necessary for the plants to restore mechanosensitivity, a specific response to mechanical stimulation. This means that if there is frequent contact with a plant and given a few days without mechanical stimulation, plants may have improved mechanosensitivity by restoring their ability to recover from the previous damage made by the stimuli. [5]

In this experiment, a notable difference from previous studies conducted by other scientists was the use of Kale and Cornflower, two medically notable plants worthy of cultivation at scale. According to Amy Richter's medically reviewed paper, Kale is capable of lowering LDL (bad) cholesterol levels and impacting blood pressure, belly fat, and fasting blood sugar levels. [1] Additionally, Cornflower is recognized as a significant source utilized in various medical industries, particularly for treating fever and water retention caused by excess fluid buildup in the human body, as suggested by WebMD [2]. Studying the growth of these plants is essential because, with suitable conditions, they can be effectively grown for use at scale. Therefore, it is crucial to understand the effects of mechanical stimuli and environmental factors on their growth. This paper will provide a correlation between the growth of plants and the frequency, as this paper aims to observe and compare the growth pattern of the plants when they are mechanically stimulate

281

,, 0HWKRGV DQG 0DWHULDOV 2.1 How the Frequency Worked During the Experiment The touch stimulation was coded with Arduino so that the touch frequency and motor speed were constant; as such, they will be 3000 ms for the whole period during the experiment. The orange wire attached to the Servo Motor was attached to the -9 input. The red wire was in the 5V input. Then, the brown wire was connected to the Ground (GND) input to make the motor rotate with the given code. Since it is evident from previous research that plants grow resilience when they are exposed to external stimuli, for the last two weeks of the experiment, the previously touched plant was left untouched to check if they developed their tissues to be more resilient by measuring their height after the stimulation is not acting upon the plants. This was checked if they were going to grow more than the ones that were untouched after they were not stimulated. By doing so, investigating if the frequency of the mechanical stimulation affects their growth either positively or negatively was possible. With these external stimulations, one primary variable was monitored: the plant's growth (DV) for every six plants, which includes three Kales and three Cornflowers, was measured by the vertical length of the plant in centimeters. By gathering the data from the untouched and touched plants, it was possible to determine the correlation between the growth of the plant and the frequency (how the frequency affects the plant's growth after they are not affected by the touch). Before the experiment, it was hypothesized that the plant would grow more than the untouched plants, as they can develop resilience to external stimuli.

2.2 Data & Method Two data sets were gathered during a month-long process: 1) the growth of the untouched plants and 2) the growth of the touched plants. These data were collected through 15 days of observations every Monday, Wednesday, and Thursday from June 26th to July 28th. During this long-term experiment, mechanical touch stimulation (IV) frequently touched the plants to affect their growth (DV). Indeed, two Kale and the other two Cornflowers were touched selectively, while the remaining Kale and cornflowers were not stimulated. To prevent the other plants from being stimulated, wooden sticks were fixed rigidly to the holes to prevent the untouched plants from the external forces acting on them.

282

Type of Plant

Frequency

Non-touched

CF1

Non-touched

CF2

CF3

2.3 Variables Dependent Variable (Growth). One dependent factor that is affected by the frequency of the touch stimulation (IV) is the plant's growth. The growth of the plant in centimeters (cm) according to the untouched and touched plants will provide two sets of data: one with the data that would tell the thigmomorphogenesis in plants, in which the mechanical stimulation changes the shape of the plant at a slower rate by leading the plants to delay flowering and improve the anchorage strength of roots, in the touched situation, and the other with the data for the untouched condition. [7] Independent Variable (Frequency). As Ghosh (2021) and Braam (2005) discussed, plants respond to frequent and low-intensity mechanical cues, including stimuli such as wind and gravity. This experiment will aim to simulate such mechanical signals through touch-based stimulations of the plants using the Arduino. The frequency of the touch stimulation per plant was designated as the independent variable; the speed of the servo motor was set to 3000 ms. Each plant had different interacting points: K3 and CF3 had an identical interacting time of 44 seconds, CF2 had a frequency of 46 seconds, and K1 had a frequency of 42 seconds.

Controlled Variable. Many aspects should be controlled during the experiment because the plants' environment should be the same; if the environment is different, the result will likely Be disrupted. The aspects that should be regulated and constant should be light exposure, temperature, humidity, nutrients, and water.

Light Exposure. Constant exposure to light on the plant is essential; according to the University of Minnesota Extension (UMN), light is a valuable source for growing plants. Plants require light for photosynthesis, which is how plants convert light and carbon dioxide (CO2) into their energy and food sources. However, if this process becomes unstable and disrupted in plants, they will not be able to grow sufficiently. If the light is inconsistent between plants, plants will be in different conditions, with differing results from each plant exposed to light or not. [14] This will be controlled by having Ultra Violet lights (UV) all day on the lamp for them to gain energy. By doing so, all plants will gain the same amount of light under the same condition.

283

Temperature. Temperature is a critical factor that either stimulates or halts plants’ growth. According to Texas A&M University, the preferred temperature is about 70 to 80 degrees Fahrenheit, 21-26 degrees Celsius. Lower temperatures make the plant recover from moisture Loss, intensify flower color and prolong flower life. On the other hand, exposure to high temperatures would lead to stressing plants, inhibiting their growth. [15] If every plant has different exposure to temperature, the possibility of having a similar growth rate will be reduced. Thus, it is important to have all plants at the same room temperature, ranging from 24 to 30 degrees Celsius.

Humidity. Humidity for plants is inarguably one of the most important variables that should be the same for all plants. Several factors make this variable crucial: it provides additional moisture to the leaf cells, helps retain warmth around the plant, and allows the plant’s root to absorb water and nutrients. [16] This indicates that if the humidity differs for each plant, those plants will have different amounts of water and nutrients given to them, also contributing to the different growth patterns between them. Since maintaining the humidity for all plants is significantly effective for plant growth, it is important to make all plants have the same humidity at 50~60%.

Nutrients. Nutrients should be controlled during the experiment as differing amounts of them would eventually affect the plant's growth. Jennifer B. Morgan and Erin L. Connolly (2023) learned that lacking nutrition reduces plant productivity and fertility. Nutrient deficiency can cause stunted growth, death of plant tissue, or yellowing of the leaves due to the less production of chlorophyll, a pigment that is specialized for photosynthesis. [16] If the number of nutrients is given differently to each plant, all of them will have different paces of growth and eventually lead to a misleading conclusion. There will be water with nutrients dissolved under the platform they are grown in so they can intake nutrients whenever they want.

Water. Like sunlight or UltraViolet light (UV), water (H2O) is an important factor that allows plants to grow. Jodi Richmond discovered that H2O is important for the photosynthesis of plants, in which they gain energy for them to use during in vivo and in vitro activities. [17] Since the amount of water given to the plants is extremely important, this will be controlled automatically as the artificial plant grower sprays water on the plants.

,,, 5HVXOWV 7DEOH $YHUDJH *URZWK 'DWD RI 7RXFKHG 3ODQWV

Type

Growth w/ Touch

Average Growth per day

Growth w/o Touch

(21 days)

Average growth per day

Total Growth

(14 days)

Total Avg. Growth per day (35 days)

5.9 cm

0.28 cm

18.4 cm

1.31 cm

24.3 cm

0.69 cm

3.4 cm

0.16 cm

17.5 cm

1.25 cm

20.9 cm

0.59 cm

CF2

6.9 cm

0.49 cm

14.1 cm

1.00 cm

21.00 cm

0.60 cm

CF3

4.8 cm

0.22 cm

17.5 cm

1.25 cm

22.30 cm

0.64 cm

284

7DEOH $YHUDJH *URZWK 'DWD RI 8QWRXFKHG 3ODQWV Type

Total Growth

Total Avg. Growth (35 days)

12.1 cm

0.35 cm

CF1

9.3 cm

0. 26 cm

3.1 Explanation of the Data for K1 (Touched) At the end of the third week, the total increase in the height of K1 was 5.9 cm, and the average growth was 0.28 cm per day (21 days). Indeed, it was expected that the growth of K1 would be taller than the untouched ones. In the second week of the experiment, there was an evident change apparent on the stem of K1. During the remaining two weeks of the experiment, K1 rapidly expanded its vertical length by 18.4 cm in total, which was 12.5 cm more than the term of being touched for the first three weeks; in addition, the average growth rate of 1.3 cm per day during the two weeks with the absence of the stimulation. This is about 1.02 cm, different from the average growth rate measured from the three weeks of being touched. The stimulated plant grew 24.3 cm vertically with an average growth rate of 1.15 cm. One additional feature that was clear during the month-long experiment was the diameter of the stem’s thickness. In fact, the height of K1 has been increasing significantly.

3.2 Explanation of the Data for K2 (Untouched) The total growth of K2 was 2.5 cm, and the average height was 0.12 cm in the third week of the experiment. K2 was growing taller every day but at a slower rate than the ones being touched. It had a relatively slower growth rate than other plants. In addition, the growth in the last two weeks of the experiment was 9.6 cm, and the average growth rate per day was 0.69 cm. The total growth throughout the experiment was 12.1 cm, and the average growth was 0.86 cm. Even though K2 had a relatively fast growth rate in the last two weeks of the experiment compared to the first three weeks of the experiment, it is evident that the growth of the plant that was not touched had a slower growth rate than the ones that were stimulated.

3.3 Explanation of the Data for K3 (Touched) From June 26th to July 13th, K3 grew 3.4 cm in total vertically and grew approximately 0.16 cm on average per day. Like K1 and other plants being touched, it was hypothesized that K3 would also grow taller than CF1 and K2, which were not touched throughout the experiment. Uniquely, unlike other plants that were being mechanically stimulated, the morphology of the plant changed; the plant altered itself to the direction it was being stimulated: the plant leaned towards the left as the plant was mechanically stimulated towards the left side. In the last two weeks of the experiment, K3 also experienced an expedited growth of plants. The growth of the plant was 17.5 cm after the touch stimulation halted. The average growth pace of the plant, which is 1.25 cm, was also higher than the untouched plants. The plant's total growth from June 26th to July 27th was 20.9 cm, while the average height was 1.5 cm.

285

3.4 Explanation of the Data for CF1 (Untouched) During the first three weeks of the experiment, although CF1 was not stimulated, it had grown 2.8 cm in total and 0.13 cm per day on average. It constantly grew throughout the experiment, and its morphology was merely changed. From July 17th, CF1 grew 6.5 cm in total for two weeks and had an average growth rate of 0.46 cm. The aggregated growth was 9.3 cm with an average rate of 0.66 cm. However, unlike other plants, CF1 had no distinctive characteristics that were altered during the experiment.

3.5 Explanation of the Data for CF2 (Touched) The average growth of CF1 was 0.49 cm, with a total height of 6.9 cm on the twenty-first day of the experiment. After the mechanical stimulation was completed, the liveliness was gone for some plant leaves. The leaves were dragging and hanging down, dangling on the tip of The artificial plant growers. From the second term of the experiment that started on July 17th, it has been shown that the total growth was 14.1 cm, with an average growth of 1.0 cm per day for fourteen days. CF2 had a total growth of 21 cm for a month-long experiment and had an average growth of 1.5 cm per day.

3.6 Explanation of the Data for CF3 (Touched) The growth of CF3 was about 4.8 cm in the first half of the experiment, and the average height was about 0.22 cm per day (21 days). After the touch stimulation, several blossoms were blooming on the leaves of CF3. While it was one of the most frequently touched plants for three weeks from June 26th, it was evident that their posture was more upright than on the first day of the experiment. CF3 had a growth of 17.5 cm for the remaining two weeks of the experiment without touch stimulation. It also had a mean growth of 1.25 cm for two weeks. CF3 grew rapidly as it grew 22.3 cm in total, with an average daily growth rate of 1.56 cm.

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51.8

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286

The basic statistics (growth of Kale) indicate the number of observations, mean, standard deviation, minimum, and maximum value. During the experiment, there were 45 observations made. The mean vertical length was 10.42 cm, with a standard deviation of 7.11 cm. The smallest size between one of the Kales was 2.9 cm at the beginning, while the tallest Kale was 30 cm at the end of the experiment. In addition, the average growth rate was 1.27 cm per day, with a standard deviation of 1.44 cm. During the investigation, the lowest growth rate was 0 cm, while the highest was 7 cm. The average temperature in the lab was 51.8 Celsius, and the standard deviation was 1.66 Celsius. The temperature range was from 40 degrees Celsius to 61 degrees Celsius. Furthermore, the humidity averaged 51.8%, and the standard deviation was 5.78 %. The humidity in the lab environment ranged from 40% to 61%. Lastly, the most crucial variable, the frequency of the touch stimulation, had a mean value of 28.66 seconds, and the standard deviation was 5.78 seconds. As some plants were untouched while others were touched, the range of touch stimulation is from 0 to 44 seconds.

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As with the number of observations made in Kale, 45 observations were made during the experiment. The mean vertical rate is 11.96 cm, and the standard deviation is 7.23 cm. In addition, the size of the Cornflower ranged from 2.3 cm to 29 cm. The average growth rate was 1.18 cm per day, with a standard deviation of 1.36 cm. The range of the growth of a plant during the whole experiment is from 0 to 5.5 cm. Moreover, the temperature and the humidity were observed to be the same in terms of mean, standard deviation, minimum and maximum value. However, the frequency statistics were different: the average standard deviation of the frequency in Cornflower was 30 seconds, and the standard deviation was 21.47 seconds. Unlike the frequency of touch stimulations in Kale, it ranged from 0 to 46 seconds.

287

4.2 Explanation of the Growth being Touched and Untouched *UDSK 7KH (IIHFW RI 7RXFK 6WLPXODWLRQ RQ .DOH¶V 9HUWLFDO /HQJWK

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Kale_1 (Touched)

Touched: 0.3571 Untouched: 1.4221

Kale_2 (Untouched)

Untouched (3 weeks): 0.1552 Untouched (2 weeks): 0.7857

Kale_3 (Touched)

Touched: 0.1815 Untouched: 0.9893

This data indicates that touch stimulation affects Kales's growth as the plants with the frequency of 0 seconds have a different vertical length and growth rate compared to the stimulated plants. This not only shows the significance of touch stimulation but also shows that a faster rate of touch stimulation allows the plants to grow faster than the ones that were not stimulated or had a faster rate of stimulation. This is supported by K1, the tallest plant grown through the experiment, as it had a faster frequency rate (42 seconds) than K3, which had a slower touch stimulation acting upon the plants. On the other hand, K2, a plant that was not stimulated at all, had a maximum size of approximately 15 cm, which was estimated to be two times shorter than the ones that were mechanically stimulated. The scatter plot shows that the space between the dots in the post-treatment period is larger than the space between the dots in the treatment period for the treatment groups. For example, the non-touched plant has only grown 46% of the vertical length of the touched plant. This shows that the growth rate for the treatment group’s plants increased in the post-treatment period compared to the treatment period. Overall, the treatment group's total growth amount is higher than the control group. In addition, the slope of the graph on the left indicates that the touched plants are likely to be benefitted in terms of their growth when it is frequently touched. This shows that thigmomorphogenesis has a quantifiable impact on plant growth but that most of the plant growth only occurs in the post-treatment (post-thigmomorphogenesis) period.

288

4.3 Explanation of the Effect of Frequency on Plants *UDSK 7KH (IIHFW RI )UHTXHQF\ RQ WKH 9HUWLFDO /HQJWK RI &RUQIORZHUV

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Cornflower_1 (Untouched)

Untouched (3 weeks): 0.1795 Untouched (2 weeks): 0.3972

Cornflower_2 (Touched)

Touched: 0.3990 Untouched: 1.3694

Cornflower_3 (Touched)

Touched: 0.2706 Untouched: 1.2342

This data shows the effect of frequency on the vertical length of Cornflowers. Similar to the data from the Kales’ vertical growth, the plant without a touch stimulation had a way shorter height than those touched. This also shows that the non-stimulated plants are likely to grow shorter than the stimulated ones. This is supported by the graph inserted on the top: it indicates that the stimulated Cornflowers are taller than the non-touched Cornflowers. Just like Kales, a more frequently stimulated plant, Cornflowers have a faster growth rate than the slower and non-stimulated ones. Within the treatment group, a lower frequency of touch stimulation is correlated with a higher rate of growth with a touch stimulation frequency of 44 seconds. However, CF1 had a touch stimulation frequency of 46 seconds with a height of 28.2cm. In addition, the stimulated plants grew faster in the last two weeks of the experiment without the stimulation. On the other hand, the untouched plant did not grow taller but rather had constant growth. The untouched Cornflowers showed that they grew 57% of the total average height of cornflowers. In addition, the slope of the graph on the left indicates that the touched plants are likely to be benefitted in terms of their growth when it is frequently stimulated. This indicates that touch affects their growth with a little of the frequency of touch stimulations.

289

4.4 Explanation of the Effect of Frequency on the Growth Rate *UDSK 7KH (IIHFW RI )UHTXHQF\ RQ WKH *URZWK 5DWH

This graph illustrates the plants’ growth affected by the frequency of the touch stimulation. All the plants experienced a minute increase in their height for the 3 weeks of the experiment. However, the growth rate of the plants has significantly increased since the stimulation stopped; the top six plots for each frequency are the growth rate measured after the stimulation was complete for the remaining two weeks. In addition, it reveals the difference between the growth of the touched and untouched plants, except for the plant with a frequency of 42 seconds. It is seen that the highest growth of the plant with a frequency of 42 seconds has a maximum growth rate of 4 cm, which is the same as the untouched plants. Yet, for other plants with a growth recurrency level longer than 42 seconds, the growth rate significantly differs from those that took shorter to re-interact with the Arduino Servo Motor. This graph additionally explains that the most appropriate frequency should be 44 seconds among the frequency levels. This is because the plant with this frequency has a maximum growth rate of approximately 7 cm, while the ones with a frequency of 46 seconds have a maximum height of 5-6 cm. Therefore, it can be generalized that touch stimulation can increase plants' height and growth rate at a significant range.

9 &RQFOXVLRQ This study investigated how touch stimulation frequency affects plants' growth patterns and morphology. Previous research suggested that mechanical stimulation inhibits plant growth, but plants develop defensive mechanisms when exposed to various touches, possibly leading to expedited growth. To explore this, the growth rate of each plant per day was measured, and it was found that touched plants tend to grow taller and more resilient after the touch stimulation stops due to their defensive mechanisms. Moreover, the growth rate increases once external forces cease. However, this depends on the type of plants they are, as the data explains that vegetables and flowers have different percentages of the growth rate from each other. The experiment's limitations include potential inaccuracies in data collection due to manual measurements and the use of different plant types. Using a single plant type would enhance the correlation between touch stimulation frequency and plant growth. This research holds promise for creating healthier plant growth conditions through thigmomorphogenesis. Faster growth rates could boost food production, improving food security worldwide.

290

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References [1] A. Ritcher, “9 Health Benefits of Kale”, Accessed: Jun. 23, 2023. [Online]. Available: https://www.healthline.com/nutrition/10-proven-benefits-of-kale [2] “Cornflower - Uses, Side Effects, and More,” Accessed: Jun. 28, 2023. [Online]. Available: https://www.webmd.com/vitamins/ai/ingredientmono-414/cornflower [3] Z. Liu, T. Fadiji, J. Yang, Z. Li, and F. Tchuenbou-Magaia, “Impact of mechanical stimulation on the life cycle of horticultural plant,” Hortic. Plant J., vol. 9, no. 3, pp. 381–394, Jun. 2023, doi: 10.1016/j.hpj.2023.01.003. [4] E. W. Chehab, E. Eich, and J. Braam, “Thigmomorphogenesis: a complex plant response to mechano-stimulation,” J. Exp. Bot., vol. 60, no. 1, pp. 43–56, Nov. 2008, doi: 10.1093/jxb/ern315. [5] R. Ghosh, A. Barbacci, and N. Leblanc-Fournier, “Mechanostimulation: a promising alternative for sustainable agriculture practices,” J. Exp. Bot., vol. 72, no. 8, pp. 2877–2888, Apr. 2021, doi: 10.1093/jxb/erab036. [6] J. Braam and E. W. Chehab, “Thigmomorphogenesis,” Curr. Biol., vol. 27, no. 17, pp. R863– R864, Sep. 2017, doi: 10.1016/j.cub.2017.07.008. [7] E. Darwish et al., “Touch signaling and thigmomorphogenesis are regulated by complementary CAMTA3- and JA-dependent pathways,” Sci. Adv., vol. 8, no. 20, p. eabm2091, May 2022, doi: 10.1126/sciadv.abm2091. [8] Washington State University, “Plants can distinguish when touch starts and stops”, [Online]. Available: https://phys.org/news/2023-05-distinguish.html [9] H. Takeishi, “Effects of elevated pressure on rate of photosynthesis during plant growth,” Aug. 2013, doi: 10.1016/j.jbiotec.2013.08.012. [10]N. Tuteja and S. Mahajan, “Calcium Signaling Network in Plants: An Overview,” Plant Signal. Behav., vol. 2, no. 2, pp. 79–85, Mar. 2007, doi: 10.4161/psb.2.2.4176. [11]L. C. T. Scorza and M. C. Dornelas, “Plants on the move: Towards common mechanisms governing mechanically-induced plant movements,” Plant Signal. Behav., vol. 6, no. 12, pp. 1979– 1986, Dec. 2011, doi: 10.4161/psb.6.12.18192. [12]Penn State University, “Calcium Deficiency.” Accessed: Jul. 12, 2023. [Online]. Available: https://plantscience.psu.edu/research/labs/roots/methods/methods-info/nutritional-disordersdisplayed/calcium-deficiency [13]J. Braam, “In touch: plant responses to mechanical stimuli,” New Phytol., vol. 165, no. 2, pp. 373–389, Feb. 2005, doi: 10.1111/j.1469-8137.2004.01263.x. [14]The University of Minnesota Extension, “Lighting for indoor plants and starting seeds”, [Online]. Available: https://extension.umn.edu/planting-and-growing-guides/lighting-indoorplants [15]“Ornamental Production”, [Online]. Available: https://aggiehorticulture.tamu.edu/ornamental/a-reference-guide-to-plant-care-handling-andmerchandising/light-temperature-and-humidity/ [16]Jennifer B. Morgan and Erin L. Connolly, “Plant-Soil Interactions: Nutrient Uptake”, [Online]. Available: https://www.nature.com/scitable/knowledge/library/plant-soil-interactionsnutrient-uptake-105289112/ [17]“How Plants Use Water,” Mar. 2021, Accessed: Jul. 26, 2023. [Online]. Available: https://extension.wvu.edu/lawn-gardening-pests/news/2021/03/01/how-plants-use-water

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[18]F. P. Hartmann, E. Tinturier, J.-L. Julien, and N. Leblanc-Fournier, “Between Stress and Response: Function and Localization of Mechanosensitive Ca2+ Channels in Herbaceous and Perennial Plants,” Int. J. Mol. Sci., vol. 22, no. 20, p. 11043, Oct. 2021, doi: 10.3390/ijms222011043.

311

A Study on the Identification and Solution of Staphylococcus aureus and E. coli Resistance to Antibacterial Copper Ions in Soil Contaminated with Copper ion (Cu 2+) Author 1

Full Name

Chung, Seungah

Cheongshim International Academy

(Last Name, First Name)

School Name

ABSTRACT Through this study, the following facts were confirmed for the first time: in soil with high concentrations of antibacterial copper ions, Escherichia coli and Methicillin-resistant Staphylococcus aureus (MRSA) increase the thickness of their cell walls, thereby increasing their ability to withstand osmotic stress, and these thickened cell walls also develop resistance to various antibiotics and copper ions. This research is significant because it confirms for the first time that antibiotic-resistant bacteria can arise not only due to antibiotics but also from other environmental conditions. To suppress this phenomenon, the study proposed a solution to administer soil bacteria that adsorb copper ions to soil with high concentrations of copper ions, thereby removing the copper ions from the soil. This prevents the thickening of the cell walls of E. coli and MRSA, thus preventing them from developing resistance to antibiotics and copper ions.

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1. INTRODUCTION and GOAL Escherichia coli (E.coli) gram negative bacteria, belongs to the bacillus(0.4~0.7×1~30ห)

Figure 1: Source of Escherichia coli electron microscopy image: Rocky Mountain Laboratories, NIAID, NIH. Staphylococcus aureus gram positive bacteria, coccus , (0.5~1.2ห)

Figure 2: The source of the electron microscope photograph of Staphylococcus aureus is not specific enough. It is recommended to provide a more detailed and reliable source for the photograph. Staphylococcus aureus is a pathogenic bacterium that can cause various severe diseases, including endocarditis, skin infections, pneumonia, osteomyelitis, and sepsis, as well as food poisoning. Symptoms of Staphylococcus aureus food poisoning include vomiting, dizziness, weakness, and abdominal pain due to the toxin produced by the bacteria. Staphylococcus aureus can contaminate meat or vegetables through food handling or be transferred to other foods by workers' hands. About 30% of healthy people carry Staphylococcus aureus, and Methicillin-resistant Staphylococcus aureus (MRSA), a multidrug-resistant bacteria, has emerged, which is resistant to various antibiotics. According to the Korea Centers for Disease Control and Prevention, 70% of the tested subjects were confirmed to be carrying MRSA. Bacteria acquire resistance to substances that negatively affect their survival, such as antibiotics, through mutations. As a result, many patients suffer from serious problems when multidrugresistant Staphylococcus aureus appears, infecting immunocompromised patients through hospitalacquired infections. Tuberculosis bacteria that are resistant to various antibiotics have also emerged, making tuberculosis a disease that requires hospitalization for several months. This study aimed to investigate whether Escherichia coli and Staphylococcus aureus have resistance to substances that negatively affect their growth, except for antibiotics, and to find ways to suppress the occurrence of

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these bacteria. Copper, which is recognized for its antimicrobial properties, was selected as the target substance for this study. Research on the bactericidal ability of copper has been ongoing for about ten years, and it has been found that copper ions react with oxygen to produce hydrogen peroxide and then form hydroxyl radicals, destroying the bacterial cell membrane. In the case of viruses, copper enters the virus and replaces the iron (Fe) and zinc (Zn) atoms of essential viral proteins, impairing their function.

Figure 3: copper ion(Cu2+) Mechanism of antimicrobial capability (Source: Google) Additionally, a newly discovered antiviral mechanism of copper ions is as follows: when a virus comes into contact with a copper surface, it recognizes the copper ions as a host and tries to release its DNA/RNA into the host's interior. However, the copper ions (Cu2+) create a signal that interferes with the replication signal of the genetic material, preventing the virus from proliferating. This new principle has been discovered.

Figure 4: Newly discovered mechanism of antiviral capability of copper ions (Cu2+) However, when the concentration of copper ions increases in the soil, copper becomes an essential trace element required for the survival of organisms, but it also becomes toxic to them. Studies have reported that high concentrations of copper ions are biologically toxic to both plants [1] and animals [2]. High concentrations of copper in the soil have also been reported to cause a decrease in soil bacteria that form the basis of organic matter cycling. In humans, it has been found to be a possible cause of Alzheimer's disease. This study aims to investigate the effects of copper ions in soil.

2. METHODS 2-1 Culture of Escherichia coli and Staphylococcus aureus in soil with high concentrations of copper ions detected. ཛSoil was collected from 10 locations in Seoul, and 1 g of each soil sample was mixed with 10 mL of

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distilled water, and then centrifuged at 6000 revolutions per minute for 10 minutes. The soil solution was separated and placed in a 15 mL conical tube, which was stored in a refrigerator. ཛྷUsing a micropipette, 100 ȝL of the soil solution was added to a kit that allowed for the detection of copper ion concentration by observing color changes. The results showed that all 10 soil samples collected from Seoul contained high concentrations of copper ions. ཝThe soil collected from Yongsan area (as in step 2) had the highest concentration of copper ions. The concentration was then converted to the content of copper ions per kg of soil. ཞBased on the results from step 3, 100 ȝL of the soil solution from the soil in Dongjak-gu, Yongsangu, and Seongbuk-gu with the highest concentrations of copper ions were inoculated into a selective culture medium for Pseudomonas fluorescens and EscherichiD FROL DQG FXOWXUHG IRU KRXUV DW ႏ after spreading the sample using a sterilized metal spreader for 3-4 minutes. ཟAfter the completion of the culturing process, the presence of Pseudomonas fluorescens and Escherichia coli in the selective culture medium for the soil samples with the highest concentrations of copper ions in Dongjak-gu, Yongsan-gu, and Seongbuk-gu was examined 2-2 The separation of copper ions from the soil and the collection of the isolated copper ions were conducted using a commercially available copper ion extraction kit according to the manufacturer's instructions." ཛIn Nutrient Broth (NB) containing added copper ion (CuSO4) (8 g NB (Difco Lab), 0.3 g CuSO4㺃 5H2O, 1 L DW, pH 7), 3 ml of liquid culture medium is inoculated with 100 ȝl of soil aqueous solution H[WUDFWHG IURP <RQJVDQ VRLO DQG LQFXEDWHG IRU KRXUV LQ D VWLUULQJ LQFXEDWRU DW D WHPSHUDWXUH RI ႏ ཛྷNutrient Broth agar plate medium containing copper ion (CuSO4) is prepared (8 g NB (Difco Lab), 0.3 g CuSO4㺃5H2O, 15 g agarose gel powder, 1 L DW, pH 7). A 10 ȝl inoculum is plated and incubated DW ႏ IRU KRXUV 7KH UHDVRQ IRU FXOWXULQJ DW ႏ D KLJKHU WHPSHUDWXUH WKDQ W\SLFDO EDFWHULDO JURZWK conditions (28- ႏ LV WKDW EDFWHULD WKDW JURZ XQGHU FRSSHU WR[icity conditions grow relatively well at D KLJK WHPSHUDWXUH ႏ FRPSDUHG WR RWKHU EDFWHULD ཝAfter undergoing the processes in ཛ-ཛྷ, the bacteria that absorb copper ions into their cell walls store copper ions present in the soil on their own cell walls (copper ions are present in the medium). The soil bacteria that remove copper ions by attaching them to their cell walls are cultured on a culture medium, which is then placed in a high-temperature and high-SUHVVXUH VWHULOL]HU DW ႏ DQG EDU IRU 15 minutes. Although the copper ions attached to the cell walls of the soil bacteria that remove copper ions by adsorbing them onto their cell walls undergo no significant changes, the bacteria themselves are destroyed due to the high temperature and pressure. The culture medium that contains soil bacteria that remove copper ions by adsorbing them onto their cell walls after undergoing the sterilization process is placed back into a syringe and passed through a microfilter with a pore size of 0.2 ȝm attached to the syringe after being sterilized. This process produces a solution containing an aqueous solution containing copper ions. ཞA kit is used to determine the concentration of copper ions in the solution obtained in ཝ by observing color changes. 2-3 Identification of antibiotic resistance of Escherichia coli and Staphylococcus aureus separated from soil detected in high concentrations of copper ions. ཛIn Experiment 4-1 Escherichia coli and Staphylococcus aureus were collected from the selectively cultured medium and inoculated into 3 ml of liquid culture medium containing 200 g/mL of antibiotics, namely methicillin and streptomycin. The culture was incubated at 37°C in a shaking incubator for 12 hours.

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ཛྷOne milliliter of the liquid culture medium from step 1 was transferred into a cuvette, and the absorbance was measured at 600 nm using a UV-spectrophotometer to determine the existence of any strains of E. coli or S. aureus resistant to the antibiotics methicillin and streptomycin. ཝThe experimental process described in steps 1-2 was repeated using normal E. coli and S. aureus as a control group. 2-4 Identification of antibiotic resistance of E. coli and Staphylococcus aureus isolated from soil samples with high concentrations of copper ions. ཛ Through the research process, it was confirmed that both E. coli and Staphylococcus aureus, which have resistance to high concentrations of copper ions, also have resistance to antibiotics such as methicillin and streptomycin. E. coli and S. aureus were cultured on agar plates and inoculated with 10 l of the culture onto 3 ml of liquid medium. Then, a solution containing copper ions (10-100 l) was added to the mixture, which was then incubated for 12 hours in a shaking incubator at 37°C. ཛྷ To determine the presence of E. coli and S. aureus with resistance to copper ions, which have antibacterial effects, 1 ml of the liquid culture medium from ཛ is put into a cuvette and the absorbance is measured at 600 nm using a UV-spectrophotometer. ཝ The research process in steps 1 and 2 is conducted with normal E. coli and S. aureus as control groups. 2-5 Confirmation of resistance to osmotic stress was found in E. coli and Staphylococcus aureus, which were also found to be resistant to copper ions and antibiotics. ཛ Through the research process, it was confirmed that E. coli and Staphylococcus aureus, which are resistant to high concentrations of copper ions, are also resistant to the antibiotics methicillin and VWUHSWRP\FLQ 7R FXOWXUH LQRFXODWH ȝO RI FXOWXUH PHdium containing E. coli and Staphylococcus DXUHXV LQ PO RI OLTXLG FXOWXUH PHGLXP DQG DGG PO RI 1D&O VROXWLRQ ,QFXEDWH DW ႏ IRU hours in a shaking incubator. ཛྷ To determine the response of E. coli and S. aureus with resistance to copper ions, which have antibacterial effects, to osmotic stress, transfer 1 mL of the liquid culture medium from step 1 into a cuvette and measure the absorbance at 600nm using a UV-spectrophotometer. ཝ The research process described in steps 1-2 was repeated using normal E. coli and S. aureus as the control group. 2-6 Identification of soil proliferation and plant contamination by E. coli and Staphylococcus aureus, which were found to be resistant to copper ions and antibiotics. ཛDuring the research process, it was confirmed that both E. coli and Staphylococcus aureus that are resistant to high concentrations of copper ions are also resistant to antibiotics such as methicillin and VWUHSWRP\FLQ $IWHU LQRFXODWLQJ ȝO RI WKH FXOWXre medium containing these bacteria into 4g of gardening soil, plant seeds (cabbage) were planted and grown at room temperature for a week. ཛྷThe leaves of the cabbage that were grown for a week were collected and placed in a 1.5 ml microtube containing 1 ml of liquid culture medium, which was stored at room temperature. ཝ$IWHU LQRFXODWLQJ ȝO RI WKH OLTXLG FXOWXUH PHGLXP IURP VWHS LQWR PO RI OLTXLG FXOWXUH PHGLXP DQG SODFLQJ LW LQ D VKDNLQJ LQFXEDWRU PDLQWDLQHG DW ႏ LW ZDV FXOWXUHG IRU KRXUV ཞBy placing 1 ml of the liquid culture medium from step 3 in a cuvette and measuring the absorbance at a wavelength of 600 nm with a UV-SPECTROPHOTOMETER, it is possible to confirm whether E. coli and Staphylococcus aureus, which have resistance to copper ions with antimicrobial effects, have multiplied on the leaves of the plant. Repeat the steps 1-4 using normal E. coli and Staphylococcus aureus as control groups. ཟCollect 0.1 g of soil on which the cabbage was grown and place it in a 15 ml conical tube. Add 10 ml of tertiary distilled water and shake well to mix the soil and tertiary distilled water. Then, centrifuge

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the mixture at 6000 rpm for 1 minute using a centrifuge to separate the solution containing the soil components. ཡ,QRFXODWH ȝO RI WKH VROXWLRQ FRQWDLQLQJ WKH VRLO FRPSRQHQWV LQWR PO RI OLTXLG FXOWXUH PHGLXP PL[HG ZLWK ȝO RI PHWKLFLOOLQ DQG VWUHSWRP\FLQ DQG FXOWXUH LW IRU KRXUV LQ D VKDNLQJ LQFXEDWRU PDLQWDLQHG DW ႏ རBy placing 1 ml of the liquid culture medium from step 7 in a cuvette and measuring the absorbance at a wavelength of 600 nm with a UV-SPECTROPHOTOMETER, it is possible to confirm whether E. coli and Staphylococcus aureus, which have resistance to copper ions with antimicrobial effects, have multiplied in the soil. 2-7 Confirmation of obtaining copper ion resistance by E. coli and Staphylococcus aureus grown under conditions containing copper ions. ཛ,QRFXODWH ȝO of cultured media containing normal Escherichia coli and yellow Staphylococcus DXUHXV LQWR PO RI OLTXLG FXOWXUH PHGLD $GG ȝO RI D VROXWLRQ FRQWDLQLQJ FRSSHU LRQV DQG FXOWXUH IRU KRXUV DW ႏ LQ D VKDNLQJ LQFXEDWRU ཛྷ$IWHU FRPSOHWLQJ WKH FXOWXUH IURP VWHS FROOHFW ȝO RI WKH OLTXLG FXOWXUH PHGLD DQG LQRFXODWH LW LQWR PO RI IUHVK OLTXLG FXOWXUH PHGLD $GG ȝO RI D VROXWLRQ FRQWDLQLQJ FRSSHU LRQV DQG FXOWXUH IRU KRXUV DW ႏ LQ D VKDNLQJ LQFXEDWRU ཝ5HSHDW VWHSV DQG WHQ WLPHV 7KHQ LQRFXODWH ȝO RI WKH ILQDO FXOWXUHG PHGLD RQWR D 3HWUL GLVK containing solid culture media. Spread it evenly using a spreader, place a disk filter that has absorbed copper ions on top of the solid culture media, and store it in a constant temperature incubator for 12 hours. If the Escherichia coli and yellow Staphylococcus aureus, which have undergone the research process, become resistant to copper ions, they will grow normally around the disk filter that has absorbed copper ions. ཞ5HSHDW VWHSV DQG WHQ WLPHV $IWHU WKH ILQDO FXOWXUH LQRFXODWH ȝO RI WKH OLTXLG FXOWXUH PHGLD LQWR PO RI IUHVK OLTXLG FXOWXUH PHGLD 0L[ ZLWK ȝO RI D VROXWLRQ FRQWDLQLQJ FRSSHU LRQV DQG FXOWXUH IRU KRXUV DW ႏ LQ D VKDNLQJ LQFXEDWRU 3ODFH 1 ml of the liquid culture media from step 4 into a cuvette and measure the absorbance at 600 nm using a UV-spectrophotometer. This will determine whether Escherichia coli and yellow Staphylococcus aureus have become resistant to copper ions. 2-8 Confirm the antibiotic resistance of E. coli and Staphylococcus aureus that have acquired copper ion resistance. ཛIn Experiment 4.7, E. coli and S. aureus were isolated and cultured on a selective agar medium. From the cultured medium, E. coli and S. aureus were collected and inoculated into 3ml of liquid culture PHGLXP FRQWDLQLQJ ȝO RI WKH DQWLELRWLFV PHWKLFLOOLQ and streptomycin. The mixture was then LQFXEDWHG DW ႏ LQ D VKDNLQJ LQFXEDWRU IRU KRXUV ཛྷTo determine whether there is resistance to the antibiotics methicillin and streptomycin in E. coli and S. aureus, 1 milliliter of the liquid culture medium from step 1 was placed in a cuvette, and the absorbance at 600nm was measured using a UV-spectrophotometer. ཝThe experimental procedure in steps 1-2 was repeated, but a control group was included using normal E. coli and S. aureus. 2-9 Inhibiting the resistance of E. coli and Staphylococcus aureus to copper ions using bacteria that adsorb copper ions ཛ,QRFXODWH ȝO RI D FXOWXUH PHGLXP FRQWDLQLQJ VRLO EDFWHULD WKDW UHPRYH FRSSHU LRQV E\ DGVRUSWLRQ onto 4g of soil for use in horticulture, and store it at room temperature for one week. ཛྷTake 0.1g of soil from step 1 and put it in a 15ml conical tube. Then, add 10ml of tertiary distilled water and shake well to mix the soil and tertiary distilled water. Centrifuge the mixture at 6000 rpm for 1 minute to separate the soil and its components from the mixed solution.

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ཝPrepare Nutrient Broth (NB (Difco Lab) 8g, CuSO4㺃5H2O 0.3g, 1L DW, pH 7) by adding copper LRQV &X62 WR ȝO RI WKH PL[HG VROXWLRQ FRQWDLQLQJ VRLO FRPSRQHQWV IURP VWHS ,QRFXODWH PO RI liquid culture medium with the mixed solution and culture for 12 hours in a shaking incubator PDLQWDLQHG DW ႏ ཞThe absorbance at 600nm wavelength can be measured using a UV-spectrophotometer to determine whether the soil bacteria that adsorb copper ions from the soil have proliferated. ཟPut 1ml of a solution containing copper ions into the soil (4g) where the copper ion-adsorbing bacteria KDYH SUROLIHUDWHG DQG VWRUH LW DW URRP WHPSHUDWXUH IRU RQH ZHHN ,QRFXODWH ȝO RI D FXOWXUH PHGLXP in which Escherichia coli and Staphylococcus aureus have been cultured onto the soil, which has been stored for one week. Then, refer to previous research to determine whether Escherichia coli and Staphylococcus aureus have developed resistance to copper ions and antibiotics.

3. RESULTS 3-1 Culture of Escherichia coli and Staphylococcus aureus in soil with high concentrations of copper ions detected.

ཛJongno-guཛྷYongsan-gu DistrictཝDongdaemun-gu DistrictཞSeongbuk-gu Districtཟ Dobong-gu DistrictའSeodaemun-gu DistrictཡGuro-gu DistrictརDongjak-guལYangcheon-gu DistrictཤGangseo-gu Figure 5: Soil samples collected from 10 locations in Seoul

1-10 Soil samples collected from each area of the Seoul Metropolitan Government" C: Copper ion kit treated with tertiary distilled water Figure 6: Identification of copper ion levels in soil collected from 10 locations in Seoul It was confirmed that all 10 soil samples collected in Seoul contained a high concentration of copper ions. In particular, the soil sample (ཛྷ) collected in the Yongsan area showed the highest concentration of copper ions. When converted to the copper ion content per kilogram of soil, the results are as follows:

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Copper ion concentration (mg/kg) Copper Ion Soil Contamination Concern Criteria 150mg/kg Approximately 171 mg/kg ཛJongno-gu District About 310 mg/kg ཛྷYongsan-gu District About 182 mg/kg ཝDongdaemun-gu District Approximately 193 mg/kg ཞSeongbuk-gu District Approximately 177 mg/kg ཟDobong-gu District Approximately 181 mg/kg འSeodaemun-gu District Approximately 177 mg/kg ཡGuro-gu District Approximately 188 mg/kg རDongjak-gu Approximately 154 mg/kg ལYangcheon-gu District Approximately 159 mg/kg ཤGangseo-gu District Table 1. Concentration of copper ions in 10 areas of Seoul (mg/kg) Based on the results of this study, soil samples were collected from Dongjak-gu, Yongsan-gu, and Seongbuk-gu, where the concentration of copper ions was found to be very high. The presence of Escherichia coli and Staphylococcus aureus in these soils was investigated.

Figure 7: Determination of the presence of E. coli and Staphylococcus aureus in the soil collected from Dongjak-gu, Yongsan-gu, and Seongbuk-gu, where the concentration of copper ions was found to be very high among the soil samples collected from 10 locations in Seoul. The media used in the study were selective culture media for E. coli and S. aureus only, and they were used to culture soil samples collected from Dongjak-gu, Yongsan-gu, and Seongbuk-gu to investigate the presence of these bacteria. E. coli was found in the soil samples from Dongjak-gu, while S. aureus was found in the soil samples from Dongjak-gu and Yongsan-gu. 3-2 Separation of copper ions from soil and collection of copper ions

Figure 8: Cultivation of soil bacteria that adsorb and remove copper ions from the soil collected in Yongsan-gu, where the concentration of copper ions was found to be very high among the soil samples collected from 10 locations in Seoul. Based on the confirmation of high copper ion concentrations in the soil of Yongsan-gu, the area with the highest concentration of copper ions, soil bacteria were isolated by adsorbing copper ions onto the cell wall of the bacteria to prevent them from being affected by copper's antibacterial properties. These bacteria were cultured and gradually formed colonies with a characteristic copper color by absorbing copper ions in the culture medium.

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Figure 9: Identification of copper ions adsorbed and removed by soil bacteria from the soil collected in Yongsan-gu, which has a high concentration of copper ions, onto the cell wall. After cultivating soil bacteria that adsorb copper ions onto the cell wall, an aqueous solution containing copper ions was obtained through sterilization and filtration. It was found that the amount of aqueous solution containing copper ions obtained increases as the amount of culture medium containing soil bacteria that adsorb and remove copper ions increases. 3-3 Identification of antibiotic resistance of Escherichia coli and Staphylococcus aureus separated from soil detected in high concentrations of copper ions

Figure 10: Liquid culture medium for normal E. coli and Staphylococcus aureus used in research

A: E. coli grown in soil with high concentrations of copper ions B: Staphylococcus aureus grown in soil with high concentrations of copper ions. C: Normal E. coli D: Normal Staphylococcus aureus A': E. coli grown in soil with high concentrations of copper ions B': Staphylococcus aureus grown in soil with high concentrations of copper ions C': Normal E. coli D': Normal Staphylococcus aureus Figure 11: Identification of antibiotic resistance in Escherichia coli and Staphylococcus aureus isolated from soil samples with high concentrations of copper ions using normal E. coli and Staphylococcus aureus in liquid culture medium In the research process, Methicillin and Streptomycin were used as antibiotics, and they have different methods of killing bacteria. Methicillin attacks and destroys the cell wall of bacteria, while Streptomycin suppresses the synthesis of 16S proteins, preventing bacteria from synthesizing DNA normally and leading to bacterial death. It was confirmed that Escherichia coli and Staphylococcus

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aureus, which have overcome the antibacterial properties of copper in soil with high concentrations of copper ions, are resistant to Methicillin and Streptomycin 3-4 Identification of antibiotic resistance of E. coli and Staphylococcus aureus isolated from soil samples with high concentrations of copper ions.

A: E. coli grown in soil with high concentrations of copper ions B: Staphylococcus aureus grown in soil with high concentrations of copper ions. C: Normal E. coli D: Normal Staphylococcus aureus A': E. coli grown in soil with high concentrations of copper ions B': Staphylococcus aureus grown in soil with high concentrations of copper ions C': Normal E. coli D': Normal Staphylococcus aureus Figure 12:. E. coli and Staphylococcus aureus isolated from soil with high concentrations of normal E. coli and Staphylococcus aureus and copper ion Check resistance to copper ions 3-5 Confirmation of resistance to osmotic stress was found in E. coli and Staphylococcus aureus, which were also found to be resistant to copper ions and antibiotics.

A: E. coli grown in soil with high concentrations of copper ions B: Staphylococcus aureus grown in soil with high concentrations of copper ions. C: Normal E. coli D: Normal Staphylococcus aureus A': E. coli grown in soil with high concentrations of copper ions B': Staphylococcus aureus grown in soil with high concentrations of copper ions C': Normal E. coli D': Normal Staphylococcus aureus Figure 13: Check the resistance of E. coli and Staphylococcus aureus isolated from soil samples with high concentrations of copper ions, using normal E. coli and Staphylococcus aureus in liquid culture medium, against copper ions E. coli and Staphylococcus aureus, which have overcome the antibacterial properties of copper in soil with high concentrations of copper ions, It was confirmed through research that it is possible

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to overcome the antibacterial effect of copper and grow it even under the conditions of the presence of high concentrations of copper ions, and that it has resistance to antibiotics. And the study confirmed that the ability to withstand osmotic stress increased significantly, which means that the cell walls of E. coli and Staphylococcus aureus are thickened. Taken together, it was concluded that E. coli and Staphylococcus, which survived in soil with high concentrations of copper ions, thickened the cell wall, increased the ability to withstand osmotic stress, and greatly increased physical resistance to copper ions and antibiotics. This is evidence that it did not go through the process of obtaining antibiotic resistance by general mutations. 3-6 Identification of soil proliferation and plant contamination by E. coli and Staphylococcus aureus, which were found to be resistant to copper ions and antibiotics.

A: E. coli soil inoculation in soil with high concentrations of copper ions B: Staphylococcus yellow soil inoculation in soil with high concentrations of copper ions C: Normal E. coli soil inoculation D: Normal Staphylococcus soil inoculation Figure 14: Check the resistance of E. coli and Staphylococcus aureus isolated from soil samples with high concentrations of copper ions, using normal E. coli and Staphylococcus aureus in liquid culture medium, against copper ions Check the resistance of E. coli and Staphylococcus aureus isolated from soil samples with high concentrations of copper ions, using normal E. coli and Staphylococcus aureus in liquid culture medium, against copper ions

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Compared to normal E. coli and Staphylococcus, it was found that E. coli and Staphylococcus resistant to copper ions and antibiotics, as well as those resistant to osmotic stress, proliferated faster in the soil. 3-7 Confirmation of obtaining copper ion resistance by E. coli and Staphylococcus aureus grown under conditions containing copper ions.

A: Low concentration of copper ions (Cu) in 10 incubations2+E. coli exposed B: Normal E. coli C: Low concentration of copper ions in 10 incubations (Cu)2+) Exposed Staphylococcus aureus D: Normal Staphylococcus aureus Figure 16: Confirmation of copper ion resistance of normal E. coli and Staphylococcus aureus when cultured under low copper ion concentration conditions (1). Normal E. coli and Staphylococcus aureus were repeatedly cultured under conditions containing low concentrations of copper ions that did not produce antibacterial effects on them. It was confirmed that E. coli and Staphylococcus, which can withstand high concentrations of copper ions, appeared. This suggests that E. coli and Staphylococcus aureus grown in soil containing copper ions can acquire resistance to copper ions.

A1-A10: Low concentration of copper ions in 10 incubations (Cu)2+E. coli exposed B1-B10: Normal E. coli C1-C10: Low concentration of copper ions in 10 incubation processes (Cu)2+) Exposed Staphylococcus aureus D1-D10: Normal Staphylococcus aureus

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A: Low concentration of copper ions (Cu) in 10 incubations2+E. coli exposed B: Normal E. coli C: Low concentration of copper ions in 10 incubations (Cu)2+) Exposed Staphylococcus aureus D: Normal Staphylococcus aureus Figure 17: Confirmation of copper ion resistance of normal E. coli and Staphylococcus aureus when cultured under low copper ion concentration conditions (2). Normal E. coli and Staphylococcus aureus were repeatedly cultured under conditions containing low concentrations of copper ions that did not produce antibacterial effects, and it was confirmed that E. coli and Staphylococcus strains that can withstand high concentrations of copper ions appeared. The resistance to copper ions was further confirmed through absorbance measurement, indicating that E. coli and Staphylococcus aureus grown in soil containing copper ions can acquire resistance to copper ions. 34-8 Confirm the antibiotic resistance of E. coli and Staphylococcus aureus that have acquired copper ion resistance.

A: Low concentration of copper ions (Cu) in 10 incubations2+E. coli exposed B: Normal E. coli C: Low concentration of copper ions in 10 incubations (Cu)2+) Exposed Staphylococcus aureus D: Normal Staphylococcus aureus Figure 18: Determine the resistance of normal E. coli and Staphylococcus to antibiotics by culturing them under low-concentration copper ion conditions. Normal E. coli and Staphylococcus aureus were repeatedly cultured under conditions containing low concentrations of copper ions that did not produce antibacterial effects, confirming the emergence of E. coli and Staphylococcus that can withstand high concentrations of copper ions. This means that E. coli and Staphylococcus aureus grown in soil contaminated with copper ions can acquire resistance to copper ions. Furthermore, it was confirmed that these E. coli and

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Staphylococcus aureus also exhibited resistance to antibiotics, specifically Methicillin and Streptomycin. Therefore, this research directly proves that copper ion-contaminated soil can give rise to antibiotic-resistant E. coli and Staphylococcus aureus. 4-9 Inhibiting the resistance of E. coli and Staphylococcus aureus to copper ions using bacteria that adsorb copper ions

Figure 19. Determination of the growth of soil bacteria that adsorb copper ions in the soil. Soil bacteria that adsorb and remove FRSSHU LRQV UHTXLUH D WHPSHUDWXUH RI ႏ LQ WKH FXOWXUH process. However, the study shows that these bacteria can grow normally even under normal temperature conditions in soil.

Control1: E. coli resistant to methicillin, an antibiotic derived from soil high in copper ions. Control2: Staphylococcus aureus resistant to methicillin, an antibiotic derived from soil high in copper ions. Control3: E. coli resistant to streptomycin, an antibiotic derived from soil high in copper ions Control4: Staphylococcus aureus resistant to streptomycin, an antibiotic derived from soil high in copper ions. A: E. coli grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper B: Staphylococcus aureus grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper. C: E. coli grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper D: Staphylococcus aureus grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper. Figure 20: Check whether antibiotic-resistant E. coli and Staphylococcus aureus are produced in soil where soil bacteria adsorbing copper ions grow.

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The concentration of copper ions in the soil was reduced by using soil bacteria that adsorb and remove copper ions. After inoculating E. coli and Staphylococcus aureus, which are resistant to methicillin and Streptomycin, there were no signs of their growth.

Control1: E. coli resistant to methicillin, an antibiotic derived from soil high in copper ions. Control2: Staphylococcus aureus resistant to methicillin, an antibiotic derived from soil high in copper ions. Control3: E. coli resistant to streptomycin, an antibiotic derived from soil high in copper ions Control4: Staphylococcus aureus resistant to streptomycin, an antibiotic derived from soil high in copper ions. A: E. coli grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper B: Staphylococcus aureus grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper. C: E. coli grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper D: Staphylococcus aureus grown in soil with high concentrations of copper ions inoculated with soil bacteria that adsorbs and removes copper. Figure 21: Determining the presence of E. coli and Staphylococcus aureus that are resistant to copper ions in soil where copper-ion adsorbing soil bacteria grow.

5. DISCUSSION Soil bacteria that adsorb and remove copper ions from the soil reduce the concentration of copper ions in the soil. E. coli and Staphylococcus aureus were inoculated with copper ions, and no resistant strains of E. coli and Staphylococcus aureus appeared. In other words, it was finally confirmed that the soil bacteria that adsorb and remove copper ions on the cell wall are capable of removing copper ions from the soil where they are present at high concentrations, and E. coli and Staphylococcus in this soil cannot obtain resistance to antibiotics.

6. CONCLUSIONS Through this study, it has been confirmed that Escherichia coli and Methicillin-resistant Staphylococcus aureus (MRSA) can develop antibiotic resistance not only due to antibiotics but also due to other environmental factors. This highlights the need to focus on the possibility of antibiotic-resistant bacteria emerging from various environmental factors, not just MRSA, which is currently a major problem. As a result, further research is needed to find solutions to these issues. Based on these findings, future studies will investigate whether antibiotic-resistant bacteria can arise from other factors such as increased acidity or soil temperature.

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7. REFERENCES [1] 㧊⼧㭒. “ῂⰂ(II)Ṗ ㌗㿪㌳㧻㠦 ╖䞲 tetracycline㦮 ☛㎇㠦 ⹎䂮⓪ 㡗䟻 (Effects of copper (II) on tetracycline toxicity to lettuce (Lactuca sativa L.) growth)”, 簙缧繗谷粋繗谷蚭 , ῃ⌊㍳㌂,(2016) [2] 㔶㥺ἓ 㣎 3ⳛ, “☯㭓, Mactra veneriformis㦮㌳㫊, 䢎䦷 ⹥ ₆ὖἚ ῂ㫆㠦 ⹎䂮⓪ ῂⰂ (Cu)㦮 ☛㎇ (Copper Toxicity on Survival, Respiration and Organ Structure of Mactra veneriformis (Bivalvia: Mactridae)” ,The Korean journal of malacology v.29 no.2 ,pp. 129 - 137 , (2013) [3] 䢣㍶䢪㣎 3ⳛ, “Cu ⌊㎇ ⁒ῢ ㎎‶ Alcaligenes sp. KC-1㦮⿚Ⰲ ⹥ ㌳㧻䔏㎇ (Characterization of Growth Inhibition and Isolation of a Copper-Resistant Rhizobacterium, Alcaligenes sp. KC-1)” Korean journal of microbiology and biotechnology v.39 no.2 ,pp. 182 - 187 , (2011) [4] Han, S.H., “Amyloid ȕ-interacting partners in Alzheimer's disease: From accomplices to possible therapeutic targets”, Progress in neurobiology v.137 ,pp. 17 - 38 , (2016) [5] ⹫㧎䢎, ῢ㡗ⳛ, “⿚Ⰲ䞲⺆㿪㡓⪳㼊㦮㡓⪳㏢䡫ὧ㠦 ⹎䂮⓪ ῂⰂ㧊㡾㦮㡗䟻 (Effect of Cupric Sulfate on the Chlorophyll Fluorescence in Isolated Chloroplasts from Chinese Cabbage)”, 䞲ῃ ㌳䢪䞯䣢㰖 v.19 no.3 ,pp. 207 - 212 , (1986) [6] ₖ⹒㭒, ㏷䢣′, “㔳ⶒ ㌳㧻㦚㽟㰚䞶㑮㧞⓪ ῂⰂ ⌊㎇㎎‶㦮⿚Ⰲ (Isolation of copperresistant bacteria with plant growth promoting capability)”, ⹎㌳ⶒ䞯䣢㰖 v.53 no.4 ,pp. 251 - 256 , (2017) [7] 㩫䢣㭒, “Thermococcus onnurineus NA1㦮㩚㌂㫆㩞㧦 domain㦮䔏㎇㡆ῂ : ῂⰂ㧊㡾㧎㰖㩚㌂㫆㩞㧦(CopR)㦮䔏㎇ ἓ䧂╖䞯ᾦ 㧒⹮╖䞯㤦,(2015) [8] https://ibs.re.kr/cop/bbs/BBSMSTR_000000000735/selectBoardArticle.do?nttId=21096&pageIndex= 1&searchCnd=&searchWrd= [9] Detection of antibiotic-resistant Escherichia coli from the feces of the Oriental magpie nestlings (₢ 䂮(Pica serica) 㥶㫆(蛕複) ⺆㍺ⶒ㠦㍲㦮䟃㌳㩲㩖䟃㎇㦚㰖┢ ╖㧻‶(Escherichia coli)㦮䌦㰖) Kim, Yong Woo , Choe, Jae Chun , Jablonski, Piotr G. , Lee, Sang-im The Korean journal of ornithology v.27 no.1 ,pp. 3 - 9 , 2020 , 1225-9179 , The Ornithological Society [10] ῃ⌊ ㌆㠛☯ⶒ 㥶⧮ ╖㧻‶㦮䟃㌳㩲㩖䟃㎇⿚䙂㢖㩚䕢 Ṗ⓻ ₆㩚㠦 ὖ䞲㡆ῂ (Plasmid-mediated Multidrug Resistant E. coli from Food Animals in Korea : Molecular Aspects and Potential) 䞲㰖㤦 (㩚⋾╖䞯ᾦ ╖䞯㤦)2015 , 117 , 㩚⋾╖䞯ᾦ ╖䞯㤦 , ῃ⌊⹫㌂ [11] Ⱎ⓮㯯㻾Ṗ 㣪ῂ⯊䔎㦮䛞㰞䔏㎇ ⹥ 䟃㌳㩲㩖䟃㎇䢿㌟䙂☚㌗ῂ‶ KCCM 40510 㠋㩲䢲㎇ (Quality Characteristics and Inhibitory Activity against Staphylococcus aureus KCCM 40510 of Yogurts Manufactured with Garlic Juice)㧊㔏′ (⏣㽳㰚䦻㼃 ῃⰓ㿫㌆ὒ䞯㤦) , 䞾㭖㌗ (⏣㽢㰚䦻㼃㿫㌆ὒ䞯㤦) , 㧊㡆㩫 (⏣㽢㰚䦻㼃㿫㌆ὒ䞯㤦) , ₖ⹒ἓ (⏣㽢㰚䦻㼃 ῃⰓ㿫㌆ὒ䞯㤦) , 䞲₆㎇ (⏣㽢㰚䦻㼃㿫㌆ὒ䞯㤦) , 㩫㍳⁒ (⏣㽢㰚䦻㼃㿫㌆ὒ䞯㤦) , 㧻㞶⧒ (⏣㽢㰚䦻㼃㿫㌆ὒ䞯㤦) , 㺚䡚㍳ (⏣㽢㰚䦻㼃㿫㌆ὒ䞯㤦) , ₖ☯䤞 (⏣㽢㰚䦻㼃㿫㌆ὒ 䞯㤦)䞲ῃ㿫㌆㔳䛞䞯䣢㰖 ,pp. 500 - 505 , 2009 , 䞲ῃ㿫㌆㔳䛞䞯 [12]㰖㡃㌂䣢䣣✳ MRSA ⹥ ⼧㤦⌊Ṧ㡒 MRSA㦮㍶㻲 Ⳋ㡃 ⹮㦧㹾㧊 (Differential innate immune response to sequence type (ST) 72 community-associated MRSA and ST5 healthcareassociated MRSA strains)㧊㡆㰖 (㩚⋾╖䞯ᾦ)

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How can Nanosensing be Used for Outer Space Health Monitoring?

Author 1

Full Name

Chung, Yehwan

Chadwick International

(Last Name, First Name)

School Name

ABSTRACT: Advancements in spacecraft technology have raised interest in a variety of space missions. However, the challenging outer space environment poses significant health risks for astronauts, hindering the actualization of these ventures. To address and prevent these health issues, nanotechnology, a multidisciplinary field focusing on materials below 100 nanometers, shows great promise in the diagnosis. This paper presents how nanotechnology can be utilized for outer space health monitoring for astronauts. The space environment exposes astronauts to microgravity and high levels of space radiation, leading to health issues, including osteoporosis, malfunctioning immune systems, and increased cancer risk. Nanosensors, nanoscale devices capable of detecting biological signals with high precision, are leading this innovative approach. The study offers different classes of nanosensors comprised of electrochemical, optical, and magnetic nanosensors. Electrochemical nanosensors record electrochemical signals converted by transducers to diagnose osteoporosis using a biological marker called Osteocalcin, while magnetic nanosensors use magnetic nanoparticles (gold nanoparticles) and biomarkers to detect cytokines that indicate the state of the immune system. The optical biosensing method incorporating gold electrodes also aids in early cancer cell detection. With nanotechnology, the health of astronauts during extended space missions can be monitored effectively and actively. Using nanosensors in the diagnosis process presents advantages, including cost-effectiveness, efficiency in space, and early detection. This research anticipates further improvements for the success of long-duration space exploration and extraterrestrial habitation by monitoring the well-being of astronauts.

KEYWORDS: Outer Space, Monitoring, Sensing, Nanotechnology, Optical-Sensor

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პ ,1752'8&7,21 Recent developments in spacecraft have intrigued researchers with topics like long outer space missions on Mars or even extraterrestrial residence. However, the health issues faced by astronauts in the outer space environment have been a problem in pursuing such ideas. In order to figure out the cause of such health issues and to further prevent it, monitoring the metabolic activities of astronauts is crucial. Various biological features in the human body can be used to monitor health signals. One such methodology used for capturing biological signals is the use of nanotechnology. Nanotechnology is a multidisciplinary field that centers around the topic of structures with dimensions below 100 nanometers (Singh, 2020). This field is based on the concept that particles act differently at a scale below 100 nanometers due to quantum effects and surface area-to-volume ratio (What Is So Special about “Nano”?, 2023). The enhanced sensitivity of nanoparticles is derived from their very high surface area-to-volume ratio (Figure 1). This feature benefits nanosensors as one of the most relevant sensing methods (Navya et al., 2016). Thus, this research aims to discover how nanotechnology can be used to monitor astronauts’ health in space effectively.

ჟ /,7(5$785( 5(9,(: Astronauts face a number of health issues due to the unique environment of space. For the early detection of such health issues, nanosensing, a field of science that treats nanoscale matters to detect chemical or physical events, is discussed. +HDOWK RI $VWURQDXWV The two leading causes of health issues for astronauts are high exposure to space radiation and the change of gravity in space. Space radiation varies from the radiation from Earth as electrons of radioactive particles have been stripped out when atoms accelerate to the speed of light. This speed of space radiation makes it challenging for current radiation shielding methods to be applied. The radiation exposure experienced by astronauts varies from 50 to 2,000 mSv, which is around 8 to 320 times greater than the average radiation exposure experienced by Americans annually (6.2 mSv) (Why (Space Radiation Matters, 2023; Radiation et al., 2015). Microgravity is the condition where an individual

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experiences a significant decrease in gravity. In space, the gravity is 88% of the gravity experienced on Earth (Allain, 2018). Prolonged exposure to microgravity causes health issues as the human body adapts to a unique environment that requires less mechanical stress. This phenomenon is believed to cause health issues, including osteoporosis, immune disorders, and more (Blaber et al., 2010). This section will discuss common health issues in astronauts, including osteoporosis immune system disorders caused by microgravity, and cancer caused by space radiation.

Musculoskeletal System Disorder Microgravity affects the musculoskeletal system, an organ comprised of the skeleton and muscle. Skeletons and muscles provide protection to the body’s organs, pump blood, and maintain structure. Microgravity induces a change in the bone tissues that causes a reduction in the mass of bones. This symptom is known as spaceflight osteopenia, which shows increased bone resorption by osteoclasts. Osteoclasts are cells that deteriorate bone to initiate the remodeling of normal bone and control bone loss by increasing resorption (Boyce et al., 2009). This is caused by the lack of mechanical stress in a microgravity environment, as mechanical stress couples the bone tissues together (Blaber et al., 2010). Skeletal muscle adaptation also occurs in response to changes in its mechanical environment. In microgravity, less mechanical stress is required, causing the skeletal muscle to adapt to such an environment by muscle atrophy (loss in muscle) (Takata S et al., 2001). Due to muscle atrophy, skeletal muscle decreases in the microgravity environment and further causes osteoporosis (Figure 2) (Bettis et al., 2018). In the microgravity environment, on average, 20% of total muscle mass and 30% of total muscle strength is reduced over the course of a month (Juhl et al., 2021). ,PPXQH 6\VWHP 'LVRUGHU Immune system disorder in astronauts is another issue caused by microgravity. Microgravity affects the immune system by reducing the blood pressure. Blood pressure is reduced by atrophy of the heart and blood vessels and the loss of blood volume (Figure 2). Reduced blood pressure lessens the volume of blood transported to the primary immune organs, including bone marrow, spleen, and lymph nodes. As those organs receive less blood, fewer immune-related cells can be induced. Research from Millie Hughes-Fulford, an American medical investigator, molecular biologist, and NASA payload specialist, and her colleagues show that the decrease in gene induction of ground-activated splenocytes ranged from 28.15% to 66.62% (Martinez et al., 2015). Spenlocytes indicate the facilitation of the immune system since it include T and B lymphocytes, dendritic cells, and macrophages that all participate in the immune system (Bronte et al., 2013).

Cancer Cancer in astronauts is a health issue caused by the unusually high radiation in space. Radiation can cause cancer when passing through the human body as it damages the DNA of a human cell, including

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the tumor suppressor gene (Figure 2). The function of the tumor suppressor gene is to slow down cell division and support apoptosis to ensure that cells do not grow into tumors (abnormal growth in tissues) (Oncogenes et al., and DNA Repair Genes, 2021). Thus, when tumor suppressor genes are damaged, the number of tumors in the human body will increase and raise the possibility of cancer (malignant tumors) (Cooper, 2023). The chance of death from cancer is significantly higher for astronauts. Among the 53 NASA astronauts, 30% passed away have suffered from cancer, while the average cancer-caused death rate is around 17% (1 out of 6) (World, 2022; Rettner, 2019). This demonstrates the cancer risk posed by space radiation to astronauts.

Nanosensing

Nanosensors are nanoscale chemical or mechanical sensors that measure and convert physical quantities into signals that can be detected by detecting instruments (Javaid et al., 2021). The three principles of nanosensors are sensing, interpreting, and reading out. Nanosensors sense the DNA, protein, or mechanical signal, interpret them, and send out signals that can further be detected and analyzed. For analyzing phenomena in the human body, nanosensors are used. Nanosensors are a type of nanosensors that detect specific enzymes, proteins, DNA, antibodies, or other biological matter (Mehrotra, 2016). Nanosensors are used in a variety of fields comprising the medical field, national security, aerospace, and integrated circuits (Deshpande et al., 2018). For biological purposes, nanosensors are used to measure glucose levels in diabetic patients. The biological components incorporated in the glucose monitoring biosensors are receptors, enzymes, antibodies, nucleic acids, microorganisms, and lectins. When the components react with glucose, the electrochemical biosensor collects the electrochemical signals expressed, recording the glucose levels of the diabetic patient (Haniye et al., 2022). The three types of nanosensors that will be discussed in the paragraph for the detection of common health issues of astronauts are electrochemical biosensing, optical biosensing, and magnetic biosensing.

Electrochemical Nanosensing: Electrochemical nanosensing uses electrochemical techniques to detect and signal specific biological molecules or biochemical reactions. Electrochemical nanosensing uses electrodes to support the immobilization of biomolecules and the movement of electrons. This type of

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nano sensing can be organized into two groups: carbon-based and non-carbon-based (Cho et al., 2020). Both groups of materials can be used as transducers that interpret signals from biological matters (biomarkers, DNA, enzymes, and more). When the transducers interpret those signals, the electrochemical signals are recorded by analyzing tools such as Cyclic Voltammetry (CV), Electrochemical Impedance Spectroscopy (EIS), and Differential Pulse Voltammetry (DPV), alerting the existence of the specific biological matter (Reza et al. et al., 2006). Optical Nanosensing: Optical nanosensing uses biological materials ranging from enzymes to whole cells and tissues as biorecognition elements. This nanosensor integrates an optical transducer system that converts optical properties into physical quantities, including light intensity, color, or wavelength, into an electrical signal. The physical quantities signal the concentration of the intended substance. Due to the optical properties of this method, in vitro diagnosis using blood, saliva, and urine is used. With an added biorecognition material (enzymes, antibodies, nucleic acids, or proteins), optical transducers emit fluorescence or bioluminescent that can be further interpreted through a signal output (Pavel Damborský et al., 2016). Magnetic Nanosensing: Magnetic nanosensing utilizes magnetic particles to signal biological labels. In this sensing method, magnetic particles are synthesized into a suitable size and modified with a biocompatible linker and suitable ligands. When bound with a biomolecule, a magnetic nanoparticlebiomolecule complex is formed. The magnetic nanoparticle-biomolecule complex should be at most the size of 100 nanometers for its use as an in vivo diagnostic tool. The magnetic signals emitted from the magnetic nanoparticles are then captured by analytics tools such as superconducting quantum interference devices (SQUIDs) or giant magnetoresistance (GMR) for interpretation (Chen et al., 2017).

,,, ',6&866,21 So far in the paper, the health of astronauts and the three different nanosensing methods have been reviewed. Now, the sensing mechanism for each disease (osteoporosis, immune disorder, and cancer) will be discussed. Sensing Osteoporosis Several costly and laborious nanosensing methods that require large instruments to detect the state of the growth of bones. Improving on these limitations, one recently suggested nanosensing method for osteoporosis is Osteocalcin (Ocn). Ocn is a peptide secreted by the osteoblast that serves as a bonebuilding marker (a category of biochemical markers). When Ocn is injected into the subject as a nanosensor, most of them bind to the inorganic part of the bone matrix. This allows Ocn to serve as a specific and sensitive monitor of the progress of osteoporosis and the bone’s response to treatment. To sense the Ocn molecules, Electrochemical Impedance Spectroscopy (EIS), an electrochemical nanosensing method, is used. EIS is an analytical tool that recognizes biological activities occurring at the electrode surface of a physical component, such as antibody-antigen recognition and substrate-– enzyme interaction, to detect specific biomarkers, pathogens, and DNA. The physical component used for Ocn sensing is nano gold electrodes. Electrodes are solid electrical conductors that carry currents to the non-metallic part of a circuit (Definition of Electrodes, 2020). Gold electrodes are often used in nanosensing due to their biological affinity, narrow size distribution, and inertness (Liu et al., 2018). To detect osteoporosis, the spectroscope observes the changes in the electrode surface of the gold HOHFWURGH DQG WKH DPRXQW RI 2FQ LQ WKH VDPSOH øQDO HW DO 6HQVLQJ 0DOIXQFWLRQ LQ ,PPXQH &HOOV Cytokines are small proteins that control the immune system and blood cells' growth. The concentration of cytokines has shown a positive correlation with immune system activation (Cytokines and Their Side Effects, 2019). Magnetic nanoparticles with their magnetic field have been suggested for sensing cytokines as a successful method. This is due to the low background magnetic signal of magnetic nanoparticles that allows the applied magnetic field to collect magnetic nanoparticles regardless of the

332

other physical properties of the particles. Gold nanoparticles are commonly used nanoparticles for magnetic nanosensing due to their electromagnetic-enhancing properties. To target specific cytokines, gold nanoparticles are engineered with biomolecules that sense specific antibodies of cytokines. When biomolecules bind to cytokines, the emitted magnetic field in response to the external magnetic field can be recorded to alert the presence of cytokines in an in vitro environment (Warangkana Lohcharoenkal et al., 2021). Sensing Cancer Cells The use of nanotechnology for sensing cancer cells can be less invasive, inexpensive, time efficient, and help the early diagnosis of cancer compared to current detection methods such as MRI and PCR (NBC News Learn, 2020). For the nanosensing of cancer cells, single-stranded DNAs present in the subject’s blood are engineered to have a different structure from its original form. The DNA strand can only reverse its structure when cancer-initiating transcription factors attach. This feature of the DNA can be used to distinguish if there are cancer-initiating transcription factors in the subject’s blood (UC et al., 2011). The change in structure can be further recorded by a type of optical nanosensing that uses structure-sensitive fluorophores. Structure-sensitive fluorophores are molecules with fluorescence properties that only express fluorescence when they sense a change in the structure of the engineered DNA (Plaxco et al., 2011; NanoTemper, 2020). Thus, researchers can observe a change in the color of the blood sample with the presence of cancer-initiating transcription cells.

ს &21&/86,21 Health issues among astronauts have been a severe problem in the development of long-lasting space exploration and the possibility of extraterrestrial residence since it is not possible to cure complicated health issues in space. Thus, the early diagnosis of health issues for further treatment is crucial. This research has demonstrated that space-efficient nanoscale devices that can help diagnose osteoporosis, immune system deficiencies, and cancer would be well-suited for deployment in the limited space environment of a spacecraft. Also, due to the small quantity and size of the material needed for nanosensing, nanosensors are inexpensive compared to alternative sensing methods such as MRI. This research suggests three types of nanosensing methods for diagnosing common health issues in space including osteoporosis, malfunctioning immune system, and cancer, which are electrochemical nanosensing, optical nanosensing, and magnetic nanosensing. However, some of these nanosensing methods need the incorporation of in vitro process that does not allow the active diagnosis of diseases compared to in vivo methods that send information directly from the subject. From this possible limitation, further research can be done on wearable nanosensors that send information in real-time. Since current wearable nanosensors are limited to analyzing external physical phenomena to determine heart rate and blood pressure, the development to analyze internal phenomena discussed in the paper including osteoporosis, immune system, and cancer is projected to innovate the nanosensing industry.

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Technological Innovations Shaping the Future of Healthcare Author 1

Full Name

Ham, Jiseok

Saint Johnsbury Academy Jeju

(Last Name, First Name)

School Name

ABSTRACT: Recent advancements in medical technology and biology have ushered in a new era in modern medicine, enabling more precise and efficient patient care. This era is marked by groundbreaking technologies, including robotic surgery, AI-based diagnosis, and genetic modification. This research examines the impact of these advanced medical technologies and explores their potential for global adoption. This investigation spotlights the ways in which technological advancements can revolutionize current medical practices. These technologies promise significant improvements in safety, precision, and patient care. Robotic surgeries, for example, leverage 3D-printed organs and stabilize hand tremors, offering surgeons precise guidance during operations and increasing surgical success rates. AI-based diagnoses help medical professionals predict potential health issues through advanced algorithms that process patient data. Genetic modifications, on the other hand, facilitate gene editing, lab-grown organs, and the removal of mutated genes or cells, thus enhancing treatment methods and organ transplant procedures. Despite its promise, the proliferation of these advanced medical technologies faces hurdles, such as predominantly limited access, and high costs. This study delves into potential investigations on the effectiveness of such advanced technology and how we can make it more accessible, thus making it more globally utilized. In recent years, significant advancements in areas such as medical technology and biology have granted the field of modern medicine a new way for more precise and efficient patient care. These advancements come with a huge range of cutting-edge technologies, including robotic surgery, AI-based diagnosis, and genetic modification. This study investigates the impact and potential global utilization of such advanced medical technologies. The research focuses on how advancements in modern technology could be used to better the current state of medicine. These technologies offer remarkable enhancements in safety, precision, and patient care. Robotic surgeries enable the usage of 3D-printed organs, while also stabilizing hand tremors and providing accurate guidance for human doctors. This ultimately leads to an increased rate of surgery success. AI-based diagnosis helps doctors predict the potential diseases of their patients through advanced computer algorithms based on collected data. Genetic modification allows gene editing, lab-grown organs, the removal of mutated genes or cells, bettering treatments, and organ transplant science. However, the widespread of these advanced medical technologies faces challenges in accessibility mainly due to limited general access and high costs. The study searches for ways that could decrease and solve the problems of such technologies possessing high prices by researching specific methods that could

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increase accessibility to a larger audience. The study also analyzes the effectiveness of such medical revolutions by suggesting specific data that shows real-life medical enhancements that were feasible due to the introduction of such technologies. The findings acknowledge specific methods to make such technologies accessible to a wider audience. This includes looking into ways to lower costs and create laws that support equitable distribution. We want to provide a framework to ensure that these revolutionary medical technologies are available to the larger public by encouraging collaboration between researchers, healthcare professionals, politicians, and industrial stakeholders. The findings will seek revolutionary ways to better utilize the great medical opportunities we are given.

KEYWORDS Robotic Surgery, AI-Diagnosis, Organ Transplant, 3D Organ, Genetic Modification

TABLE OF CONTENTS 1. Research Title 2. Abstract 3. Introduction a. b. c. d.

The introduction of advanced technology in medical areas How much do treatments differ from previous solutions Research Method Purpose of the Study

4. Weaknesses a. b. c. d.

Accessibility Cost Requirement for expertise Prior activities that tried to solve the weaknesses

5. 3 Main technologies a. Robotic Surgery b. AI-diagnosis c. Genetic Modifications 6. Effectiveness (Positive Cases) a. Robotic Surgery - Data b. 3D Organ Transplant c. Genetic Modifications - Data 7. Limitations a. Robotic Surgery b. 3D printed Organ c. AI-Diagnosis 8. Conclusion

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INTRODUCTION Part A - The introduction of advanced technology in medical areas Over the past few years, the medical field has experienced extreme success in various technological and biological domains. Cutting-edge technologies, such as robotic surgery, AI-based diagnosis, and genetic modification, have emerged as game-changers, transforming the entire state of modern healthcare. Before the adoption of advanced technology in medical areas, it was nearly impossible to perform well-needed scientific activities such as gene editing or creating artificial organs. Such advancements have allowed humanity to access solutions to diseases that were believed to be incurable. New technologies focus on using the help of AI-based algorithms and robots.

Part B - How such treatments differ from previous solutions Besides accuracy and efficiency, there are other unique differences that these newly adapt treatments hold. Customization is one of those factors. Artificial organ 3D printing allows for the creation of custom implants that fit specifically to the patient’s body. This leads to better outcomes and improved patient comfort. Artificial organs and tissues produced through 3D printing can potentially be created utilizing the patient’s own cells, deducting the risk of rejection by the human immune system and the need for immunosuppressive drugs. Another difference is that these treatments are able to target and modify specific genes responsible for genetic disorders. Gene editing has the potential to cure certain genetic diseases by correcting or replacing faulty genes. A representative example is cystic fibrosis, a genetic disorder that causes the production of thick mucus in the lungs of the patient.

Part C - Research Method: Literature Review During the course of this study, my primary goal was to focus on gathering information from recent and reliable sources, with a maximum publication date of three years ago. The intention was to guarantee that the data I utilized were valid and accurate. The sources that were selected not only met these criteria but also possessed a proven track record of authenticity. Variables that were taken into consideration during the data selection process included limitations, advancements, and practical applications of various medical technologies. Two factors that shaped the direction of my source selection were reliability and recency. In order to uphold the credibility of this study, I leaned toward published journals and research reports from reputable organizations. Through the use of a traditional review, I was able to obtain a comprehensive understanding of the present landscape and development within the medical field. This phase of the study provided me with knowledge of current technologies utilized within the medical sector. Among the plethora of possibilities, I chose three specific technologies for deeper examination: Artificial Intelligence (AI), 3D organ printing, and gene editing. During the systematic review phase, I closely examined each of the previously mentioned technologies. A deep delve into the intricacies of how these technologies function have shown clear and immense promise, but also noteworthy limitations in terms of their integration into the public health system. It is essential to keep in mind the silver lining that despite such limitations, progress is actively being made. Integration of new technology does not happen in one day but it is rather an ongoing journey, marked by small steady advancements. Over time, these small steps will bridge the gap between the potential of these technologies and their practical implementations in our healthcare systems.

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Part D - Purpose of the study The purpose of this study is to comprehensively investigate and evaluate the impact of advanced medical technologies on the field of modern medicine, with a specific focus on robotic surgery, AI-based diagnosis, and genetic modification. By examining these innovative technologies, we aim to highlight their potential to revolutionize current medical practices, leading to more precise, efficient, and personalized patient care. Through a thorough review of relevant literature and scientific research, we seek to analyze the unique advantages and capabilities of each technology, such as the utilization of 3D printed organs in robotic surgeries, the power of AI-based diagnoses, and the potential of genetic modification to address genetic disorders, possibly leading up to treating cancer.

WEAKNESSES Part A - Accessibility The rapid advancements in medical technology have truly revolutionized the field of healthcare. However, these innovations also have a critical drawback - their lack of accessibility. The surgical robot, ‘da Vinci’, acts as a good example. While the da Vinci robot is known for its ease of use, faster recovery times, and minimally invasive procedures, its incredible $2-million price tag poses a gigantic barrier. According to Bec Crew, it is known that there are only about 5,500 da Vinci robots functioning worldwide. Although it contains significant capabilities, it is of no use when nearly no one can access the technology. Despite the impressive capabilities of the da Vinci robot, the growing divide in accessibility is a concerning issue. Hospitals that can afford the technology became highly competitive, drawing patients seeking cutting-edge treatment. Most hospitals are unable to afford such resources, leaving a few to monopolize. Another problem is with its relatively disappointing performance. Although its impact has been particularly noteworthy in urology, where it monopolizes robot-assisted radical prostatectomies, the answer to the question: ‘Do these enhancements translate into better long-term outcomes?’ appears to be ‘no’. Clinical trials and studies have constantly proven that while robotic surgery may offer immediate benefits, the ultimate cancer outcomes are equivalent to traditional procedures. This reveals that such technology may not be worth the fund it requires.

Part B - Cost High cost is a significant factor that can act as a weakness for advanced medical technologies like robotic surgery and 3D-printed organs. 1. Robotic Surgery Robotic surgery is an advanced medical technique that comes with significant costs. The high expense cost of robotic surgeries is due to several factors. The primary factor is the price of the robotic systems themselves. The da Vinci Surgical System, one of the most popular robotic surgical systems, comes with a price tag of approximately $2 million per system. This high initial investment cost requires patients to pay extreme budgets in order to try such surgery. In addition to the extreme system costs, the need for replaceable parts and options creates more burden. Having thousands of different surgeries, certain parts of the machine need to be replaced. These replacement parts can accumulate expenses over time, contributing to the ongoing cost of performing robotic surgeries.

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Interestingly, the lack of strong competition in the field of robotic surgery also plays a role in maintaining higher costs. With the dominance of a single system, such as the da Vinci Surgical System, there's limited market pressure to drive down prices. Unlike many other technologies that become more affordable with increased popularity and diversity in products, the costs associated with robotic surgery have not seen a significant reduction, possibly due to the specialized nature of the equipment and ongoing research and development costs. 2. 3D-Printed Organs While the potential for 3D-printed organs is revolutionary, the cost that follows is unignorable. One of the primary cost factors is the equipment required for bioprinting. Specialized bioprinters, used for creating complex organ structures, can come with a price tag of around $100,000 on average. This investment price acts as a gigantic barrier for hospitals and researchers to acquire such technology. The materials used in the bioprinting process also require huge expenses. Creating living tissues through bioprinting requires specialized materials such as chitosan and hydroxyapatite, that are relatively expensive and hard to obtain. Research and development costs are also noticeable. The field of bioprinting and 3D technology is still in its early stages, and continuous research is essential for the improvement of the technology. This research requires investment, which also impacts the cost of 3D-printed organs. The expertise of skilled professionals is essential for the success of bioprinting procedures. Researchers and professionals experienced in bioprinting techniques are needed to carry out the process accurately. However, their specialized skills often come with higher salary expectations, adding to the overall cost. Moreover, the process from research and development to regulatory approval is lengthy and costly. Companies must invest in testing, trials, and safety assessments to gain regulatory approval for 3Dprinted organs. This process can contribute to the overall expenses associated with this advanced medical technology.

Part C - Requirement for Expertise Utilizing advanced medical technology such as robotic surgery, as discussed previously, highlights the extreme importance of expertise and prior experience as a notable weakness. These technologies not only require high-cost equipment, but they demand skilled experts with specialized training and high familiarity with the technology. Robotic surgery involves the application of remote telepresence manipulators, commonly referred to as robot-assisted surgery. However, despite being called ‘robots’, the technology itself requires highskilled experts as support. A huge weakness is that the effectiveness of the technology heavily depends on the skill of the human operator behind it. Surgeons who utilize robotic surgery must have a high level of expertise not just in the technical aspects of the treatment but also in handling any potential issues that might occur. The weakness becomes clear when considering that the robot's capabilities are controlled by human hands. The surgeon should not only have knowledge of machinery but should also have sufficient skill in traditional surgery. This overall sets up a huge entry barrier. Furthermore, robotic surgery calls for more than just academic understanding. Laparoscopic techniques need the development of practical skills under supervision. This practical training helps surgeons grasp the subtleties of the robotic system, foresee difficulties, and adjust to unforeseen circumstances.

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Because it may prevent robotic surgery from being widely used, the demand for knowledge and experience can be seen as a serious limitation. Despite the technology's promised advantages, institutions and individual practitioners may be put off by the difficulty of obtaining the required knowledge. Before being permitted to undertake robotic procedures, surgeons who lack the necessary knowledge in laparoscopy and robotic surgery must complete extra training, frequently through structured programs. This additional step in the credentialing procedure highlights how dependent the technology is on knowledgeable human operators and the difficulties in assuring a high degree of expertise. In conclusion, the need for expertise and prior experience when utilizing advanced medical technology like robotic surgery is a notable weakness. The technology's effectiveness depends on the skill of human operators, and the requirement for specialized training, hands-on experience, and a deep understanding of surgical techniques acts as a potential barrier to its widespread.

Part D - Prior Attempts in Overcoming These Weaknesses Prior initiatives have focused on finding solutions to the high expenses connected with robotic surgery, especially robotic radical prostatectomy (RALP). It is known that open radical prostatectomy is more expensive than robotic surgery due to inefficient operating rooms as well as initial robotic system investment, maintenance, instrument, and equipment costs. The use of efficient and cost-effective instruments, patient participation in cost-sharing, concentrating on highvolume sites where efficiency can balance costs, and improving operating room turnover are some potential remedies. In order to increase productivity, strategies including developing a "reduced" instrument protocol, minimizing extraneous accessories, and optimizing operating room architecture are examples given by Martini Klinik in Hamburg, Germany. The ultimate goal is to keep expenses as low as possible without sacrificing patient care. The concern is raised by the greater costs associated with robotic surgery, which result from variable instrument costs and fixed robot costs. In order to discover the best equipment to employ for a robot-assisted prostatectomy, the study enlisted skilled robotic surgeons. A basic set of instruments was identified by examining expenses and locating cost-effective alternatives, demonstrating the possibility for significant cost reduction. The study also discovered that these cuts did not affect patient outcomes, keeping ideal levels of predicted blood loss, operating hours, and intraoperative problems. This proves that it is possible to reduce costs without sacrificing patient care quality by streamlining instrument sets. Overall, these earlier efforts aimed to ensure the effectiveness of robotic surgery while minimizing the drawbacks related to high costs.

Three Main Technologies Part A - Robotic Surgery The fusion of robotics, computer science, and medical innovation has significantly changed the area of surgery during the past few decades. The emergence of minimally invasive surgery (MIS), which has profoundly altered the landscape of surgical practice, has been one of the most innovative developments during this time. With the use of innovative tools like high-definition cameras and microinstruments, surgeons may execute complex operations through tiny incisions, reducing surgical trauma and its associated problems. In comparison to open surgery, minimally invasive surgery has a number of shown benefits, such as lessened surgical trauma, a lower chance of consequences including infections and discomfort, shorter hospital stays, a quicker return to normal activities, and better cosmetic outcomes. However,

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due to the technical difficulties brought on by changed visual and tactile sensations, learning MIS skills requires intensive and ongoing training. Robotics and computer sciences have been incorporated into surgical procedures to help overcome these difficulties and improve surgical precision. Surgeons now have access to instruments that make up for the limitations of human observation and manipulation, much to how aviation and military technologies have altered their respective fields. Surgeons may practice in more realistic threedimensional (3D) environments thanks to virtual reality (VR) simulators, which also provide them the chance to view and interact with patient-specific virtual models. Surgeons can plan and practice surgeries using these models, which were developed using data from medical imaging, before carrying them out on live patients. A new idea called augmented reality (AR) combines real-time patient photos with computergenerated graphics to give surgeons navigational guidance while doing procedures. This method improves the surgeon's understanding of the target structures and anatomical variances by superimposing important information onto their field of vision. Robotic surgery was first developed in the 1970s with the intention of remotely assisting astronauts and warriors in hazardous situations. For image-guided precision jobs, early robotic platforms were used, eventually developing into the sophisticated systems we see today. The Zeus® system and the da Vinci® Surgical System are two notable examples. The latter, distinguished by its immersive 3D camera and comfortable interfaces, has emerged as the leading robotic surgical platform, revolutionizing surgical procedures in a range of specialties. Although robotic surgery has a lot of potential, it has some drawbacks, such as a lack of force feedback. Nevertheless, advances in surgical precision, patient safety, and postoperative results are still being driven by the interaction of robotics, computer science, and surgery. Robotic surgery has the potential to change medical practice and set new benchmarks for patient care as the discipline develops.

Part B - AI-Diagnosis Through the incorporation of Artificial Intelligence (AI) into the diagnosis process, the healthcare industry is undergoing a revolutionary change. AI-driven diagnosis is a stunning fusion of cuttingedge computing techniques with medical knowledge, delivering previously unheard-of potential to improve precision, effectiveness, and patient outcomes. This innovative method uses machine learning, deep learning, and data analytics to evaluate complex medical data, spot trends, and help medical practitioners come to accurate diagnostic conclusions. The interpretation of medical pictures, test findings, and patient histories is frequently used in traditional diagnostic techniques. AI diagnosis, on the other hand, elevates this procedure by analyzing enormous amounts of data at rates that are faster than humanly possible. Machine learning algorithms develop their capacity to recognize minor differences and anticipate potential medical issues by learning from prior patient data. AI diagnosis hence offers the possibility of early disease detection, individualized treatment plans, and improved patient care. Critical issues regarding accuracy, ethics, and the function of healthcare personnel are raised by the incorporation of AI diagnosis into healthcare operations. The ability of AI with the knowledge of medical professionals to coexist in harmony is still a hurdle. While AI is capable of analyzing enormous information quickly, it lacks the empathy and contextual knowledge that therapists offer. In order to improve patient outcomes, coordinated efforts are necessary for the future of AI diagnosis, where AI serves as a potent tool to help medical practitioners make wise judgments.

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The path toward AI-driven diagnosis is marked by both enthusiasm and responsibility as AI continues to develop and adapt to medical difficulties. It is crucial to make sure that these technologies are thoroughly examined, used responsibly, and smoothly incorporated into clinical practice. There is great promise in the ability of AI to change diagnoses, moving us closer to a time when healthcare is proactive as well as profoundly individualized, ultimately improving the standard of medical care and patient well-being.

Part C - Genetic Modifications In the realm of biological science and medicine, genetic modifications represent a profound and transformative field that holds the potential to reshape the very fabric of life itself. Through genetic modifications, scientists can deliberately alter the genetic material of organisms, unlocking new avenues for treating diseases, enhancing agricultural productivity, and advancing our understanding of fundamental biological processes. Genetic engineering is fundamentally the act of changing an organism's DNA, the genetic code that determines its characteristics and functions. This manipulation can take many different forms, from precise gene editing with tools like CRISPR-Cas9 to the genetic engineering practice of introducing genes from one organism into another. These developments provide scientists the ability to focus on certain genetic variations that cause diseases, providing opportunities for developing more potent treatments and perhaps even curing inherited conditions. The effects of genetic manipulation go much beyond the boundaries of research facilities and labs. They hold the potential to produce genetically modified organisms (GMOs) with greater nutritional value and improved disease resistance and environmental resiliency. By creating crops that produce larger yields while using fewer pesticides and fertilizers, genetic alterations in agriculture can help to address the problems with global food security. However, there are ethical, societal, and regulatory issues that go along with the tremendous potential of genetic changes. The ability to change genetic information raises concerns about unexpected repercussions, long-term ramifications, and the possibility to change the process of evolution as it occurs naturally. Concerns like designer babies, in which genetic changes could be exploited to choose particular human features, also spark ethical discussions. Collaboration between scientists, policymakers, ethicists, and the general public is necessary to successfully balance the advantages and risks of genetic alteration. To make sure that genetic alterations are used responsibly and for the benefit of all, it is crucial that we negotiate this frontier with prudence, strict oversight, and a dedication to open communication. By doing this, we may be able to make ground-breaking improvements in agriculture, medicine, and our knowledge of life itself.

EFFECTIVENESS Part A - Robotic Surgery Robotic Surgery: Transforming Healthcare with Effectiveness and Positive Outcomes Robotic surgery is a monument to the fantastic developments that technology and creativity have made possible for patient care in the dynamic environment of modern medicine. Medical experts are achieving unprecedented levels of efficacy and successful outcomes in a variety of surgical procedures by utilizing cutting-edge robotic devices. The revolutionary potential of robotic surgery is highlighted by two noteworthy stories from various healthcare organizations, which demonstrate enhanced patient experiences and quicker recovery times.

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The significant effects of robotic-assisted surgery are best illustrated by Anita White's experience as she underwent a succession of unanticipated medical procedures. Anita was initially apprehensive about getting a hysterectomy because of her past experiences. But after reading about the advantages, she decided to have a robotically assisted hysterectomy. The procedure's recovery time was significantly cut down, and its invasiveness was lowered because of the use of a da Vinci robot. Anita's uterus, ovaries, and fallopian tubes were removed with just four little incisions, and she was able to get back to her active lifestyle in just a few days. The success of Anita's case highlights how robotic surgery has the potential to improve postoperative results and quality of life. The benefits of this technology for cancer therapies are also highlighted by Amy and Jan's experiences with robotic surgery at Ohio State University's Center for Advanced Robotic Surgery. Amy underwent a robotic gynecologic cancer surgery after receiving an endometrial cancer diagnosis. Her treatment, carried out by a skilled specialist employing cutting-edge robotic equipment, led to a faster recovery, fewer scars, and most significantly, cancer-free results. Jan, who had tonsil cancer, benefited from Dr. Enver Ozer's da Vinci robotic surgery. Her lymph nodes were carefully checked after exact tissue removal utilizing the robotic system, resulting in a cancer-free outcome without the need for radiation or chemotherapy. These examples highlight how robotic surgery can improve survival rates and reduce postoperative treatments in challenging oncological situations. The outcomes of these cases are consistent with a more significant trend in healthcare, where robotic surgery is transforming patient care. Numerous benefits of the robotic-assisted technique include improved surgical accuracy, smaller incisions, less blood loss, and speedier recovery times. Less discomfort, shorter hospital stays, and quicker return to normal activities are all benefits for patients. Additionally, the use of cutting-edge technologies, such as the da Vinci robot, improves a surgeon's skills and enables complex treatments with better results. Robotic surgery is a major advance in a society where patient care is of utmost importance. The experiences of Anita, Amy, and Jan highlight how new technology has the ability to not only improve surgical procedures but also the lives of patients as a whole. The spectrum of healthcare options is expanding thanks to ongoing improvements in robotic systems and surgical methods, which promise even more patient success stories and successful treatments in the future.

Part B - 3D Organ Transplant Advancements in 3D Bioprinting Revolutionize Organ Transplants. Recent developments in the field of 3D bioprinting have been truly spectacular, bringing the idea of printing transplantable, functional human organs closer to reality. More and more successful examples are demonstrating the efficacy and favorable outcomes of 3D organ transplantation. These ground-breaking innovations have the power to solve the urgent need for organ donors and give patients in need of life-saving treatments new hope. 3D Bioprinting: Transforming Organ Transplants In order to produce three-dimensional objects using bioprinting, living cells, and biomaterials are precisely deposited layer by layer. By producing organs and tissues that are unique to each patient, cutting down on the need for immunosuppressive medications and the danger of organ rejection. Here are some inspiring examples of how 3D bioprinting is useful in the field of organ transplantation:

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1. Bioprinted Mini Human Heart Using stem cell-derived heart cells and 3D-printed acrylic pieces, researchers at Boston University have successfully produced a miniature version of a human heart. MiniPUMP (miniaturized Precision-enabled Unidirectional Microfluidic Pump) is a little heart that can beat on its own and mimic the actions of a real human heart. This ground-breaking discovery makes it possible to research heart development, the effects of diseases, and the efficacy of medications without using human subjects. 2. Functional Kidney Tissue For patients with end-stage renal illness, 3D bio-printed kidney tissue is being developed by Trestle Biotherapeutics, a business with headquarters in the United States. Using stem cell biology and 3D bioprinting, this completely functional kidney tissue aims to give patients an alternative to dialysis and possibly do away with the necessity for transplantation. By offering viable replacement organs, the innovation promises patients with renal illness a better future. 3. 3D Bioprinted Cornea The first 3D bio-printed cornea in the world was successfully produced in India by researchers using bio-ink made from human corneal tissue. This development may help millions of people worldwide whose corneal issues result in blindness. Researchers anticipate that the capacity to 3D print corneas will change ophthalmology treatments and offer cures for corneal ailments. 4. Miniature 3D Bioprinted Liver By utilizing blood cells to create miniature copies of a human liver, scientists at the University of So Paulo in Brazil have made a significant advancement. This procedure, finished in just 90 days, exemplifies how crucial liver functions can be integrated within 3D printed tissue. The accomplishment of this project highlights the capability of 3D bioprinting to create functional organ models for drug testing and disease study. 5. 3D Printed Nose Reconstruction Not just for internal organs, 3D bioprinting has also been effectively used in reconstructive surgery. A 3D bio-printed nose implant was given to a patient whose cancer therapy caused her to lose a portion of her nose. Through the process of producing a biomaterial implant, the patient was able to regain both her beauty and functionality. 6. Promising Future and Ethical Considerations Despite the fact that these achievements show how revolutionary 3D bioprinting has been for organ transplantation, there are still obstacles to be solved, such as long-term viability and regulatory permissions. The fabrication and use of bio-printed organs raise ethical issues that need to be carefully considered. Despite these difficulties, the developments made so far provide a glimpse of a time when bioprinting can offer patients individualized, useful organs, revolutionizing healthcare and saving many lives.

Part C - Genetic Modifications Gene editing has emerged as a revolutionary tool in the field of medical science, offering promising solutions to previously incurable diseases. Two notable sources illustrate the effectiveness and positive outcomes of gene editing techniques.

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Source A: NPR Article - "CRISPR gene-editing may boost cancer immunotherapy, a new study finds" The NPR report emphasizes the promise of CRISPR gene editing in enhancing cancer therapies. It highlights the cases of Katie Pope Kopp and Victor Bartolome, who volunteered for research testing the gene-editing approach in treating their different malignancies. Kopp, who had non-Hodgkin lymphoma, and Bartolome, who had blood cancer, were both treated with CAR T-cell therapy that used the CRISPR gene-editing technology. This therapy includes altering the patient's immune cells to attack their malignancies more effectively. The study's findings were encouraging. Both Kopp and Bartolome are still in remission after getting the experimental treatment. Dr. Joseph McGuirk, an oncologist at the University of Kansas, described the therapy as including the injection of "living drugs" into patients that last for extended periods of time. These live medications are immune cells that have been genetically modified to target and destroy cancer cells. The gene-editing technology also has the potential to improve CAR T-cell therapy for a broader range of malignancies and patients, according to the article. The therapy is known as "off-the-shelf" CAR-T, which means that batches of genetically altered cells are readily available for every patient, decreasing the need for bespoke treatments. This method has the potential to be less expensive and more appropriate for individuals with aggressive diseases who cannot afford to wait. Source B: Scientific American Article - "Four Success Stories in Gene Therapy" The Scientific American article discusses four success stories in gene therapy, illustrating its potential in treating various diseases: 1. The article covers the efforts of Jean Bennett and Albert Maguire, who created a gene treatment for retinal illnesses that result in significant eyesight loss. They were able to target and fix mutations in the RPE65 gene using CRISPR technology. The FDA approved Luxturna therapy, which has restored eyesight to individuals with Leber congenital amaurosis and retinitis pigmentosa. 2. Training the Immune System to Fight Cancer: The article discusses the success of chimeric antigen receptor (CAR) T cell therapy in treating cancer. This therapy reprograms a patient's immune cells to target cancer cells. Clinical trials have shown significant remission rates in patients with acute lymphoblastic leukemia (ALL) and diffuse large B cell lymphoma. 3. The article mentions a clinical trial using CRISPR-Cas9-based treatment to treat sickle cell disease and beta-thalassemia. In vivo, gene editing is used in this therapy to encourage the creation of healthy fetal hemoglobin. Initial findings showed that patients with both illnesses had higher hemoglobin levels and fewer symptoms. 4. Derailing a Potentially Lethal Illness: The article discusses the success of antisense therapy in treating spinal muscular atrophy (SMA). This therapy helps restore the production of motor neuron proteins and has shown promising results in improving motor function and life expectancy for patients with SMA. These two sources show the growing success and potential of gene editing approaches in treating a wide range of disorders. From cancer immunotherapy to the prevention of vision loss and the treatment of blood disorders, gene editing provides hope for patients who previously had few or no treatment options.

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LIMITATIONS A. Robotic Surgery Robotic surgery has brought about a significant transformation in the field of medical procedures, offering benefits such as improved precision, minimally invasive approaches, and enhanced outcomes for patients. However, despite its advantages, there are several limitations associated with robotic surgery that need to be addressed for its wider adoption and optimal utilization. 1. Cost: The high cost of robotic surgery is one of the most significant impediments to widespread use. For many medical institutes, the initial expenditure required to purchase and maintain robotic surgical systems is prohibitively expensive. This financial barrier may restrict robotic surgery to only well-funded medical centers, resulting in discrepancies in healthcare access. 2. Technical Difficulty: Robotic surgery is a highly difficult process that necessitates specialized training and cutting-edge technology. Surgeons must learn how to use the robotic console and manipulate the robotic arms. Technical problems or malfunctions during surgery might endanger patient safety and cause surgical delays or cancellations. 3. Limited Tactile Feedback: A significant disadvantage of robotic surgery is the surgeon's lack of tactile feedback. In contrast to traditional surgery, in which physicians can directly feel and assess tissue texture, robotic surgical systems do not have the ability to communicate detailed tactile information. The lack of tactile feedback might make precise tissue manipulation and assessment difficult. 4. Extended Operating Times: Robotic-assisted operations can take longer to complete in some situations than traditional open surgeries. The configuration of robotic systems, as well as the learning curve associated with their operation, might lead to lengthier surgical timeframes, which can have an impact on overall efficiency and patient outcomes. 5. Patient Selection: Not every patient is a good candidate for robotic-assisted surgery. Decisions to employ this technology must be carefully considered on a case-by-case basis, taking into account aspects such as the patient's medical condition, the procedure's complexity, and potential benefits over traditional procedures. 6. Learning Curve: Surgeons must undergo extensive training to become proficient in robotic surgery. This learning curve might result in differences in results among less experienced surgeons, highlighting the importance of effective training programs and mentorship. 1. Access and Disparities: Robotic surgery is only available at medical centers that have the required resources and qualified people. Because of this scarcity, people in remote or disadvantaged locations may have unequal access to healthcare services. As a result, there may be discrepancies in healthcare outcomes. 2. Conversion to Open Surgery: Complications during robotic surgeries may necessitate conversion to traditional open surgery. Scar tissue or unanticipated complications may force the surgeon to abandon the robotic method for patient safety, disrupting the planned minimally invasive benefits.

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3. Nerve Damage and Compression: During surgery, the robotic arms and tools may put pressure on adjacent nerves and tissues, potentially causing nerve damage or compression. The patient may experience issues such as numbness, weakness, or discomfort as a result of this. 4. Technical Failures: While technical failures or malfunctions in robotic systems are uncommon, they can occur. Despite stringent testing and maintenance protocols, there is still the possibility of a robotic malfunction, which could jeopardize patient safety and cause surgical delays.

B. 3D Organ Printing While 3D printing holds promise in producing functional organs for transplantation, several practical constraints and challenges must be addressed for its successful implementation: 1. Customization and Variability: Each patient's organ needs are unique, and demand for printed organs can fluctuate. Unlike traditional organ transplantation, in which donor organs are matched to certain qualities of the recipient's body, 3D-printed organs require extensive customization to fulfill the demands of individual patients. This heterogeneity presents difficulties in designing and manufacturing organs with the necessary chemical and physical properties. 2. Chemical and Structural Composition: In order for 3D printed organs to be successful, their chemical and structural compositions must closely resemble those of normal organs. This kind of precision is difficult to achieve and necessitates the use of bio-inks and complicated technical techniques. It is crucial for functional success to ensure tissue integration into complicated organ architecture. 3. Operational Challenges: A practical constraint is the time window for creating functional 3D organs. Rapid organ prototyping necessitates a detailed evaluation of patient tissue features, which increases the time required for designing and printing. Unlike traditional transplantation, in which donor organs are functioning in a living host, 3D-printed prototypes must be rigorously tested to ensure functionality and durability. 4. Perishability and Maintenance: 3D printed organs have a limited shelf life and must be maintained on a continuous basis. It is critical to ensure the long-term performance and stability of these printed organs. However, due to the erratic nature of organ demand, maintaining the 3D printing technology and bio-inks used in organ printing labs might entail considerable expenses and obstacles. 5. Validation and Testing: While the potential benefits of 3D organ printing are significant, the technology must be thoroughly verified and tested before being scaled up for clinical usage. It is critical to ensure the safety, functionality, and compatibility of 3D-printed organs with the recipient's body. 6. Ethical and Legal Issues: The introduction of 3D organ printing creates ethical, legal, and societal concerns that must be addressed. Intellectual property rights, patient permission, and the responsibility of medical practitioners to ensure the success of 3D-printed organ transplants must all be carefully considered.

C. AI - Diagnosis 1. Error Proneness: According to the research, AI, particularly deep neural networks, may be more prone to errors in image-based diagnosis than human clinicians. This shows that AI systems may not be as accurate and judgmental as experienced medical practitioners. 2. Feature Analysis: It is proposed that AI and human clinicians may use various features for analysis

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when evaluating medical photos. Because of this disparity in feature usage, AI may misidentify certain medical diseases or patterns that human clinicians would recognize more precisely. 3. Medical Image Complexity: Medical images, such as those from radiology or pathology, can be highly complicated and require detailed interpretation. AI algorithms may struggle to recognize tiny subtleties or deviations that skilled therapists can pick up on after years of training and competence. 4. Lack of Contextual awareness: AI lacks the contextual awareness and clinical reasoning abilities possessed by human clinicians. When making a diagnosis, clinicians evaluate a patient's medical history, symptoms, and other pertinent information, which can have a substantial impact on the accuracy of their evaluations. 5. Issues with Generalization: AI models, especially deep neural networks, may fail to generalize successfully to different populations or unusual medical disorders. Training AI systems on a single set of data may not effectively prepare them for unexpected or unusual occurrences, potentially resulting in misdiagnoses. 6. Ethical and Legal Implications: Misdiagnoses or inaccuracies in medical diagnoses made by AI systems might have ethical and legal ramifications. Patients may receive needless treatments or experience delays in receiving correct care as a result of AI faults. 7. Ongoing Need for Human Oversight: The findings emphasize the ongoing importance of human oversight and intervention in AI-generated diagnoses. Even as AI technologies advance, human clinicians must remain involved to validate and verify the accuracy of AI-generated diagnoses.

CONCLUSION This research aimed to comprehensively explore and assess the influence of advanced medical technologies on modern medicine. The study specifically delved into the impacts of robotic surgery, AI-driven diagnosis, and genetic modification. We started off having questions regarding the effectiveness of advanced medical technology and were able to find answers throughout the research process. We also focused on researching the weaknesses of such technology and finding possible solutions. The search for information was carried out by a series of literature reviews focused on the impact of advanced modern technologies in the medical field. This included gathering sources from wellknown scientific journals, research papers, and scholarly publications. Our aim was to get relevant and accurate information. The selected sources were evaluated based on their credibility, relevance, and accuracy. The gathered information covered various aspects such as the benefits, weaknesses, and positive effects of such technology. Some notable limitations of such products were high costs, low accessibility, and potential safety concerns. 1. High Costs: Advanced medical technologies and innovative treatment methods often come with substantial costs. Such expenses often arise from manufacturing, ongoing maintenance, R&D, regulatory compliance, etc. Through cost-sharing strategies, the financial burden can be distributed among various shareholders. By pooling resources, the overall cost of implementing these technologies can be reduced, making them more affordable for patients. 2. Low Accessibility: Disparities in healthcare resources and infrastructure can lead to unequal access to medical technologies. This is often prevalent in remote or low-income regions. By

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optimizing protocols and providing guidelines, technologies can be applied where they are most needed maximizing efficiency and effectiveness. This will ultimately help bridge the accessibility gap. 3. Potential Safety Concerns: While it is true medical technologies can revolutionize healthcare, we must be aware of their potential safety risks to patients and healthcare providers. Rapid introduction of new medical technologies without thorough testing can often lead to severe consequences. Through extensive training and regulations, we can minimize the likelihood of errors and adverse events. With the aid of regulatory agencies, evaluating the safety and efficacy of technologies can be properly screened before they are widely adopted. This research has shown that technological advancements have led to a transformation within the medical field. These innovations have not only elevated the precision of diagnoses and the effectiveness of treatments but have also redefined the ways in which healthcare is accessed and delivered. Through the integration of AI-diagnosis, 3D-printing, and gene-editing, medical practitioners can now make more informed decisions, leading to improved patient outcomes. By acknowledging the limitations and actively pursuing solutions, we can expect to experience the full potential of medical technology to create a future where advanced healthcare is accessible to all.

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REFERENCES Crew, Bec. “Urology Fellow, Jeremy Fallot, and Nurse, Shauna Harnedy ... - Nature.” A Closer Look at a Revered Robot, 23 Apr. 2020, media.nature.com/original/magazine-assets/d41586-020-01037-w/d41586-020-01037-w.pdf. Deamer, Lanna. Why Is Robotic Surgery so Expensive?, 30 Oct. 2020, www.electronicspecifier.com/industries/medical/why-is-robotic-surgery-so-expensive. Reynolds, Joyce. “How Much Does a 3D Printed Organ Cost.” Nikko Industries, Nikko Industries, 26 Oct. 2022, www.nikkoindustries.com/blogs/news/how-much-does-a-3d-printed-organ-cost. Muigai, Anne W. T. “Expanding Global Access to Genetic Therapies.” Nature News, Nature Publishing Group, 7 Jan. 2022, www.nature.com/articles/s41587-021-01191-0). Robotic Surgery (Urologic) Standard Operating Procedure (SOP) - American Urological Association, www.auanet.org/guidelines-and-quality/guidelines/other-clinical-guidance/robotic-surgery-(uro logic)-sop. Accessed 21 Aug. 2023. Goldberg, Hanan. “Erus 2018: How to Reduce the Costs of Robotic Surgery?” UroToday, 5 Sept. 2018, www.urotoday.com/conference-highlights/eau-robotic-urology-section/erus-2018/106778-erus2018-how-to-reduce-the-costs-of-robotic-surgery.html. Delto, Joan C, et al. “Reducing Robotic Prostatectomy Costs by Minimizing Instrumentation ...” Reducing Robotic Prostatectomy Costs by Minimizing Instrumentation, 6 May 2015, www.liebertpub.com/doi/abs/10.1089/end.2014.0533. Diana, M, and J Marescaux. “Robotic Surgery.” Academic.Oup.Com, 27 Jan. 2015, academic.oup.com/bjs/article/102/2/e15/6141447. “Patient Stories.” Ohio State Center for Robotic Surgery, wexnermedical.osu.edu/robotic-surgery/ohio-states-center-for-advanced-robotic-surgery/patient -stories. Accessed 21 Aug. 2023. TriHealth, www.trihealth.com/institutes-and-services/robotic-surgery/success-stories/anita-white. Accessed 21 Aug. 2023. V., Carlota. “The Most Promising 3D Bioprinting Projects.” 3Dnatives, 2 Feb. 2023, www.3dnatives.com/en/bioprinting-projects-3d-printed-organs-070420205/.

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“Using Bioprinting to Improve Quality of Life for Diabetes Patients.” CELLINK, 13 Jan. 2023, www.cellink.com/blog/how-this-doctor-is-using-bioprinting-to-improve-quality-of-life-for-pati ents-with-diabetes/. Stein, Rob. “CRISPR Gene-Editing May Boost Cancer Immunotherapy, New Study Finds.” NPR, NPR, 13 Dec. 2022, www.npr.org/sections/health-shots/2022/12/13/1140384354/crispr-improves-cancer-immunothe rapy-car-t-cell. Daley, Jim. “Four Success Stories in Gene Therapy.” Scientific American, Scientific American, 1 Nov. 2021, www.scientificamerican.com/article/four-success-stories-in-gene-therapy/. Kennedy, Shania. “Ai May Be More Prone to Errors in Image-Based Diagnoses than Clinicians.” HealthITAnalytics, HealthITAnalytics, 10 May 2022, healthitanalytics.com/news/ai-may-be-moreprone-to-errors-in-image-based-diagnoses-than-cl inicians. Author links open overlay panelP. Sreekala a, et al. “3D Organ Printing: Review on Operational Challenges and Constraints.” Materials Today: Proceedings, Elsevier, 14 Sept. 2020, www.sciencedirect.com/science/article/abs/pii/S2214785320362210. “Challenges of Robotic Surgery.” Adotrip, Adotrip - Nothing is Far, 25 Apr. 2023, www.adotrip.com/medical-tourism/robotic-surgery/challenges-of-robotic-surgery.

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Understanding Photodetector Mechanisms in PET Scans for Tumor Localization Author 1

Full Name

Jung, Michelle

HPrep Academy

(Last Name, First Name)

School Name

ABSTRACT: PET scans play significant roles in diagnosing diseases, especially in their early stages. Since PET scans are vital in diagnosing cancer, it is important to understand the mechanics of PET scans. Comprehending the underlying mechanisms of tumor detection can provide the benefit of advancing PET scans in the future. This comprehension will allow more individuals to understand the basics of detector systems in PET scans. Creating a simulation of the introductory mechanics behind PET scan detector systems presents an equation that aims to introduce and enhance the understanding of the concept of PET imaging mechanics.

KEYWORDS: Imaging Test, PET, PET Scan Mechanism, Photodetector, Positron Emission Tomography, True Coincidence, Tumor Localization

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Introduction Advancements in imaging techniques transformed the medical field with their ability to diagnose and treat diseases. Imaging techniques like positron emission tomography (PET) contribute to such advancements as they help visualize internal structures, such as organs and tissues in organisms. In the field of medicine, PET scans are usually used to diagnose cancer in patients as PET can detect internal biological abnormalities, which helps diagnose diseases even in earlier stages when detection may be difficult. The fundamental information behind PET scans is the concept of tomography. Tomography utilizes Xray techniques that shadow the structure inside the body. To perform imaging, two main types of tomography need to be used for this task: linear and nonlinear. While both tomography types share similar fundamental mechanisms, they differ in the benefits and information they can provide. PET scans, in particular, can perform both linear and nonlinear tomography. Linear tomography employs an X-ray emitting tube that moves in a linear motion in one direction and a film moving in the opposite direction of the X-ray tube (Britannica, 2014). The X-ray tube emits X-rays to blur motion occurring in the part of the body. Furthermore, nonlinear or multidirectional tomography uses a similar technique to produce a more clear image of the region. Compared to linear tomography, this technique uses films and X-ray tubes that move in “a circular or elliptical pattern” (Britannica, 2014). When both objects operate in a synchronized manner, a clear image can be produced. The performance of PET scans is correlated with the role of photodetectors as they play an essential role in detecting tumors in patients. However, this technology has its limitations, which include its accuracy and resolution limit. Such limitations have delayed treatment procedures for patients, causing their prognosis to worsen. To improve the quality and preciseness of this technology, the basis of how PET scans operate should be understood. This research presents a simulation that is represented by an equation that involves only true coincidence events when the emitted gamma rays or photons are detected 180 degrees apart. The focus on true coincidence events reduces the results of limitations while enhancing the understanding and accuracy of PET scan mechanisms. By exploring and analyzing the fundamentals of PET imaging, the function behind photodetectors can be uncovered, and the framework of how photodetectors locate tumors when true coincidence occurs can be revealed. Ultimately, by developing a profound understanding of PET scans, the underlying mechanics of photodetectors can be interpreted.

Literature Review – Mechanism This section will discuss the three main components of PET scans: radiotracers, the physical components, and the positron annihilation event.

1. Positron Emission Tomography (PET) Scans Figure 1 shows the major steps for performing positron emission tomography (PET) scans where medical experts can check and diagnose diseases in patients. In contrast to other cancer diagnosis techniques, PET scans allow for the early detection of diseases as they can detect changes in cellular activity before physical changes in organs and tissues occur. To perform a PET scan on a patient, radioactive glucose, referred to as a radiotracer, must be injected into the patient's vein through an intravenous line (IV), inhaled, or swallowed. As the radiotracer spreads in the body, the radiotracer, containing a positron-emitting nucleus, interacts with nearby electrons to create a pair of gamma rays or annihilation photons that travel at 511 keV (MacDonald, L. R. et al., 2008). These photons, detected by the

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photodetectors on PET scans, are analyzed by a computer to create an image of the target organs or tissues. In particular, a true coincidence occurrence indicates the detection of the site of decay of the radiotracer. Depending on the amount of radiotracer absorbed, the brightness and contrast of the area in the image will depict the function of the target organ and tissue, allowing doctors and experts to diagnose diseases in patients. (1) Radiotracers One of the most common radiotracers used for PET scans is 18F-fluorodeoxyglucose (FDG). This particular radiotracer is marked with a radioactive fluorine isotope (18F) that emits positrons when it undergoes radioactive decay. 18F replaces a hydroxyl group (-OH) on a glucose molecule, as shown in Figure 2 (Kobayashi et al., 2012). This replacement retains the function of a glucose molecule, but it gives the molecule a radioactive trait while allowing the substance to be easily consumed by cells inside the body (ANSTO Staff, 2019). One unique benefit of FDGs is that they function like glucose molecules in the body. When the FDGs are absorbed into the tissues of a patient, they can indicate whether or not an area is “glucose avid” (Evangelista et al., 2019). If an area is a glucose avid or intaking glucose at a higher rate, the area on the PET scan image will be darker, meaning there is a higher possibility that cancer cells are present. (2) Main Physical Components of a PET Scan PET scans consist of five primary parts: the gantry, detector system, collimator, data acquisition system, and computer system. The gantry is the frame of the machine, which is a rotating ring that contains photodetectors. With its ability to rotate, the detectors enable the PET scan to acquire a thorough patient image. The detector system in the gantry consists of photodetectors arranged in a circular formation. These detectors can detect the positron-electron annihilation event inside the body, allowing experts to observe and locate areas that have cancerous cells through a variety of methods, including the use of the radiotracer FDG to observe glucose avidity. Collimators are specifically used for two-dimensional, not three-dimensional, scanning. Their role is to detect coincidence events detected by the detector system; however, two-dimensional scanning is utilized less, and new promising techniques, such as line of response (LOR), have emerged. Therefore, this eliminates “the need for a physical collimator” when gaining “positional information … from the detected radiation” (Badawi, 1999). To acquire data for image analysis, data can be organized and performed by generating sinograms and michelograms. These two methodologies help create an image of the body. After obtaining such data, computer systems help professionals to analyze and use the images to detect diseases such as cancer in patients. (3) Positron Annihilation Event The injected radiotracers emit positrons, which are positively charged particles that have the same properties as electrons, also known as anti-electrons (“Positron,” 2023). These positrons interact with the surrounding electrons to create a pair of gamma rays or photons that go in different directions, known as the positron annihilation event. Depending on which photodetectors detect the photons, the coincidence event can be determined, as shown in Figure 3. For example, A in the figure illustrates a true coincidence event, which is when the photons created from the event go in opposite directions at a 180-degree angle. In addition to this, other events like scatter and random coincidence can occur. Scatter coincidence is when “at least one of the detected photons has undergone at least one Compton scattering event prior to detection[,]” and random coincidence occurs when “two

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[unrelated] singles correspond to photons that were not created in the same positron annihilation” (Oliver and Rafecas, 2016; Badawi, 2019).

2. Photodetectors Inside the gantry's ring is a circular array of photodetectors that can detect the gamma rays or photons generated from the positron annihilation event. When gamma rays are emitted, detectors play a significant role in capturing the image of the target organ or tissue. The three general types of photodetectors used in PET scans are the following: photomultiplier tubes, silicon photomultipliers, and scintillation detectors. (1) Photomultiplier Tubes (PMTs) A photomultiplier tube (PMT) transforms a light source into an amplified electrical signal by emitting secondary electrons (Flyckt and Marmonier, 2002). This allows PMTs to achieve “high gain, relatively low noise, high timing resolution and reasonable QE [quantum efficiency]” (Jiang et al., 2019). This photodetector consists of three main components inside a vacuum glass tube: a photocathode, a dynode, and an anode (Jiang et al., 2019). Photoelectrons that are emitted from the photocathode move toward the dynodes (Ota, 2021). While there are “two types of photoelectric conversion processes[,]” external and internal, PMTs use external photoelectric conversion processes in which “a photoelectron is emitted from a photocathode into a vacuum” (Ota, 2021). The emitted photoelectron is then “efficiently guide[d]” to the dynodes from the photocathode. As this progresses, for each dynode, a significant increase in kinetic energy can be observed, generating “a secondary emission of electrons upon” collision (Jiang et al., 2019). Since there are generally ten dynodes in each PMT, the number of electrons “can be multiplied by up to ~106 within a few nanoseconds” (Ota, 2021). The anode lastly retrieves the electrons and “generate[s] a high photocurrent pulse, which is significantly greater than the noise current[,]” also known as the electrical readout signal (Jiang et al., 2019). (2) Silicon Photomultiplier (SiPMs) A silicon photodetector (SiPM) is comprised of single photon avalanche diode (SPAD) arrays, which “are solid-state detectors that offer imaging capabilities … of individual photons” and provide the abilities for “unparalleled photon counting and time-resolved performance” (Bruschini et al., 2019). A SiPM usually “consists of hundreds to thousands of” SPADs and requires a lower operating voltage of 20 to 70 V compared to PMTs, which require 1000 V (Ota, 2021). They also have “immunity to magnetic fields[,]” are “sturdier and more rugged[,]” and are relatively “smaller in size” (Piatek, 2019). These abilities allow SiPMs to be more efficient in performing their role as a photodetector, creating the ability “for high-resolution and time-of-flight (TOF) detection” in the medical field (Kim et al., 2021). (3) Scintillation Detectors An individual scintillation detector consists of scintillation crystals that can convert the 511 keV from the positron annihilation event (gamma rays or photons) into fluorescent photons. This conversion allows professionals to determine the location, energy, and time of the gamma photons through the photoelectric sensors of the PET scanner. With the use of scintillation detectors, they can be used for determining “the high-energy part of the X-ray spectrum … [as] the material of the detector is excited to luminescence” (Kramar, 1999).

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3. Data Acquisition Two major approaches can be used to acquire data from PET scans: sinograms and michelograms. As shown in I of Figure 4, a sinogram represents the “LOR associated with each coincidence event … as a function of angle of orientation versus the shortest distance between the LOR and the center of the gantry” (Fahey, 2002). As shown in II, michelograms help people “understand how [images or data of] 3D PET scans are acquired” (Fahey, 2002). Accordingly, to understand the mechanism of finding such information, a simulation can be created to deepen the understanding of how photodetectors in PET scans work. The equation presented below helps to understand how photodetectors can detect photons emitted from the positron annihilation event. This helps to simulate, calculate, and locate the location of the tumor or photon emission site. However, the equation is limited under the hypothetical situation that the events are all true coincidence occurrences.

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(4) Data Analysis In a PET scan image, areas that are most likely to contain cancer cells have a darker shade. This indication depends on the role of radiotracers. For instance, if an FDG is used on a patient, the amount of glucose being absorbed into their organs and tissues would determine whether an area will contain cancer cells. This is often referred to as glucose avidity: increases in glucose absorption will make the regions appear darker in the image. This indication allows for quality image acquisition of the target organ or tissue, allowing experts to determine the possibility of their patients having cancer.

Results and Limitations The simulated equation presents a way to calculate and locate the position of a supposed tumor when a PET scan is performed on a patient. The equation uses conversions between Cartesian an d polar coordinates by using trigonometry concepts. It focuses on using the polar coordinate syst em to identify the location. Despite the clear understanding the equation can provide for tumor localization when two pairs of photodetectors are given, the equation primarily focuses on only true coincidence incidents. While so many other events can occur, solely focusing on true coincidence events limits localizing objects like tumors in realistic situations such as in clinical trials. Additionally, because the equation neglects the possible sources of error, it would only be applicable in ideal situations with no errors.

Conclusion PET scans can detect the location of a tumor when gamma rays or photons are emitted. Before performing a PET scan, patients must consume a radioactive substance that emits positrons, such as a radiotracer. Typically, FDGs are used in these procedures as it is a radiotracer which is an analog of glucose. This allows FDGs to function like normal glucose molecules in the body but with a radioactive trait. When the positrons from the radiotracer interact with surrounding electrons, positron-electron

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annihilation occurs, which emits gamma rays or photons. The detector system in PET scans detects the positron annihilation incident, allowing the photodetectors to identify the tumor's location. In this research, a simulation of this phenomenon is illustrated. When two pairs of photodetectors detected only through true coincidence are provided, the tumor's location can be determined through the simulation. However, this equation has limitations; since it focuses on only true coincidence incidents, it does not account for incidents like random and scatter coincidences. It is also set in an ideal situation where the tumor location is exactly at the point of intersection. This would affect the accuracy and reliability of the derived results as the equation fails to account for any potential errors that could be present in real-world applications. Nonetheless, this equation is efficacious in shedding light on how to understand the underlying mechanisms of photodetector systems in PET scans and opening doors to other possible research, such as improving the role of photodetectors in PET scans, image resolution from acquired data and PET scans, in general.

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References 1. ANSTO Staff. (2019, May 20). Pet innovation. ANSTO. https://www.ansto.gov.au/news/petinnovation. 2. Badawi, R. (Ed.). (1999, January 12). The physical principles of PET. Introduction to PET Physics. https://depts.washington.edu/imreslab/from%20old%20SITE/pet_intro/intro src/section2.html. 3. Britannica, T. Editors of Encyclopaedia (2014, October 20). tomography. Encyclopedia Britannica. https://www.britannica.com/science/tomography. 4. Bruschini, C., Homulle, H., Antolovic, I. M., Burri, S., & Charbon, E. (2019). Single-photon avalanche diode imagers in biophotonics: review and outlook. Light: Science &amp; Applications, 8(1). https://doi.org/10.1038/s41377-019-0191-5. 5. Evangelista, L., Gori, S., Rubini, G., & Gallo, M. (2019). Management of hyperglycemia in oncological patients scheduled for an FDG-PET/CT examination. Clinical and Translational Imaging, 7(6), 447–450. https://doi.org/10.1007/s40336-019-00347-y. 6. Fahey F. H. (2002). Data acquisition in PET imaging. Journal of nuclear medicine technology, 30(2), 39–49.9. 7. Flyckt, S.-O., & Marmonier, C. (2002). PHOTOMULTIPLIER TUBES principles & applications. 8. Jiang, Chalich, & Deen. (2019). Sensors for Positron Emission Tomography Applications. Sensors, 19(22), 5019. https://doi.org/10.3390/s19225019. 9. Kim, H., Kao, C. M., Hua, Y., Xie, Q., & Chen, C. T. (2021). Multiplexing Readout for Time-ofFlight (TOF) PET Detectors Using Striplines. IEEE transactions on radiation and plasma medical sciences, 5(5), 662–670. https://doi.org/10.1109/trpms.2021.3051364. 10. Kobayashi, K., Bhargava, P., Raja, S., Nasseri, F., Al-Balas, H. A., Smith, D. D., George, S. P., & Vij, M. S. (2012). Image-guided biopsy: What the interventional radiologist needs to know about pet/CT. RadioGraphics, 32(5), 1483–1501. https://doi.org/10.1148/rg.325115159. 11. Kramar, U. (1999). X-ray fluorescence spectrometers. Encyclopedia of Spectroscopy and Spectrometry, 2467–2477. https://doi.org/10.1006/rwsp.2000.0336. 12. MacDonald, L. R., Schmitz, R. E., Alessio, A. M., Wollenweber, S. D., Stearns, C. W., Ganin, A., ... & Kinahan, P. E. (2008). Measured count-rate performance of the Discovery STE PET/CT scanner in 2D, 3D and partial collimation acquisition modes. Physics in Medicine & Biology, 53(14), 3723. 13. Merriam-Webster. (2023). Positron. Merriam-Webster. https://www.merriamwebster.com/dictionary/positron. 14. Ota R. (2021). Photon counting detectors and their applications ranging from particle physics experiments to environmental radiation monitoring and medical imaging. Radiological physics and technology, 14(2), 134–148. https://doi.org/10.1007/s12194-021-00615-5. 15. Piatek, S. (2019, October 7). What is an SiPM and how does it work?. Hamamatsu Photonics. https://hub.hamamatsu.com/us/en/technical-notes/mppc-sipms/what-is-an-SiPM-and-howdoes-it-work.html.

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16. Schmitz, R. E., Alessio, A. M., & Kinahan, P. E. (n.d.). Physics of PET - UW departments web server. https://depts.washington.edu/imreslab/education/Physics%20of%20PET.pdf. 17. Verel, I., Visser, G. W., & van Dongen, G. A. (2005). The promise of immuno-PET in radioimmunotherapy. Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 46 Suppl 1, 164S–71S.

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Securing the Future: The Necessity and Potential of Post-quantum Cryptographic System

Author 1

Author 2

Full Name

: Jung Seoeun

(Last Name, First Name)

School Name

: Boylan Catholic High School

Full Name

(Last Name, First Name)

School Name

: : :

ABSTRACT: In the wake of the advancements in quantum computing, the vulnerability of contemporary cryptographic systems presents a formidable challenge. These systems, critical for secure communication in myriad applications, notably banking, are threatened by the sheer computational prowess of quantum computers. This study explores the necessity and potential of post-quantum cryptographic systems as a countermeasure to quantum-enabled breaches, thereby fortifying the security foundations of our increasingly digital world. This research delves into the vulnerabilities exploited by quantum attacks and the limitations inherent in current cryptographic systems. It further elucidates the concept and mechanisms of post-quantum cryptography, elucidating how it can address these vulnerabilities and shore up existing security systems. Through an extensive literature review and case studies, the research delineates the evolution of cryptographic systems and illustrates how new post-quantum cryptographic systems have managed to mitigate the issues observed in earlier incarnations. The study acknowledges that implementing post-quantum cryptographic systems perfectly is currently constrained by technological, temporal, and financial factors. By drawing comparisons between past and present quantum cryptographic systems, the steady advancements being made toward this ambitious goal can be affirmed. The study concludes by underlining the imperative for post-quantum cryptographic systems, given their robustness against quantum attacks and superior security potential. Although limitations persist, it outlines the directions for future research to refine these systems, emphasizing their potential to enhance security for national defense and economic systems significantly. The findings thus suggest an urgent shift towards post-quantum cryptographic systems, which would substantially fortify digital security in an era defined by quantum computing.

KEYWORDS: Quantum computing Â Cryptographic system Â Post-quantum cryptographic system

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Introduction to Implication of Quantum Computing on Cryptography $ Quantum Computing Advancements Quantum computing uses the quantum states of subatomic particles to store and process information, exponentially increasing computational speed compared to classical computers. However, this advancement also threatens by breaking of current cryptographic systems, which promotes the exploration of post-quantum cryptography.

% Importance and Applications of Current Cryptographic Systems Current systems such as RSA and AES encryption underpin many modern security systems, protecting critical data in sectors such as banking and e-commerce. However, their security mechanisms become vulnerable when faced with quantum computing capabilities.

& Vulnerability of Current Cryptographic Systems to Quantum Attacks Quantum computers’ unprecedented computational power can break current encryption methods. For example, Shor’s algorithm can break RSA encryption efficiently. The NIST predicts that by 2029, quantum computers could compromise 128-qubit AES encryption, emphasizing the urgency to develop more secure cryptographic systems.

' Research Objective: Exploring the Necessity and Potential of Post-Quantum Cryptographic System This study explores post-quantum cryptography, an emerging field aiming to withstand quantum attacks. With the potential to compromise sensitive data and disrupt digital integrity, the urgency of transitioning to a post-quantum cryptographic system is clear. This research will highlight these risks and potential solutions, acknowledging the challenges associated with this transition and current technological limitations.

( Research Method: Literature Review In this study, I focused on the correlation of other research papers with our research paper, credibility, whether the paper was scientifically proven, and recency. Research papers had to be related to our research topic “Securing the Future: The Necessity and Potential of Post-quantum Cryptographic System.” Therefore, I selected data that help us understand quantum computing theory, the structure and vulnerabilities of current encryption systems, and an in-depth understanding of post-quantum encryption. The selection of prior studies and literature was made based on reliability. Verified journals, reports published by public research institutes or universities, or books written by experts in the field were preferentially selected. Quantum computers and encryption are rapidly developing technology fields, so literature that reflects the latest research results and information was selected, but classical literature that explains the basic theories and principles of the field was also considered. I compared and analyzed the findings of different researchers. This helps us understand the potential of post-quantum cryptosystems. To explore this study, I analyzed prior research and related literature using comprehensive reviews, systematic reviews, and content analysis methods. Through a comprehensive review, I was able to understand the basic theoretical background of quantum computers, encryption, and how these technologies have evolved. Through this, it was possible to form an in-depth understanding of the complex interaction between quantum computers and cryptography.

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Next, I used systematic reviews to explore detailed issues about the vulnerabilities of existing encryption systems and how quantum computing attacks can exploit these vulnerabilities. Lastly, through content analysis methods, I could gather the information by analyzing the significance of each document and data. I focused on the reliability, generalizability, and logic of the resources to check if the information is appropriate for the study.

Advancements in Quantum Computing and Vulnerabilities of Current Cryptographic Systems Present-day encryption relies heavily on mathematical computations that are excessively time-consuming for conventional machines to decipher. Scientists, recognizing this limitation, have been diligently developing quantum computers capable of factoring increasingly larger numbers. A simplified explanation of this process involves multiplying two large integers. Calculating the product is straightforward, but finding the biggest prime factor of an extremely large number is exponentially more challenging. Nonetheless, a quantum computer can accomplish this task with relative ease, thereby cracking the code. Peter Shor developed a quantum algorithm (aptly named Shor’s Algorithm) that can factor large numbers significantly faster than a traditional computer. Shor's Algorithm employs quantum mechanics to find prime numbers, thereby breaking RSA encryption much more swiftly and efficiently than in the classical case, given that RSA relies on factorization for its methodology. [1]

Figure 1: Classical Cryptographic System (Ugwuishiwu, C. H., Orji, U. E., Ugwu, C. I., & Asogwa, C. N. (2020). An overview of quantum cryptography and Shor’s algorithm. Int. J. Adv. Trends Comput. Sci. Eng, 9(5).) Grover's algorithm, another quantum computing algorithm, is specialized in solving search problems and can locate specific values in unordered data much faster than traditional computing. Unlike binary search algorithms used in traditional computing, Grover's algorithm exploits the characteristics of quantum computing, presenting a given dataset as a quantum bit, and utilizing it to manipulate and retrieve the data. The algorithm expresses a given dataset as a quantum state and then manipulates this state using a quantum gate. In this manipulated state, the quantum gate is repeatedly applied to locate a specific value. The time complexity of Grover's algorithm is O(¥N), which operates faster than the O(log N) of binary search algorithms used in traditional computing [2]. Therefore, Grover's algorithm can be especially useful for locating specific values in large datasets.

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Figure 2: Quantum circuit for Grover’s algorithm (Younes, A. (2008). Strength and weakness in Grover's quantum search algorithm. arXiv preprint arXiv:0811.4481.) Finding the key to AES encryption traditionally requires trying every possible key, but Grover's algorithm considerably reduces the number of attempts. It can locate a key for AES within approximately the square root of the key space. For instance, a 128-bit AES key only requires about 2^64 attempts to find the key. [3] Public-key cryptosystems like RSA hinge on the multiplication of large prime numbers to carry out encryption, and the complexity of factoring those prime numbers. While this process is daunting for classical computers, quantum computers can easily deconstruct these large numbers using Shor's algorithm. In the case of symmetric-key encryption systems, decrypting is straightforward if you possess the secret key, but locating the key is a daunting task. Nevertheless, with quantum computing, this task can be efficiently solved with Grover’s algorithm. [4]

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Figure 3: How the RSA algorithm works by producing large prime numbers. (GeeksforGeeks. (2022, December 3). How to generate large prime numbers for the RSA algorithm. GeeksforGeeks. https://www.geeksforgeeks.org/how-to-generate-large-prime-numbers-for-rsa-algorithm/) Given the limitations and vulnerabilities of existing cryptographic systems against the prowess of quantum computers, the importance and urgency of developing post-quantum cryptographic systems cannot be emphasized enough.

a. Fundamental Theory of Post-Quantum Cryptography System i. Definition and Principles of Post-Quantum Encryption ii. Key Types of Post-Quantum Cryptographic Systems and Their Correspondence Post-quantum cryptography is an area of cryptographic research being explored to counter security threats arising from advances in quantum computing. The field is being developed in response to the possibility that quantum computers may be able to break current symmetric-key cryptography or public-key cryptography. Lattice-based encryption is an encryption scheme based on a mathematical structure called a lattice, which resembles a grid of graph paper. The scheme leverages the complexity of the lattice to provide security. Major algorithms in this category include lattice-based machine learning encryption and lattice-based synthetic encryption.

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Figure 4: Example for lattice-based encryption in a two-dimensional lattice: The secret, well-formed base is {sഓ0, sഓ1 }; the public, “scrambled” base is {pഓ0, pഓ1 }. The sender uses {pഓ0, pഓ1 } to map the message to a lattice point mഓ and adds an error vector to obtain the point ഓc. The point ഓc is closer to mഓ than to any other lattice point. Therefore, the receiver can use the well-formed secret base {sഓ0, sഓ1 } to easily recover mഓ (dotted vectors); this is a hard computation for an attacker who only has the scrambled base {pഓ0, pഓ1 }. For a secure scheme, the dimension of the lattice must be much higher than 2 as in this example. (Dr. Ruben Niederhagen, prof. dr. Michael Waidner - Fraunhofer sit. (n.d.). https://www.sit.fraunhofer.de/fileadmin/dokumente/studien_und_technical_reports/Practical.PostQuan tum.Cryptography_WP_FraunhoferSIT.pdf ) Code-based encryption is an encryption method that utilizes the properties of linear codes. Linear codes are mathematical tools used for error correction, and code-based cryptography leverages these properties to perform secure key exchange and message authentication. It uses a combination of codes like the math concept of a matrix. A representative algorithm is McEliece encryption. Polynomial hash-based encryption is an encryption method that utilizes a hash function that converts an arbitrary message into a polynomial to ensure the integrity of the message and perform authentication. NTRU-based algorithms belong to this type of encryption method.[5]. Multivariate cryptography is another type of encryption method based on multivariate polynomials [6]. Because it provides a shorter signature than other encryption methods, it is considered one of the future cryptography methods. As one of the challenges for post-quantum cryptography was the size of the signature, shorter encryption methods like multivariate cryptography are in the limelight. How post-quantum encryption works depends on the specifics of each technique, but in general, it leverages the properties of quantum computing to make it difficult for quantum computers to decrypt. For example, lattice-based encryption utilizes the intractability of the lattice problem to perform encryption, and code-based encryption uses the complexity of linear codes to constrain the computational power of quantum computers [7]. These principles of operation help explain why it is difficult for quantum computers to break post-quantum encryption.

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iii.

Discussion on how post-quantum encryption responds to quantum forgery

Post-Quantum Cryptography is Quantum-Safe Cryptography designed to guard information from quantum computers’ attacks and operate on existing computers and networks. Post-Quantum Cryptography replaces Public Key Cryptography algorithms already five decades old with ones that can resist the Quantum Threat. Unlike traditional encryption, which involves complex mathematical computation, quantum cryptography utilizes the principles of quantum mechanics to encrypt messages. This makes quantum cryptography much more secure, perhaps even unhackable. Quantum cryptography uses the laws of quantum physics to transmit private information in a way that makes undetected eavesdropping impossible [8].

Post-Quantum Cryptography algorithms are built on problems that are hard for Quantum Computers, and they are executed on classical computers. Examples of such algorithms are based on problems of Lattice such as Modulo Learning With Errors [Kyber], Modulo Learning with Rounding [Saber], Ring Learning With Rounding [NTRU], and Learning With Errors [FrodoKEM], or problems of codes such as Goppa codes [Classic McEliece] [9].

Figure 5: NIST (National Institute of Standards and Technology) announced Post Quantum Algorithms Selections that could prevent attacks on quantum computers. (Dougfinke. (2023, May 9). Nist to announce PQC algorithm selections on July 5, 2022. Quantum Computing Report. https://quantumcomputingreport.com/nist-to-announce-pqc-algorithm-selections-on-july-5-2022/) New applications could be built entirely using Post-Quantum Cryptography algorithms, but the existing applications need to transfer to new cryptography in an incremental and managed manner. To ease the transition, cryptographic agility - the ability to use mixed algorithm suites - is needed.

1. Challenges of Implementing Post-Quantum Cryptography Systems (Limitation) There are many limitations for post-quantum cryptography systems to be commercialized or developed. First, it is hard to prove the security of the post-quantum cryptography system. Because of a lack of technology, it is not possible to prove post-quantum cryptography’s safety when attacked by quantum computers. Secondly, only a few people know about the field of quantum computers or post-quantum cryptography. Due to a lack of interest and technology, the number of people who try to study

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post-quantum cryptography is small. Thus, difficulty in training makes professional manpower a challenge. Third, it is important to standardize the post-quantum cryptography system in order to build and deploy it, but standardizing is currently difficult. Because many research institutes or companies adopt various quantum cryptographic systems, compatibility, and standardization require time for development. The cost required to unify these companies and research institutes will be astronomical. Therefore, commercialization may be difficult until these problems are solved. Lastly, there are no current algorithms for post-quantum cryptography systems. Although companies like Google or federal agencies like NIST work to finalize or create the technologies to make the post-quantum cryptography algorithms, there are no completed versions of algorithms to create post-quantum cryptography. 2. Conclusion There are various current cryptography systems used by the government, big companies, and many other places to protect important information from attacks. However, due to the development of quantum computers, there are large threats posed to the current cryptography system. In this research, I explored the significance of the post-quantum cryptography system and the positive influence of the development of post-quantum cryptography on securing the data. Although because of a lack of interest, support, and technology, I also studied the limitations of the development of post-quantum cryptography and how the challenges could be solved. According to NIST (National Institute of Standards and Technology), a lot of their final systems for post-quantum cryptographic standards have trouble for not working as they are supposed to work. For example, they have challenges with the size of the signature being big, more processing requirements to make the system perfect, and problems not connecting senders and recipients properly. The future direction of the post-quantum encryption system is expected to require a lot of study. Research and development will be needed in various areas such as strengthening stability, improving efficiency, strengthening standardization and compatibility, responding to attacks from evolving quantum computers, and finally, industrial application and security utilization. The threat of quantum computers on the current cryptography system brought the post-quantum cryptography system as a replacement for the current system. The necessity of the development of cryptography systems is shown in almost every field such as banking systems and government. Using a literature review, I studied the importance of the post-quantum system following the quantum attack and the challenge it will face in the future. Due to the limitations of current technology, it is impossible to fight all the challenges caused by different cryptography systems. Further study will be needed to assure the security of both individuals and society as a whole.

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References : [1]Lee, J. (2007). A Study on the RSA Open Cryptography System and All Attacks. (dissertation). Ju-haeng Lee, Incheon, Gyeonggido. [2]Yuan, Q. (2009). Quantum online algorithms (dissertation). Yuan, Qingqing, Santa Barbara, California. [3]Jeon, S. (2003). A Study on Database Protection Using AES Algorithm (dissertation). Jeon Sang-deok, Seoul. [4]GeeksforGeeks. (2022, December 3). How to generate large prime numbers for RSA algorithm. GeeksforGeeks. https://www.geeksforgeeks.org/how-to-generate-large-prime-numbers-for-rsa-algorithm/ [5]Hashing key based analysis of Polynomial Encryption Standard - MECS Press. (n.d.). https://www.mecs-press.org/ijcnis/ijcnis-v8-n11/IJCNIS-V8-N11-5.pdf [6]Jayashree Dey Indian Institute of Technology Kharagpur, Dey, J., Kharagpur, I. I. of T., Ratna Dutta Indian Institute of Technology Kharagpur, Dutta, R., Koichiro, A., Daniel, A., Magali, B., R., B. E., Luk, B., Ward, B., Henri, B. O. and G., Bruno, B., F., B. J., Daniel, C., Felipe, C., Ryann, C., Daniel, C. R. and S.-T., Antoine, C., … Metrics, O. M. A. (2023, December 1). Progress in multivariate cryptography: Systematic Review, Challenges, and Research Directions. ACM Computing Surveys. https://dl.acm.org/doi/10.1145/3571071#:~:text=Multivariate%20cryptography%20is%20the%20gene ric,is%20NP%2Dhard%20in%20general. [7]A decade of lattice cryptography - IACR. (n.d.-a). https://eprint.iacr.org/2015/939.pdf [8]Admin. (2023, March 14). Quantum-safe cryptography and the Quantum Threat. PAM solutions, Key Management Systems, Secure File Transfers. https://www.ssh.com/academy/cryptography/what-is-quantum-safe-cryptography [9]Analysis of Post-Quantum Cryptography use in practice - researchgate. (n.d.). https://www.researchgate.net/profile/Avtandil-Gagnidze/publication/350727272_Analysis_of_Post-Q uantum_Cryptography_Use_in_Practice/links/606ee4ba92851c8a7bafc2e2/Analysis-of-Post-Quantum -Cryptography-Use-in-Practice.pdf

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Interaction of Thigmomorphogenesis and Nutrient Application on the Production of Basil Author 1

Full Name

Kim, Aaron Junung

HPrep Academy

(Last Name, First Name)

School Name

ABSTRACT: This research paper aims to explore how the application of nutrients (nitrogen, phosphorus, and potassium) and thigmomorphogenesis (plant’s response to mechanical disturbance) influences the growth of basil. In this study, Arduino, a setting that operates mechanical perturbation, was used to disturb plants mechanically, and plants were grown in a hydroponic setting. The finding from this research suggests that a positive correlation between the delivery of nutrients and thigmomorphogenetic response exists. When basils are applied with nutrients, they tend to grow taller in every aspect. This finding will result in improvement in agriculture. Although the experiment lacks accurate measurement and advanced tools, this experiment can be improved with the use of precise measuring equipment and sophisticated techniques.

KEYWORDS: Basil, Touching, Plant, Nutrient, Thigmomorphogenesis

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1. Introduction Recently, analytical research has proven that there is an increased demand for the use of herbs for therapeutic purposes. Among those herbs, Basil which gained popularity as a tonic agent and vermifuge in the past, has been gaining the most attention from scientists due to its rich medical properties and health benefits.[1] The beneficial properties of basil are anticancer, hepatoprotective, hypoglycemic, and hypolipidemic. As a result of the increasing trend of interest, it has become significant to understand methods to further enhance the production of basils.[2] Known as Ocimum basilicum, basil is one of the most farmed herbs due to its wide spectrum of uses in various cuisines, decorative purposes, and therapeutic uses. Due to its wide application, basil has been used as traditional medicine for remedial purposes since the past, especially throughout the Old World. As it demonstrates long-time medical use, basil contains abundant medical components. Mueen Ahmad Ch et al. (2015) noticed from their experiments that basil application has beneficial impacts due to its anti-inflammatory properties.[1]

The anti-inflammatory property of basil derives from its compounds, including phenolic substances such as Rosmarinic acid and Chicoric acid. Basil contains substantial amounts of these compounds, which gives basil inflammatory effects.[3] According to the research, these substances play a significant role in inhibiting the inflammatory mediator and enzymes, resulting in a relieved inflammatory response. Its impact on inflammatory response shows the historical use of basil for medical use.

Additionally, basil contains high phenol compounds that contribute to its medical benefit as an antioxidant. These compounds contribute to relieving oxidative stress in the body, which are causes of various diseases and chronic inflammation.[4] It also neutralizes these stresses, being a valuable element for maintaining health. It is thought that these properties of basil enhance antioxidant activity, increasing basil’s therapeutic potential.

Besides basil’s anti-inflammatory and antioxidant properties, several other pharmacological advantages exist. According to Li et al. (2017), basil has many health benefits, which include antitumor, anti-oxidant, and anti-aging properties. Additionally, it supports immune system enhancement, has antimicrobial qualities, and can be used to treat various chronic diseases such as diabetes mellitus and cardiovascular health.[4] Also, Mueen Ahmad Ch et al. (2015) explain that “basil possesses central nervous system (CNS) depressant, anticancer, cardiac stimulant, hepatoprotective, hypoglycemic, hypolipidemic, immunomodulator, analgesic, anti-inflammatory, antimicrobial, antioxidant, antiulcerogenic, chemomodulatory and larvicidal activities.”[1]

In this research, an experiment to test the impact of mechanical perturbation and the application of nutrients on basil growth will be conducted. During the experiment, basils were grown in a hydroponic setting that constantly provided adequate light, water, and basic nutrients for the basils. According to Mamun et al. (2023), hydroponic agriculture has several benefits over the conventional farming method; it provides a higher production rate of plants, which require less time while providing food with higher value.[1] Moreover, problems that exist in conventional farming no longer affect the production of crops in hydroponic farming. This implies that in the future when overpopulation significantly affects the existing population through a food shortage, hydroponic farming could be a solution.

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This research paper will investigate how Thigmomorphogenesis, a plant’s long-term response to touch, affects basil production in the presence of additional nutrients (phosphorus, potassium, and nitrogen).[5] To accomplish this purpose, this study will use Arduino to set up touch-induced settings for plants, which will constantly disrupt basil. By analyzing data in the data analyzing tools Matlab and Stata, this study will gather data for the growth rate of each plant.

Thigmomorphogenesis is plants' response to external stimuli. Janet Braam and E. Wassim Chehab (2017) explain, “Thigmomorphogenesis derives from three Greek roots, ‘stigma’ for touch, ‘morphe’ for form or shape, and ‘genesis,’ for origin or generation.” As the term explains, due to Thigmomophogenesis, plants grow stockier in width and develop more chlorophyll components.[5] The reason why plants evolved this response is astonishing: plants in harsh conditions must withstand mechanical perturbations and not get affected by the same factor more than once. According to Telewski et al. (1986), it was observed that A. fraseri grown against the wind had undergone radial expansion due to higher cell division.[6] These modifications resulted in better morphology for plants to survive the windy environment.

In previous research papers on Thigmomorphogenesis, it was found that calcium, Jasmonates, ethylene, and auxin are chemical molecules that are responsible for changes in the morphology of plants after touching.[7] First of all, how do plants recognize when it is ‘touched’? Sara Zaske mentioned that, from the experiment conducted by Knobluach and his team, it was found that plants' cells release calcium ions to adjoining cells when they recognize external stimuli. Additionally, from this experiment, the team noticed that, unlike animal cells that sense stimuli through sensory cells, plant cells sense pressure through the cell wall, which is common in all plant cells.[8]

Also, according to Braam and Davis (1990), Calcium, Jasmonate, Ethylene, and Auxin play significant roles in thigmomorphogenesis.[9] Calcium, being an essential signaling molecule in most organisms, shows an immediate increase upon receiving mechanical stimuli. Also, calmodulin and calmodulinlike proteins have touch inducibility, and when Ca binds to them, they regulate other target enzymes. As a result, increased Ca level inside the cell causes modification of the plant’s shape and growth pattern. Overall, this suggests that Calcium is deeply involved in response to mechanical stimuli as a secondary messenger, which impacts the process of growth and development in plants. 2+

Furthermore, Jasmonate, being the plant hormone involved in the regulation of growth and response to various external stresses, plays a pivotal role in plants' response to external stimulation.[10] When plants undergo mechanical perturbations, the Jasmonate level inside the plant increases, which is associated with a change in morphology and growth pattern of the plant, similar to the thigmomorphogenesis response.[9] According to Sohn et al. (2022), Jasmonate contributes to inhibited growth of root, hypocotyl, deletion in flowering, petal expression, and cause of leaf senescence.[11] However, while it is still unknown how Jasmonate interacts with other plant hormones and causes inhibitions in overall plant growth, there is certainly a direct relationship between the level of jasmonate and the delayed growth of plants.

Ethylene is another phytohormone that regulates a plant’s life cycle including growth, reproduction, seed germination, ripening of fruits, and leaf and flower senescence. The endogenous level of Ethylene increases when the plant receives mechanical perturbation. According to Iqbal et al. (2017), it was known that a high concentration of Ethylene would cause an inhibitory effect on plant growth, which indicates that a high level of ethylene caused by touch-induced accumulation would lead to slower growth of plants.[12]

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When plants are touched repetitively, they tend to grow at slower rates due to thigmomorphogenesis.[6] On the other hand, it is widely known that providing plants with nutrition fosters the growth of plants, which provides the opposite effect of mechanical perturbation on the plants. Nutrients that will be additionally provided are nitrogen, phosphorus, and potassium. These NPK(nitrogen, phosphorus, and potassium) are generally known to increase plant yield and growth.[7] Nitrogen. Nitrogen, being the most abundant element in the atmosphere, is also an essential nutrient for the growth of plants. Nitrogen is one of the most significant elements for plants due to numerous reasons. A plant’s ability to uptake phosphorus from fertilizer is heavily affected by the presence of nitrogen fertilizer.[13] Nitrogen promotes growth in the root and enhances the plant's ability to absorb phosphorus from the soil. Moreover, nitrogen deficiency in plants would lead to the yellow color of leaves due to lacking amount of chlorophyll in leaves, quicker senescence, and slowed shoot growth.[14], [15]

Phosphorus. Phosphorus is also an essential nutrient for plant growth other than Nitrogen. It is responsible for the pivotal functions of plants. Ishan Ajmera et al. (2019) explain that phosphorus is deeply involved in a plant's energy transfer.[16] Being the fundamental element for energy molecules, adenosine triphosphate(ATP), in organisms, phosphorus allows plants to facilitate energy storage and transfer. In advance, ATP plays vital functions in various parts of the metabolic systems of plants, including photosynthesis, respiration, and nutrient uptake.

Additionally, Phosphorus is an essential element that promotes root growth in young plants. According to Niu et al. (1959), in an environment of low phosphorus, plants generally change their root system through short and lateral root development, which plants to absorb nutrients from wider areas with higher efficiency, allowing plants to grow in low phosphorus conditions.[3] Also, phosphorus deficiency causes the photosynthesis rate to drop in the plant, leading to slower growth and development in plants.[17] As a result, a deficiency of phosphorus in plants will cause abnormal coloration, reduced leaf size, and inhibit the development of the shoot.[18]

Potassium. Potassium, being another essential element for plant growth, is involved with various physiological and metabolic processes of plants. Potassium plays a role as a key molecule for enzyme activation in plants.[19] This enzyme includes sugar transportation, protein synthesis, photosynthesis, and osmoregulation, which all of these are crucial parts of a plant’s survival. Potassium is vital for photosynthesis, where plants convert sunlight into high-energy chemicals. Potassium stimulates ATPases in the plasma membrane, leading to an acid-stimulated response that results in cell wall relaxation and activation of hydrolytic enzymes. This process supports photosynthesis and promotes cell growth. This process produces abundant carbohydrates, which provide plants with the energy and building blocks they need for growth and development.

Furthermore, Potassium is capable of doing something other than energy production. Potassium plays an important role in osmotic regulation, which is vital for maintaining the plant’s turgor pressure and water balance. As a mineral with low water potential, plants utilize potassium as an element for regulating water potential.[19]

Therefore, the research paper hopes to find how the difference in nutrient availability and thigmomorphogenesis influences the growth of basil production.

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2. Methods and Materials 2.1 Plant Groups Due to basil’s pronounced medical benefit, basil was chosen for the experiment. The basil groups’ response to essential nutrients and mechanical perturbations will be observed and be recorded 13 times. Data will be gathered from 8 groups that represent different nutrient application conditions and frequency of mechanical distribution. The group will be mainly separated into 2 sections, each containing 4 groups. The first section will contain 4 groups: group 1, group 2, group 3, and group 4. The Image 1.1 second section will contain other sets of 4 groups: group 5, group 6, group 7, and group 8. All four groups in section 1 will be applied with nutrients, while those in section 2 won’t be. Every 4 groups in each section will be treated with a different frequency of mechanical perturbation. Groups 1 and 5 won’t be disturbed. Groups 2 and 6 will be every hour. Groups 3 and 7 will be every 3 hours. Lastly, groups 4 and 8 will be disrupted every 6 hours.

2.2 Arduino Settings The touch will be done by an Arduino set that will be programmed to touch plants every 1 hour, 3 hours, and 6 hours as aforementioned. Servo motors from the Arduino that are connected to the CPU will be used. As it is shown in the image, the orange line is connected to 9, while the red line is connected to 5v, which provides voltage for the motor. Additionally, the brown line will be connected to the Ground. This line will receive a signal from the CPU and send it to the servo motor, which will enable mechanical perturbation for the plants.

2.3. Data Analysis Tools Matlab and Stata. In terms of data analysis, Matlab and Stata will be used. Matlab is a program where various methods for data analysis can be done: this includes graphing data, creating tables, and plotting data in 3D models. Using Matlab, data gathered from observations will be plotted on a scatter plot, which will provide a general growing trend of basil groups in different conditions. Stata is another data analyzing tool that allows visualization and analysis of data. In this research, Stata will provide a detailed analysis of the relationship between variables in the experiment.

2.4. Controlled Environment Controlled Variable. To gain a clear and only relationship between a dependent variable and the independent variable, other variables are not supposed to interfere. This means that other variables must be excluded and remain constant throughout the experiment. Therefore, to create a condition where all plants grow in equivalent conditions except for nutrient availability and mechanical perturbation, all other factors that can potentially influence a plant's growth must be controlled. These factors include light exposure, amount of water available, humidity, and temperature.

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Light Exposure. Light provides energy for plants to grow, reproduce, and survive. Plants gain energy through the process of photosynthesis, where chlorophylls inside the green leaf of the plants convert light energy from photons to usable form chemical energy. According to the University of Minnesota Extinction, in conditions of light shortage, plants’ leaves might have abnormal colors like yellow due to decreased chlorophyll production. Additionally, leaves can undergo senescence and shed leaves. Moreover, the plant's stem can appear thinner and less healthy. Overall, unequal distribution of light for plants will cause varied growth rates between the plants, eventually interrupting the result of the experiment. Therefore, light must be controlled since it will be grown under the same light source at an equal distance throughout the experiment.

Amount of Water Available. As light is an essential source for a plant's survival, so is water, according to WVE, extinction. Edu, water takes up to 95 percent of plant tissue and is essential for various activities, including plant growth and seed germination. However, the most important feature of water in plants is that it is directly related to photosynthesis. For plants to create food from carbon dioxide and sunlight, water must be divided through the process of hydrolysis, which separates oxygen and hydrogen molecules from water molecules. Then these oxygen molecules are reduced by electron molecules from the Electron Transfer Chain. Hydrogen molecules from water are also gathered in a place called thylakoid that is located inside the chlorophyll and creates chemical gradients, enabling ATP synthase to create ATP for plants. Therefore, without water, plants cannot perform photosynthesis only from carbon dioxide and sunlight. Therefore, the same amount of water must be provided for the plants of all groups to ensure plant growth is only affected by thigmomorphogenesis response and amount of nutrient availability.

Humidity. Humidity is another important factor in the growth of plants. According to Chia et al. (2022), it was shown that humidity increases plant growth because it keeps the stomata of plants open, which causes plants to have more water and a higher photosynthetic rate, leading to faster growth of plants.[20] This means that there is a difference in humidity between the experimental groups that would cause different growth between the plants, eventually leading to different investigation results. Temperature. Temperature is another important factor that affects not only plants but also the entire organism. Because temperature affects the molecular reaction of organisms, temperature has a quick and neglectable impact on organisms.[21] As all organisms do, plants gain food and maintain themselves through molecular processes, including photosynthesis, transpiration, respiration, and other metabolic processes. Additionally, it was known that as the temperature of the environment increases, the rate of photosynthesis, transpiration, and respiration increase correlatively. This indicates that the growth of plants heavily depends on the environment's temperature.[22] Therefore, to test all groups in the most equal and fair environment, the temperature must be controlled the same. Amount of Additional Nutrients. Besides nitrogen, phosphorus, and potassium, plants require a lot of nutrients for healthy growth. Calcium (Ca), magnesium (Mg), and sulfur (S) and the micronutrients chlorine (Cl), boron (B), iron (Fe), manganese (Mn), copper (Cu), zinc (Zn), nickel (Ni) and molybdenum (Mo) are elements that can be obtained from soil and are needed for plants to survive.[23] In addition, there are other molecules needed for plants to survive. This indicates that if plants are given different amounts of these elements, it might cause different growth rates of plants and lead to unequal experiment results. As a result, plants will be grown in the same Hydroponic Cultivator that is filled with the same nutrient component, which provides the same nutrient, except for nitrogen, phosphorus, and potassium, for all plant groups.

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Independent variables. As aforementioned, from many previous researches, it was known that nitrogen, phosphorus, and potassium are the 3 most essential elements that are associated with plant growth. On the other hand, in most cases, the thigmomorphogenesis response of the plants caused by mechanical perturbation causes slower growth of the plant and a change in the plant’s morphology. Overall, since these factors influence the course of a plant's growth, they are set as independent variables. Amount of Nutrients: Nitrogen, Phosphorus, and Potassium. In this research paper, NPK 20-20-20 (amazon.in/shiviproducts.) was used to provide enough nitrogen, phosphorus, and potassium for basil. Basil groups that were given nutrients were provided with a 10 ml solution that mixed fertilizer and water in a 1:10 ratio. Dependent variables. The most visible change in a plant that occurs due to mechanical perturbation is its inhibited growth in height (cm). Setting height as a dependent variable for this experiment, the height of the plant is measured from all 8 groups of basil. Additionally, because thigmomorphogenesis affects growth, there will be a difference in growth rate(dH/dt). Therefore, changes in height from the previous measure will be recorded for accurate data.

3. Results

Variable

Observation

Mean

Standard Deviation

Minimum

Maximum

Temperature

27.8

1.8

25.8

31.7

Humidity

0.53

0.05

0.43

0.61

Table 1.1 Table 1.1 provides the condition of the experiment during the 14 days of the observation. This table demonstrates that during the 13 temperature and humidity observations, the mean temperature was DURXQG Û& &HOVLXV GHJUHH ZLWK D VWDQGDUG GHYLDWLRQ YDOXH RI Û& 7KH FRROHst record was done ZKHQ WKH WHPSHUDWXUH ZDV Û& ZKLOH WKH RSSRVLWH ZDV GRQH ZKHQ WKH WHPSHUDWXUH ZDV Û& Additionally, the mean temperature humidity was 53% with a standard division value of 5%. The driest record was 43% while the most moist record was 64%.

Number of obs

104

F(5, 98)

63.42

Prob > F

0.0000

R-squared

0.7639

Adj R-squared

0.7519

Root MSE

0.92792

Table 1.2

379

Height

Coef.

Std. Err.

P > | t | [95% Conf.

Interval

Day

0.2776823

0.024663

11.16

0.000

0.2283028

0.3270618

Touched_0123

-1.067096

0.0815164

-13.09

0.000

-1.228863

-0.9053291

Temperature

0.0597659

0.0574952

1.04

0.301

-0.0543315

0.1738634

Humidity

1.064563

1.94912

0.55

0.586

-2.803403

4.932529

Nutrition

0.7326823

0.1819802

4.03

0.000

0.3715585

1.093826

Table 1.3 The most significant point of Table 1.2 and 1.3 is that it shows the coefficient values of the independent variables (IV) on explaining Height (DV). Column of Coef. (coefficient) shows that value Humidity has the largest value as it has 1.064563. This indicates that Humidity has the most impact on the Height of the basil. Then Coef. is followed by Nutrition, Day, Temperature, and Touched_0123. While all other variables have a positive coefficient with Height, only Touched_0123 has a negative value. This indicates that when plants are touched (Touch_0123), the Height of plants is negatively affected, and growth decelerates. Only considering Coefficient of Humidity must have the greatest impact on the basils. However, because P > | t | (P value) is far above 0.05, which is standard for statistically significant 95 percent confidence, Humidity is not statistically significant for an explanation of Height in the experiment. In addition, because the P value of Temperature is more than 0.05, Temperature is not as statistically significant as Humidity is. This indicates that only 3 variables that are below 0.05, Day, Touched_0123, and Nutrition, have statistical significance on the Height of the basil. As a result, excluding time (day), only Nutrition (nutrient) and Touched_0123 (mechanical perturbation) are set as independent variables.

Figure 1.1 Figure 1.1 demonstrates 4 basil groups that are not applied with additional nutrition. Each group indicates a different touching frequency. Untouched Basil groups represent Basil groups that are not treated with any mechanical perturbation. On the other hand, Touched Basil1, Touched Basil2, and Touched Basil3 represent frequencies of 6 hours, 3 hours, and 1 hour. In the graph, there is a clear difference in the growth rate of basil between untouched groups and touched groups. The blue graph, which represents untouched basils, exceeds the height of all other three groups on every observation. Moreover, there is a trend that as touch frequency increases, the growth rate of basil tends to decrease.

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Figure 1.2 Similar to Figure 1.1, Figure 1.2 represents the different groups of basils based on the touch frequency. However, these groups were applied with additional NPK nutrients. The general trend of the groups is almost exact to that of Figure 1.1. However, the only difference is that basils, which received additional nutrients, grew taller than those without nutrients. This reflects that additional application of NPK nutrients causes basils to grow at a higher rate even with basil’s thigmomorphogenetic response.

Figure 2.1 Figure 2.1 shows the difference in the height of plants in existence or the nonexistence of additional nutrients. Dots plotted on 0 of the x-axis represent basils not applied with nutrients, while dots on 1 represent basils applied with nutrients. The height of both groups was averaged by collecting all the data on whether plants were touched or not. As the graph shows, distinct differences in height between two populations of dots are plotted. In addition, it is noticeable that the basil of group 1 has a slightly higher height than that of group 0. From these, it is possible to notice that this change is coming from the different applications of NPK composition. Therefore, it can be inferred from Figure 2.1 that there is a positive relationship between the application of nutrients and thigmomorphogenesis on the growth of plants.

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4. Conclusion and Discussion In conclusion, this research paper investigated how the interaction between the thigmomorphogenesis response of plants and different applications of nutrients (nitrogen, phosphorus, and potassium) affect the growth rate of basil.

Several researches have been done about Thigmomorphogenesis, aiming to understand the mechanism of thigmomorphogenesis and the interaction between mechanical perturbation and other external stimuli in plant growth. Nonetheless, there needs to be more research on how different applications of nutrients on plants affect a plant's thigmomorphogenetic response.

To address the question of how additional application of NPK (nitrogen, phosphorus, and potassium) affects the thigmomorphogenetic response of plants, the height of 8 basil groups was measured, and four groups of basils were provided with additional amounts of NPK fertilizer. In addition, Arduino was used to disturb plants, while Matlab and Stata were used to analyze data. As a result, from the data that was gathered and analyzed, it was concluded that there is an actual positive relationship between additional NPK and mechanical stimulation on the growth of the basils. When treated with more NPK fertilizer, basils showed a higher growth rate.

Although I have concluded the effects of nutrients and mechanical disturbances, this research can be improved in various aspects. Unfortunately, due to a lack of adequate and advanced laboratory equipment, it wasn’t able to find out the exact relationship between the application of nutrients and plant thigmomorphogenesis response on mechanical perturbation. Initially, this research aimed to figure out the change in the level of calcium, ethylene, jasmonate, auxin, and other macromolecules after the plants were exposed to mechanical perturbation. Furthermore, data might include some errors. Because the height of the plants was measured using a ruler by hand, data might differ if it is measured with equipment with higher accuracy and precision. In the future, when this experiment is repeated for similar purposes, using camera settings to record the gradual growth of plants and measuring tools with higher accuracy will provide a more lucid data set to investigate the effect of mechanical perturbation on plants.

Overall, I hope this study provides an appropriate guideline for growing healthier plants in the agricultural aspect. Furthermore, knowing the relationship between the nutrient and thigmomorphogenetic response will help determine how nutrients can be used most effectively, preventing any waste of nutrients. This, in turn, provides economic benefits for the agriculture industry.

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Appendix

Matlab_code1 %%% Untouched (cm) Height_Basil_untouched = [data ]; %%% Touched Height_Basil_touched1 = [data]; Height_Basil_touched2 = [data]; Height_Basil_touched3 = [data]; %%% Date after transplanting on a hydroponic Da1 = [date]; p1 = polyfit(Da1, Height_Basil_untouched, 1); y1 = polyval(p1, Da1); p2 = polyfit(Da1, Height_Basil_touched1, 1); y2 = polyval(p2, Da1); p3 = polyfit(Da1, Height_Basil_touched2, 1); y3 = polyval(p3, Da1); p4 = polyfit(Da1, Height_Basil_touched3, 1); y4 = polyval(p4, Da1); subplot(1,1,1); plot(Da1, Height_Basil_untouched, 'bo', 'Markersize', 10, 'linewidth', 2); hold on; plot(Da1, Height_Basil_touched1, 'ro', 'Markersize', 10, 'linewidth', 2); plot(Da1, Height_Basil_touched2, 'ko', 'Markersize', 10, 'linewidth', 2); plot(Da1, Height_Basil_touched3, 'go', 'Markersize', 10, 'linewidth', 2); xlabel('Time(days)') ylabel('Height(cm)') set(gca, 'fontsize', 20) xlabel('Time(days)') ylabel('Height(cm)') legend({'Untouched Basil', 'Touched Basil1', 'Touched Basil2', 'Touched Basil3'}, 'Location', 'northwest') set(gca, 'fontsize', 20); Return; Arduino_code Servo servo1; Servo servo2; int pos = 0; void setup() { servo1.attach(2); servo2.attach(3); }

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void loop() { for (pos = 0; pos <= 180; pos += 1) { servo1.write(pos); delay(100); } delay(900000); for (pos = 180; pos >= 0; pos -= 1) { servo1.write(pos); delay(100); } delay(900000); for (pos = 0; pos <= 180; pos += 1) { servo2.write(pos); delay(100); } delay(900000); for (pos = 180; pos >= 0; pos -= 1) { servo2.write(pos); delay(100); } delay(900000); }

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References [1] M. Ch, S. Naz, A. Sharif, M. Akram, and M. Saeed, “Biological and Pharmacological Properties of the Sweet Basil (Ocimum basilicum),” Br. J. Pharm. Res., vol. 7, no. 5, pp. 330–339, Jan. 2015, doi: 10.9734/BJPR/2015/16505. [2] “Spices and herbs: global market size forecast,” Statista. https://www.statista.com/statistics/876234/global-seasoning-and-spices-market-size/ (accessed Aug. 03, 2023). [3] P. M. Nguyen, E. M. Kwee, and E. D. Niemeyer, “Potassium rate alters the antioxidant capacity and phenolic concentration of basil (Ocimum basilicum L.) leaves,” Food Chem., vol. 123, no. 4, pp. 1235–1241, Dec. 2010, doi: 10.1016/j.foodchem.2010.05.092. [4] H. Li et al., “Evaluation of the chemical composition, antioxidant and anti-inflammatory activities of distillate and residue fractions of sweet basil essential oil,” J. Food Sci. Technol., vol. 54, no. 7, pp. 1882–1890, Jun. 2017, doi: 10.1007/s13197-017-2620-x. [5] J. Braam and E. W. Chehab, “Thigmomorphogenesis,” Curr. Biol., vol. 27, no. 17, pp. R863– R864, Sep. 2017, doi: 10.1016/j.cub.2017.07.008. [6] F. W. Telewski and M. J. Jaffe, “Thigmomorphogenesis: Field and laboratory studies of Abies fraseri in response to wind or mechanical perturbation,” Physiol. Plant., vol. 66, no. 2, pp. 211– 218, Feb. 1986, doi: 10.1111/j.1399-3054.1986.tb02411.x. [7] E. Darwish et al., “Touch signaling and thigmomorphogenesis are regulated by complementary CAMTA3- and JA-dependent pathways,” Sci. Adv., vol. 8, no. 20, p. eabm2091, May 2022, doi: 10.1126/sciadv.abm2091. [8] S. Zaske, “Plants can distinguish when touch starts and stops,” May 2023, [Online]. Available: https://news.wsu.edu/press-release/2023/05/31/plants-can-distinguish-when-touch-starts-andstops/ [9] E. W. Chehab, E. Eich, and J. Braam, “Thigmomorphogenesis: a complex plant response to mechano-stimulation,” J. Exp. Bot., vol. 60, no. 1, pp. 43–56, Nov. 2008, doi: 10.1093/jxb/ern315. [10] E. W. Chehab, C. Yao, Z. Henderson, S. Kim, and J. Braam, “Arabidopsis Touch-Induced Morphogenesis Is Jasmonate Mediated and Protects against Pests,” Curr. Biol., vol. 22, no. 8, pp. 701–706, Apr. 2012, doi: 10.1016/j.cub.2012.02.061. [11] S.-I. Sohn et al., “Jasmonates in plant growth and development and elicitation of secondary metabolites: An updated overview,” Front. Plant Sci., vol. 13, p. 942789, Aug. 2022, doi: 10.3389/fpls.2022.942789. [12] N. Iqbal, N. A. Khan, A. Ferrante, A. Trivellini, A. Francini, and M. I. R. Khan, “Ethylene Role in Plant Growth, Development and Senescence: Interaction with Other Phytohormones,” Front. Plant Sci., vol. 08, Apr. 2017, doi: 10.3389/fpls.2017.00475. [13] D. L. Grunes, “Effect of Nitrogen on the Availability of Soil and Fertilizer Phosphorus to Plants,” in Advances in Agronomy, Elsevier, 1959, pp. 369–396. doi: 10.1016/S0065-2113(08)60127-3.

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[14] “Nitrogen Deficiency,” Plone site. https://plantscience.psu.edu/research/labs/roots/methods/methods-info/nutritional-disordersdisplayed/nitrogen-deficiency (accessed Aug. 02, 2023). [15] “Managing Pests in Gardens: Trees and Shrubs: Disorders: Nitrogen deficiency—UC IPM.” https://ipm.ucanr.edu/PMG/GARDEN/PLANTS/DISORDERS/nitrogendeficiency.html (accessed Aug. 02, 2023). [16] I. Ajmera, T. C. Hodgman, and C. Lu, “An Integrative Systems Perspective on Plant Phosphate Research,” Genes, vol. 10, no. 2, p. 139, Feb. 2019, doi: 10.3390/genes10020139. [17] C. Foyer and C. Spencer, “The relationship between phosphate status and photosynthesis in leaves”. [18] “Phosphorus Deficiency,” Plone site. https://plantscience.psu.edu/research/labs/roots/methods/methods-info/nutritional-disordersdisplayed/phosphorus-deficiency (accessed Aug. 02, 2023). [19] X. Xu et al., “Effects of Potassium Levels on Plant Growth, Accumulation and Distribution of Carbon, and Nitrate Metabolism in Apple Dwarf Rootstock Seedlings,” Front. Plant Sci., vol. 11, p. 904, Jun. 2020, doi: 10.3389/fpls.2020.00904. [20] S. Y. Chia and M. W. Lim, “A critical review on the influence of humidity for plant growth forecasting,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1257, no. 1, p. 012001, Oct. 2022, doi: 10.1088/1757-899X/1257/1/012001. [21] C. C. Nievola, C. P. Carvalho, V. Carvalho, and E. Rodrigues, “Rapid responses of plants to temperature changes,” Temperature, vol. 4, no. 4, pp. 371–405, Oct. 2017, doi: 10.1080/23328940.2017.1377812. [22] E. W. Support, “Environmental factors affecting plant growth,” Ag - Community Hortic., Jan. 2019, Accessed: Aug. 02, 2023. [Online]. Available: https://extension.oregonstate.edu/gardening/techniques/environmental-factors-affecting-plantgrowth [23] P. J. White and P. H. Brown, “Plant nutrition for sustainable development and global health,” Ann. Bot., vol. 105, no. 7, pp. 1073–1080, Jun. 2010, doi: 10.1093/aob/mcq085.

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Nanotechnology and Space Exploration: How Can Carbon Nanotubes and Self-Healing Materials Contribute to Making Advancements in Space Exploration Technology? Author 1

Full Name

Kim, Jinheon

Seoul Foreign School

(Last Name, First Name)

School Name

ABSTRACT: Nanotechnology has grown rapidly since it was first introduced to the scientific field and holds the potential to advance space exploration. This research aims to solve the problems that are currently encountered in space exploration by utilizing nanotechnology, specifically carbon nanotubes and selfhealing materials. Six research papers have been reviewed to study this topic, two each focused on nanotechnology, carbon nanotubes, and self-healing materials. The paper discusses the current problems in space exploration, including the need for materials that can withstand extreme thermal conditions, UV radiation, and micrometeoroid and orbital debris impact. It also examines the challenges of detecting and manually fixing wiring problems in spacecraft. To these challenges in space exploration, carbon nanotubes and self-healing materials are potential solutions. Carbon nanotubes are stronger and lighter weight than most alternative materials, making them useful in spacecraft. Selfhealing materials can repair themselves autonomously, eliminating the need for manual repairs. The paper concludes by discussing the potential benefits of using nanotechnology in space exploration: making the spacecraft safer, more durable, more efficient, and providing the potential to increase the affordability and accessibility of space exploration.

KEYWORDS: Nanotechnology, Space exploration, Carbon nanotubes, Self-healing materials

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პ ,QWURGXFWLRQ Space traveling technology has improved in recent years as space travel has become more frequent for exploration and survival purposes. However, many challenges still need to be addressed, such as maintaining the functionality of spacecraft after collisions with micrometeoroids and the wear and tear of wires due to natural aging. Nanotechnology has the potential to address these challenges and improve space-traveling technology. Nanotechnology is the study of materials at the atomic and molecular level, and it can create new materials with properties that are not found in nature. For instance, nanotechnology could be used to create self-repairing materials that can withstand the harsh environment of space. This research will explore the role of nanotechnology in space exploration. The research will review the literature on various available nanomaterials and their functionalities. It will also examine previous research on whether nanotechnology can solve the problems that astronauts face in space and identify any correlations between these topics. These correlations can then be used to develop solutions for current space exploration using nanotechnology. This research aims to gain a deeper understanding of nanotechnology and its potential applications in space exploration. The research will focus on the mechanisms of carbon nanotubes and self-repairing technology. The findings will be used to develop new applications for nanotechnology in space exploration.

ჟ 'LVFXVVLRQ %DFNJURXQG Despite recent advances in space exploration technology, many challenges still prevent humans from exploring deeper regions of space. These challenges include economic, safety, and health issues. One of the most significant economic challenges is the amount of energy required to enter or escape the orbit. This is because the gravitational force that pulls on a spacecraft is immense, and the more massive the spacecraft, the more energy is required to overcome this force. Another challenge is the safety of astronauts. Even if a spacecraft is launched successfully, its wiring can become frayed over time, making it difficult to detect damage. If the damage is not found and repaired, it could cause the spacecraft to malfunction, putting the astronauts at risk. In addition to these challenges, a spacecraft must endure extreme thermal conditions, impacts from micrometeoroids or orbital debris, UV radiation, and material aging. These harsh conditions can impose a threat on the astronauts, as the current generation of spacecraft is not durable enough to withstand them for long periods of time. Finally, it is challenging to monitor astronauts’ health while in space. Doctors are not allowed to accompany astronauts on missions, so there is no way to provide them with medical care if they become ill or injured. These are just some of the challenges that must be addressed before humans can explore deeper regions

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of space. Nanotechnology has the potential to address many of these challenges, and this research will explore the best ways to use nanotechnology in spacecraft.

ჟ, /LWHUDWXUH 5HYLHZ (1) Nanotechnology 1.1 Nanotechnology in Space Exploration Integrating nanotechnology and space technology has gathered significant interest from many scientists. By harnessing the capabilities of nanotechnology, significant advancements in space missions are expected, ultimately bringing closer to unlocking new possibilities in space exploration. Figure 1 Nanotechnology and surface area

Source: PETA Science Consortium International e.V. https://www.thepsci.eu/nano/ (8/3/2023) Nanotechnology is an area of study that intervenes in the physics and chemistry of atoms or molecules that are less than 100 nanometers. The properties of matter no longer resemble the properties of the bulk as the size decreases to the nanometer scale. It has a unique characteristic because the optical and electronic behavior of bulk materials can also be changed as their size decreases (Sharma, 2012). Nanotechnology is expected to find applications in various fields of study. This is not an exception for the field of space exploration, as nanotechnology can contribute to many improvements in such fields. This includes reducing the costs of space exploration by minimizing the mass and volume of spacecraft, which allows the onboard autonomy (the spacecraft’s ability to operate and make decisions independently without constant human intervention) of spacecraft to be increased. According to Sharma (2012), some onboard autonomy includes essential factors such as the autonomous attitude, orbit control,

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payload data processing, health monitoring, lowering mission risks, providing superior materials with improved mechanical characteristics (carbon nanotubes and nanoparticle reinforced polymers) for space structures, and helping life support, gas storage, wastewater treatment, and sensors (Sharma, 2012).

1.2 Nanotechnology In NASA’s Vision Nanotechnology plays a crucial role in NASA’s vision for space exploration, where it seeks to develop future systems with life-like characteristics to enhance robotic missions. The goal is to enable these missions to function effectively in distant and challenging environments without continuous human control while also reducing costs through smaller and more efficient systems (S.L. Venneri, 2001). To meet the challenges of space exploration effectively and economically, NASA emphasizes the need for spacecraft with autonomy, self-reliance, self-repair, adaptability, and extreme efficiency in utilizing limited resources (S.L. Venneri, 2001).

1.3 Promising Applications of Nanotechnology Nanotechnology offers promising solutions to address these challenges. Utilizing carbon nanotubes can reduce launch vehicle weight because of their lightweight characteristics and their very strong degree of strength, optimizing space travel. Additionally, advancements in nano-phase materials, molecular electronics, and nanosensors hold the potential to improve human health monitoring systems and healthcare delivery (Sharma, 2012). One of the critical applications lies in nanoscale, biocompatible sensors that provide detailed health information at the cellular level when distributed throughout astronauts’ bodies. These sensors can be externally monitored or self-stimulated to transmit signals through chemical messengers, facilitating real-time health assessment (S.L. Venneri, 2001).

(2) Carbon Nanotubes (Problem in heavyweight) Advances in carbon nanotechnology, specifically carbon nanotubes (CNTs), present opportunities for developing multifunctional composite structures in spacecraft. CNTs are large cylindrical molecules made of a hexagonal arrangement of hybridized carbon atoms (Pernigoni et al., 2021). The application of CNTs in spacecraft has gathered significant interest due to their characteristics of low mass, high material strength, and protection against radiation. With the integration of CNTs, the safety measures of spacecraft could improve and extend the operational life of space missions. These unique properties can improve mission success and overall mission architecture, leading to more affordable space exploration (Samareh et al., 2019).

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Figure 2 Carbon Nanotubes Computer rendering of a single-walled carbon nanotube

Source: Britannica https://www.britannica.com/science/carbon-nanotube (8/3/2023)

2.1 Applications of Carbon Nanotubes CNTs have numerous beneficial applications, but challenges persist in scaling their nanoscale properties to macroscale composites without compromising their unique attributes. Researchers have explored using CNT-based nanocomposites for Electromagnetic interference/Electrostatic discharge (EMI/ESD) protection in spacecraft composite structures, aiming to eliminate the labor-intensive processes required for traditional shielding methods (Rawal et al., 2013). In the context of thermal radiation and impact protective shields (TRIPS), CNTs can be incorporated into phenolic-impregnated carbon ablators, providing both thermal protection and radiation shielding for spacecraft components that are weak to the exposure of extreme conditions. In addition, CNT applications, such as nanotube propellant additives, could improve engine performance and reduce system mass fractions, ultimately enabling more efficient missions (Samareh et al., 2019). Furthermore, CNT-based composites offer opportunities for the improvement of spacecraft components. For instance, Lockheed Martin Space Systems has successfully evaluated CNTs and graphene-based nanocomposites for spacecraft structures, improving properties like modulus, strength, impact resistance, thermal conductivity, and electrical conductivity. Although CNTs do not yet match the electrical conductivity of metallic surface layers, they can satisfy EMI/ESD characteristics (Rawal et al., 2013). The Juno spacecraft is a successful example of CNT-based composite integration. CNT-based composite parts were used to fabricate tubular struts and an engine cover sandwich panel, providing micrometeoroid protection and support for the rocket engine motor. It also proves that CNT-based composites can provide multifunctional attributes, including effective electromagnetic shielding, thermal and electrical conductivity, and enhanced fracture toughness (Rawal et al., 2013).

2.2 Future of Carbon Nanotubes The use of CNTs in spacecraft is still in its early stages, but the potential benefits are significant. CNTs can make spacecraft lighter, stronger, and more versatile. This could lead to more affordable, efficient, and safer space exploration missions. Although CNTs are still relatively expensive, the cost is expected to decrease as the technology matures. Despite these challenges, the potential benefits of using CNTs

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in spacecraft are significant, and the research and development of CNT-based composites is an active area of research (Rawal et al., 2013).

(3) Self-Repairing Technology 3.1 Self-healing Materials and Their Advantages The use of self-healing materials (artificially or synthetically created materials that have the ability to repair damages automatically) in spacecraft has received significant attention, primarily because of their capability to autonomously repair damages from impacts with micrometeoroids and orbital debris (MMOD), accidental contact with sharp objects, structural fatigue, and material aging (Pernigoni et al., 2021). However, the caveats that are limited by the spacecraft’s limits go beyond just repairing the damages in the wiring. There is also the need to find the damages in the first place. The challenges in detecting damages and the complexity of manual inspections of spacecraft wiring usually play the role of an obstacle. Also, traditional repair methods are intrusive and can even cause additional damage. Unfortunately, wiring problems have led to numerous mission-related accidents (Williams et al., 2017). For instance, inspectors found 38 wiring defects on the Endeavor Space Shuttle and 26 on the Columbia (Lloyd).

3.2 Intrinsic and Extrinsic Mechanisms There are two main methods in the aspect of material healing and damage restoration: intrinsic and extrinsic mechanisms. Extrinsic mechanisms involve incorporating an individual healing agent, such as a liquid healing agent stored in dedicated containers like capsules or vascular networks. However, in this approach, usually, only single healing events are possible. The extrinsic mechanism is very appealing at certain times because it ensures thermal protection and autonomous repair. Conversely, intrinsic mechanisms offer an inherent healing ability within the material itself, relying on reversible chemical or physical bonds. Unlike extrinsic methods, intrinsic mechanisms do not require healing agents but often need external stimuli to trigger the self-healing response. One key advantage of intrinsic mechanisms is the potential for multiple damage restorations to occur at the exact location, providing a more sustainable and long-lasting approach to damage repair. In some cases, these intrinsic mechanisms can complement and be integrated with extrinsic solutions, offering an adaptable and effective strategy for improving material resilience and longevity in various applications, including impact protection and space exploration (Pernigoni et al., 2021). )LJXUH ,QWULQVLF DQG H[WULQVLF PHFKDQLVPV

Source:ResearchGate https://www.researchgate.net/publication/360852802_Recent_Advances_of_SelfHealing_Electronic_Materials_Applied_in_Organic_Field-Effect_Transistors (8/3/2023)

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3.3 Reasons Why Self-Healing Materials Should Be Used In Space Exploration The implementation of self-healing materials in spacecraft is crucial for several reasons. In the event of damage, astronauts would otherwise need to invest substantial time and effort into locating the source of the damage and finding appropriate repair solutions. Such damage can severely impact the functionality and effectiveness of the spacecraft, potentially compromising its overall utility. By integrating self-healing mechanisms, the damaged material can partially or fully restore its primary functionality with minimal external intervention, allowing for prompt rupture repair. Incorporating these innovative materials promises to enhance safety and prolong the operational life of spacecraft missions (Pernigoni et al., 2021). Self-healing capability is a valuable feature that can significantly reduce maintenance requirements and enhance the safety of critical systems (Williams et al., 2017).

3.4 Examples of Self-Healing Materials Flexible self-healing high polymers have been developed to emphasize how valuable self-healing capabilities are. These polymers possess flexible films with excellent thermal stability, electrical properties, flame resistance, and solvent resistance. The mechanism involves synthesizing a film using polyimide, a high-performance polymer group with an imide ring bond, which is then microencapsulated into the wire. Within the wire, there is a conductor covered by inner insulation. The inner insulation is further protected by a self-healing layer, which is covered by outer insulation. Microencapsulation of healants allows the self-healing process using innovative low-melting polyimide chemistry polymers (Dr.Martha K. Williams et al., 2017). A proposed space debris impact protection system by Aissa and her colleagues in 2021 involves blending microcapsules containing a monomer, carbon nanotubes (CNTs), and epoxy resin within layers of carbon fiber-reinforced polymer (CFRP). The healing agents used in this system were 5ethylidene-2-norbornene (5E2N) and dicyclopentadiene (DCPD) (Pernigoni et al., 2021). The use of self-healing composite ceramics in space is highly desirable. These ceramics offer both thermal protection and the capability of autonomous repair. The self-healing mechanism entails inserting SiC non-oxide ceramic into an Al2O3 oxide ceramic matrix, which prevents oxidation when damage occurs. If SiC is exposed to sufficiently high temperatures, an oxidation reaction occurs, filling and bonding the damaged surface, resulting in complete autonomous damage restoration (Pernigoni et al., 2021). Another self-healing ceramic composite incorporates 10-micrometer titanium (Ti) microparticles into an Al2O3 matrix to heal surface cracks. Through the oxidation of titanium, complete crack filling is necessary to prevent new ruptures upon reloading the damaged and healed region. A microcapsulebased space coating has the ability to repair in-orbit cracks through self-healing triggered by UV radiation (Pernigoni et al., 2021).

3.5 Future of Self-Healing Materials Future spacecraft will have to be long-lasting, extraordinarily reliable and autonomous, adaptable to a wide range of conditions, and require minimal maintenance. Self-healing materials offer the potential for significant advancements in spacecraft technology and mission success by enabling the damaged material to restore its functionality autonomously and swiftly, especially in extreme conditions such as in outer space, where manual repair is not available. To be able to replace traditional space technologies, these new solutions should ensure mass and cost savings, as well as increased performance and minimum risk. Despite still being at an early development stage, their promising characteristics pave the way for novel space applications that compete with traditional solutions (Pernigoni et al., 2021)

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,9 5HVHDUFK 0RGHOLQJ Figure 4 Problems in Outer Space

Figure 4 shows the steps a spacecraft goes through to explore outer space and the problems it faces throughout the mission. These steps include the construction of the spacecraft, launching, escaping the orbit, traveling through space, and maintaining the spacecraft’s condition. According to NASA, when the spacecraft is constructed, steel and aluminum are commonly used, which, when the spacecraft is fully built, can weigh about 2 million kilograms. Since the spacecraft is very heavy, it consumes a gargantuan amount of fuel, which, according to NASA, is about 5000 kg per second. Following the liftoff, the spacecraft has to escape the orbit going against the pull of gravity. The air resistance causes heat to be created on the spacecraft. After it escapes the atmosphere and travels further into space, it has to go through extreme temperatures that range from hundreds of degrees below zero to many

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hundred degrees above. It also experiences UV radiation that causes both strengthening and weakening of the compartments of the vehicle and destroys all the electronics in it. Besides this, the spacecraft is interrupted by MMOD impacts, in which the speed can range from 10 to 20 kilometers per second. This can cause significant damage to the sensitive spacecraft’s surfaces. Finally, the material aging and fraying of the spacecraft must be addressed. The fraying of the wiring in the spacecraft is very hard to detect because of its length, and this can threaten the astronauts’ safety since it might cause the spacecraft to malfunction. Figure 5 Nanotechnological Solutions to Problems in Outer Space

Figure 5 details how nanomaterials can help advance spacecraft development. The four traditional problems of spacecraft development are micrometeoroid and orbital debris impact, wiring repair, thermal endurance, and fuel efficiency. Carbon nanotubes help to address the issues of orbital debris and thermal endurance through their strength (being 50 times more potent than steel), lightweight nature, and radiation shielding. Self-repairing materials eliminate the need for manual wire repair, collision repair, and regular maintenance, therefore addressing the issues of fuel efficiency and debris impact by prolonging the spacecraft’s operational life.

ტ &RQFOXVLRQ The multidisciplinary field of nanotechnology has brought the science of “small but strong” closer to reality, affecting many fields, including space exploration. Nanomaterials show significant potential for improving space exploration in many ways. As mentioned above, the spacecraft encounters many problems throughout its operational life, including extreme thermal conditions, UV radiation, micrometeoroid and orbital debris impact, and wiring problems. As a solution for these problems, carbon nanotubes and self-healing materials could be used to overcome them, as they have superior properties compared to usual materials. Nevertheless, these materials have yet to overcome the technical barrier, and more research must be conducted to utilize them in practical applications. Although many

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challenges lie ahead, it is expected that nanotechnology can overcome these challenges and bring an entirely new perspective to science. Over the next few decades, it is widely anticipated that nanotechnology will continue to expand as it holds the potential to deliver the most significant technological breakthroughs of all time.

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References 1. A Samareh, J., & J Siochi, E. (2017, August 22). Systems analysis of carbon nanotubes: opportunities and challenges for space applications. IOPscience. https://iopscience.iop.org/article/10.1088/1361-6528/aa7c5a/meta 2. Galvez, R., Gaylor, S., Young, C., Patrick, N., Johnson, D., & Ruiz, J. (n.d.). The Space Shuttle and Its Operations The Space Shuttle Processing the Shuttle for Flight Flight Operations Extravehicular Activity Operations and Advancements Shuttle Builds the International Space Station. NASA. https://www.nasa.gov/centers/johnson/pdf/584722main_Wings-ch3a-pgs53-73.pdf 3. Lloyd, R. (1999, September 3). 64 cases of wiring problems found on shuttle fleet September 3, 1999. CNN. http://edition.cnn.com/TECH/space/9909/03/shuttle.repairs/ 4. Nanotechnology and Nonanimal Testing Methods. (n.d.). PETA Science Consortium International E.V. Retrieved August 3, 2023, from https://www.thepsci.eu/nano/ 5. Pernigoni, L., Lafont, U., & Grande, A. M. (2021). Self-healing materials for space applications: overview of present development and major limitations. CEAS Space Journal, 13(3), 341–352. https://doi.org/10.1007/s12567-021-00365-5 6. Rawal, S., Brantley, J., & Karabudak, N. (2013, June 1). Development of carbon nanotubebased composite for spacecraft components. IEEE Xplore. https://doi.org/10.1109/RAST.2013.6581186 7. Ren, G. (2023, July 21). carbon nanotube | Properties & Uses. Encyclopedia Britannica. https://www.britannica.com/science/carbon-nanotube 8. Rickman, S. L., Richards, W. L., Christiansen, E. L., Piazza, A., Pena, F., & Parker, A. R. (2017). Micrometeoroid/Orbital Debris (MMOD) Impact Detection and Location Using Fiber Optic Bragg Grating Sensing Technology. Procedia Engineering, 188, 233–240. https://doi.org/10.1016/j.proeng.2017.04.479 9. Sharma, R. (2012). Nanotechnology in Space Exploration: Needs and Applications. Journal of Pure Applied and Industrial Physics, 2(3A), 286–402. http://www.physicsjournal.org/dnload/RAVI-SHARMA/PHSV02I3AP0328.pdf 10. Space Shuttle Propulsion Trivia. (2005). In NASA. NASA Facts. https://www.nasa.gov/sites/default/files/113069main_shuttle_trivia.pdf 11. Venneri, S. L. (2001). Societal Implications of Nanoscience and Nanotechnology (pp. 177, 178, 179, 180, 181). National Aeronautics and Space Administration. http://www.cuttingthroughthematrix.net/articles/March2001NSF_Societal_Implications_of_N anoscience_and_Nanotechnology.pdf#page=177 12. Williams, M. K., Gibson, T. L., Jolley, S. T., & Caraccio-Meier, A. J. (2017, February 22). Self-Healing Technologies for Wiring and Surfaces in Aerospace and Deep Space Exploration Applications. NTRS. https://ntrs.nasa.gov/citations/20170001799 13. Zhen, Y. (2022, May). Recent Advances of Self-Healing Electronic Materials Applied in Organic Field-Effect Transistors. ResearchGate. https://www.researchgate.net/publication/360852802_Recent_Advances_of_SelfHealing_Electronic_Materials_Applied_in_Organic_Field-Effect_Transistors.

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Novel selenium antibacterial compounds against super bacteria Author 1

Full Name

: Kim, Ju Hyun

School Name

: Korean Minjok Leadership Academy

ABSTRACT: To make a new type of antibacterial substance, various reactions between various compounds containing selenium and sulfur were tried. As expected, selenium cysteine and selenourea were not inferior as ingredients of antibacterial substances. Among them Arg + Trp + selenocysteine + thiourea + HCHO conditions showed the highest antibacterial effect to S. aureus. This was partially purified by chromatography. Through gel filtration chromatography, it was confirmed that elution came out in void volume, and it was found that the molecular weight was not small, and it was confirmed that it was a slightly polar substance through adsorption chromatography.

398

I. Introduction Through previous experiments, we knew that substances with antibacterial effects contained a lot of sulfur. Recently, as selenium has been attracting attention in relation to antioxidant effects related to aging, I learned about selenocysteine and selenourea while looking for biomolecules with interest in selenium. Selenocysteine, also called the 21st amino acid, is a compound in which selenium is substituted for the oxygen of the amino acid serine, which is the same group 16 element, and the sulfur position of the amino acid cysteine. Moreover, selenourea was similarly a compound in which selenium was substituted for the oxygen of urea and the sulfur of thiourea. Moreover, since thiourea is a compound that has recently attracted attention as a component element of many antibacterial substances(H. Arslan, 2009), we tried to make a new type of antibacterial substance through a reaction between various compounds containing selenium and sulfur.

II. Methods 1. materials All the chemicals were purchased from sigma-aldrich. fig 1. chemicals for the experiment

It was expected to make an antibacterial substance containing selenium by combining the following 10 compounds. table 1. compounds used for making antibacrial agent compound including S or not including Se or not 1

Arginine

Tryptophan

Cysteine

Selenocysteine

Thiourea

Selenourea

ż ż ż ż

399

HCHO

Methionine

5-sulfosalicylic acid dihydrate

p-Toluenesulfonic acid

The structural formulas of the major compounds used in the experiment (cysteine, selenocysteine, arginine, tryptophan, thiourea, and selenourea) are as follows.

cysteine

selenocysteine

thiourea

selenourea

arginine

tryptophan

5-sulfosalicylic acid

p-toluene sulfonic acid

fig 2. The structural formulas of the major compounds used in the experiment VRSA was prepared with VRSA media for testing the antibacterial effect.

2. Antibacterial effect test of 3-component system Each compound was prepared at a concentration of 0.3M to try to create a new antibacterial substance with a combination of various selenium compounds and sulfur compounds, mainly arginine and tryptophan. The final concentration of each component was adjusted to be 0.1M. To summarize this: table 2. composition of 3-component system

Arg+ Trp

cys

selenocysteine

thiourea

selenourea

5sulfosalicyli c acid

p-toluene sulfonic acid

HCHO

Met

400

7KHVH FRPELQHG PL[WXUHV DUH PLFURZDYHG IRU VHFRQGV DW D WLPH XQWLO WKH\ UHDFK ႏ UHSHDWHGO\ :KHQ KHDWHG IRU DERXW VHFRQGV RYHU DERXW WLPHV WKH WHPSHUDWXUH H[FHHGHG ႏ ȝl of the obtained product was dropped on a paper disk having a diameter of 8 mm at a time, and drying was repeated to confirm susceptibility to Staphylococcus aureus after dropping a total of 300 ȝl. Staphylococcus aureus was prepared by liquid culture in LB broth in advance.

3. Antibacterial effect test of 4-component system It was expected to create a new antibacterial substance by combining arginine, tryptophan, selenium cysteine or selenourea with various other compounds. The concentration of each component was prepared in advance at a concentration of 0.4M, and the final concentration of each component was adjusted to be 0.1M. To summarize this: table 3. composition of 4-component system cys

selenocysteine

thiourea

selenourea

5sulfosalicyli c acid

p-toluene sulfonic acid

HCHO

Met

Arg + Trp + selenocysteine

Arg + Trp + selenourea

4. Antibacterial effect test of 5-component system It was expected to create a new antibacterial substance by combining arginine, tryptophan, selenium cysteine or cysteine, and thiourea or selenourea with various other compounds. The concentration of each component was prepared in advance at a concentration of 0.5M, and the final concentration of each component was adjusted to be 0.1M. To summarize this: table 4. composition of 5-component system cys Arg + Trp +selenocysteine +selenourea

selenothiourea cysteine

selenourea

5sulfosalic ylic acid

p-toluene sulfonic acid

HCHO

Met

401

Arg + Trp +selenocysteine +thiourea

Arg + Trp +cysteine +selenourea

Arg + Trp +cysteine +thiourea

As before, the mixtures thus combined were subjected to microwaves for 5 seconds at a time until the WHPSHUDWXUH UHDFKHG ႏ 7KH WHPSHUDWXUH H[FHHGHG ႏ ZKHQ LW ZDV H[SRVHG IRU DERXW VHFRQGV in total over about 5 times. 60 ȝl of the obtained product was dropped on a paper disk having a diameter of 8 mm at a time, and drying was repeated to confirm susceptibility to Staphylococcus aureus after dropping a total of 300 ȝl. 3. Crude separation using the gel filtration chromatography method of the substance with the most excellent antibacterial ability Among these, in the case of samples with a clear antibacterial effect, the position of the antibacterial substance was identified through a sensitivity test for each fraction. In addition, we tried to determine the partial properties using TLC. This was confirmed using 254nm and 365nm ultraviolet light from a UV lamp. 4. Partial separation using adsorption chromatography of substances with the most excellent antibacterial ability The fractions showing the highest antibacterial effect were collected through gel filtration chromatography and adsorption chromatography using silica gel was performed. As the eluent, a gradient of ethanol and water was applied. The final elution concentration was 40% ethanol and 60% water. And sampling from each fraction was tested for antibacterial properties.

fig 2. Adsorption chromatography is in progress.

402

III. Results Combinations with various antibacterial properties were identified as follows.

fig 3. antibacterial effects with products including S or Se Based on these antibacterial effects, the antibacterial effects are summarized as follows. մ means weak antibacterial effect, մմմ means strong antibacterial effect, and × means no antibacterial effect was observed. table 5. antibacterial effects with 3-component systems

Arg + Trp

cys

selenocysteine

thiourea

selenourea

5sulfosalicyl ic acid

p-toluene sulfonic acid

HCHO

Met

table 6. antibacterial effects with 4-component systems cys

selenocysteine

thiourea

selenourea

5sulfosalic ylic acid

p-toluene sulfonic acid

HCHO

Met

Arg + Trp + selenocysteine

մմ

Arg + Trp + selenourea

մմ

403

table 7. antibacterial effects with 5-component systems cys

selenothiourea cysteine

selenourea

5sulfosalic ylic acid

p-toluene sulfonic acid

HCHO

Met

Arg + Trp +selenocysteine +selenourea

մմ

Arg + Trp +selenocysteine +thiourea

մմ

մմմ

Arg + Trp +cysteine +selenourea

մմ

Arg + Trp +cysteine +thiourea

մմ

Arg + Trp + selenocysteine + thiourea + HCHO conditions showed the highest antibacterial effect. This was partially purified by chromatography. Through gel filtration chromatography, it was confirmed that elution came out in void volume, and it was found that the molecular weight was not small, and it was confirmed that it was a slightly polar substance through adsorption chromatography.

254 nm exposure of adsorption chromatography eluates

365 nm exposure of adsorption chromatography eluates

fig 4. TLC with adsorption chromatography fractions

404

The following are the assay results of the column fractions.

fig 5. antibacterial effects with adsorption chromatography fractions

IV. Conclusion To make a new type of antibacterial substance, various reactions between various compounds containing selenium and sulfur were tried. As expected, selenium cysteine and selenourea were not inferior as ingredients of antibacterial substances. Among them Arg + Trp + selenocysteine + thiourea + HCHO conditions showed the highest antibacterial effect to S. aureus. This was partially purified by chromatography. Through gel filtration chromatography, it was confirmed that elution came out in void volume, and it was found that the molecular weight was not small, and it was confirmed that it was a slightly polar substance through adsorption chromatography. In addition, 5-sulfosalicylic acid and ptoluene sulfonic acid, which contain sulfur, seem to contribute to the synthesis of antibacterial substances.

V. References 1. Hakan Arslan, et al., Antimicrobial Activity of Some Thiourea Derivatives and Their Nickel and Copper Complexes, Molecules. 2009 Jan; 14(1): 519–527 2. Shraddha Pandey, et al., Biogenic synthesis and characterization of selenium nanoparticles and their applications with special reference to antibacterial, antioxidant, anticancer and photocatalytic activity, Bioprocess and Biosystems Engineering 2021, 44, 2679–269

405

Development of Eco-friendly Fishing Nets with Ramie and Linen Fiber Coated with Natural Beeswax Author 1

Author 2

Author 3

Kim, Yesel Priscilla

School Name

Tabor Academy

Full Name

Full Name (Last Name, First Name)

(Last Name, First Name)

School Name

Full Name

(Last Name, First Name)

School Name

ABSTRACT: The detrimental impact of abandoned fishing nets on the ocean environment is a growing concern. These discarded fishing gears, often referred to as ghost nets, are predominantly composed of nonbiodegradable plastic, primarily Nylon. As a result, they continue to trap marine life and cause widespread harm even after being abandoned. This study proposes a solution by investigating the use of natural fibers, specifically ramie, and linen, as alternatives to plastic fishing nets. These fibers possess qualities of durability, biodegradability, and resistance to rotting. To enhance their protective capabilities, the fibers are coated with a mixture of natural beeswax and canola oil, which provides a water-resistant layer. The resultant coated fabrics are compared with their uncoated counterparts to assess the impact of the coatings on water resistance, absorbency, and smoothness. Microscopic imaging reveals the efficacy of the coatings, highlighting their potential to minimize drag underwater and protect against erosion. Tensile strength tests before and after soaking fibers in salt water indicate that coated fibers, particularly those with a 1:1 ratio of beeswax to canola oil, exhibit enhanced durability and resistance to saltwater exposure. Human skin cell viability tests suggest that the raw materials were the least toxic, and for the coatings, the 1:3 ratio was the least toxic. Overall, this study concludes that the proposed method offers a promising solution to mitigate the harmful effects of abandoned plastic fishing nets.

KEYWORDS: Fishing nets, Eco-friendly material, Linen, Ramie, Beeswax

406

Introduction Many fishing gear get lost or abandoned, polluting the ocean. Every year, more than 640,000 tonnes of fishing gear are discarded and lost in the sea. Most fishing nets are made up of Nylon: a type of plastic that does not decompose. This leads to lost fishing gear, also known as ghost nets, constantly catching fish for many years. With only fishing nets, hundreds of millions of marine organisms are killed or injured every year. 1 Though not used by fishermen anymore, ghost nets still function by themselves: catching fish, sea turtles, dolphins, birds, sharks, seals, and more. Once tangled, the nets keep animals from moving freely, often drowning mammals and birds from rising to the surface for air. Ghost nets not only prove threatening to marine animals but to the environment as well. 2 Coral reefs are damaged due to the fishing nets hooking onto the corals, and getting pulled by the current, breaking off pieces of coral. 3 Lastly, not only are fishing nets detrimental to marine life, but they also pose a risk if they get stuck in any water transportation that requires an engine with propellers. The ramie plant (Boehmeria Nivea), also called China grass, is native to eastern Asia and has been used for over 6000 years. As a fiber, ramie is stronger than flax, cotton, and wool. 4 It increases in strength when wet and does not shrink or get misshapen. As a plant, ramie can be harvested every 60 days. It grows up to 3 meters (8 feet) high and does not need pesticides, herbicides, and fertilizers to grow. 5 Linen is one of the oldest fabrics. It is also one of the most sustainable fabrics because it is entirely biodegradable, does not produce any waste, and retains carbon. Agriculturally, linen is convenient because only rainwater is required to survive. 6 Just like ramie, linen does not need pesticides or a lot of fertilizer to grow. 7 For coating the fibers, beeswax was used. This natural wax does not expire, is biodegradable, and provides some protection against salt water for the fibers. Since beeswax is easily removed and heavily used, frequent maintenance is necessary for an efficient coating on the fibers. Beeswax can easily be found in non-toxic and food-safe forms, which is crucial for the health of marine life. 8 Detrimental to marine organisms and marine environments, ghost nets are among the most harmful plastics. Plastic takes a few hundred years to decompose, so ramie –a type of fiber– that is durable, biodegradable, and resistant to rotting would solve many or most of the problems caused by plastic fishing nets. In addition, by applying a coating of beeswax or a mixture of beeswax and canola oil, the fiber would have a more protective and slightly water-resistant layer. Comparing ramie fiber with linen fiber where ramie would most likely have a more durable constitution while linen would be less toxic.

Methods Preparing beeswax solution with canola oil Beeswax and canola oil were purchased from the market in Korea. About 30 g of beeswax was microwaved for 3 minutes to melt into liquid. Then, canola oil was added depending on the desired ratios: 1:1, 1:2, 1:3, 2:1, 3:1, and one with only beeswax. Coating ramie and linen with different ratios of beeswax and canola oil Strings of ramie and linen fiber were cut in about 30 cm lengths. Then, by holding onto one side of the string, three of each fiber was dunked into the solution for about 30 seconds. Then, they were taped above the lab bench to dry. This was repeated for each coating ratio. Once the coatings had dried, three of each string were placed into their designated Petri dishes.

407

Microscope imaging Each coated sample of linen and ramie was placed one by one under the microscope. Two images were taken for each sample to analyze the presence of sticking-out fibers and the smooth surface, facilitating a thorough assessment of the coatings' performance. Cell cytotoxicity test Detroit551, human skin cells, were cultured using the RPMI1640 cell culture media. After the cells were detached from the cell culture dish with the Trypsin-EDTA solution, the cells were collected inside the tube. Then, the cells were distributed equally into the six-well culture plates. The coated ramie and linen were cut into 5 cm and submerged into the cell culture plate. After one week of incubation, the cells were detached and stained with Propodium Iodide and Acridine Orange. Then the cell viability was measured using the automated cell counter device LUNA-FL. Saltwater soaking test NaCl (35 g) was prepared with distilled water (1 L) to make 0.6 M NaCl solution, the same ocean salt concentration. The water 50 mL was added to each tube, and each coated ramie and linen were soaked for one week. Tensile strength analysis zwickiLine machine was used to test the tensile strength of the coated linen and ramie with the normal fishing net. The fiber was installed into the chain with the appropriate grips for textile testing on the machine’s load frame. The crosshead speed (10mm/min) was used for the test. The tensile strength was recorded in units of force per unit cross-sectional area (MPa).

Results and Discussion

Figure 1. A three-step process for coating ramie and linen using honey bee wax and canola oil.

408

The purpose of these steps is to create different ratios of coating on either ramie or linen. For step one, beeswax was measured to around 30 g and melted with different ratios of canola oil in the microwave for 2 minutes. If the ratios were reversed and there were more beeswax than canola oil, then the solution would be microwaved for a longer time. In step two, once three pieces of ramie and those of linen were cut, they were dipped into the solution vertically to coat evenly. This was repeated for all the strings of fiber. Finally, they were taped individually and labeled onto the benchtop to dry. Under the fiber, an aluminum foil was set up to catch any excess solution. Through this method, we successfully created the beeswax-coated ramie and linen fabrics with different beeswax and oil composition.

Figure 2. Comparison of naked and coated ramie and linen fabrics. Ramie and linen fibers were covered with varying ratios of beeswax and canola oil and allowed to dry. Zoomed-in images were taken of each fiber ratio to investigate the impact of the coatings. The coatings made the fibers somewhat more water-resistant, less absorbent, and smoother. However, the coatings also had two negative consequences: they made the fibers less flexible, and when canola oil was utilized, there were noticeable traces of excess oil. Despite these drawbacks, the coatings were mostly beneficial because they were evenly applied and provided protection for the fibers.

409

Type

Ramie

Linen

Raw

Only Bees wax

1:1 Ratio (Wax : Oil)

410

1:2 Ratio (Wax : Oil)

1:3 Ratio (Wax : Oil)

2:1 Ratio (Wax : Oil)

411

3:1 Ratio (Wax : Oil)

Figure 3. The microscope image of the surface of the raw and coated ramie and linen fiber with different beeswax oil ratios. Using microscopic imaging, we observed the efficacy of each coating: from smoothness to the amount of uniform coating. Each ratio for both ramie and linen fibers was placed under a microscope to examine how well the coatings worked. By comparing the surfaces of all ratios in comparison to the two raw fibers, we can conclude that the coatings provide a smooth layer that would potentially help with any drag when underwater which causes quicker wear. Through these images, to a certain degree, these coatings provide a smooth surface that would give protection and smoother movements against drag and erosion underwater.

412

Before Soaking (Mpa)

After Soaking (Mpa)

Raw ramie

30.2

31.4

21.3

20.1

Raw linen

54.1

53.6

51.1

53.2

Ramie wax only

32.5

33.4

30.6

31.5

Linen wax only

55.1

56.1

53.7

52.2

1 to 1

36.8

36.1

36.7

35.1

1 to 2

31.6

31.9

33.3

30.5

2 to 1

34.2

33.6

31.2

33.5

3 to 1

33.1

32.5

30.3

33.4

1 to 3

35.5

34.5

31.6

32.6

1 to 1

63.1

63.8

62.1

62.9

1 to 2

56.3

53.3

53.1

52.1

2 to 1

57.8

52.4

55.6

55.9

3 to 1

54.6

52.1

52.2

50.2

1 to 3

58.1

54.1

53.1

51.6

Beeswax: oil (ramie)

Beeswax: oil (linen)

Table 1. Results of tensile strength before and after soaking in salt water. The tensile strength of every fiber was measured based on the unit megapascals. To observe the resistance of each fiber to salt water, the same concentration as sea water, the fibers were tested both before and after soaking in the salt water. Through these results, linen fiber was generally more durable than the ramie fiber (Table 1). As for the coated fibers, the 1:1 ratio fibers for both ramie and linen were the most durable compared to other ratio fibers, as indicated in Table 1. In addition, the 1:1 and 1:2 ratio coatings for both the fibers showed the most resistance to the salt water. Overall, the 1:1 ratio coating on linen was the most durable and showed the most resistance to the salt water.

413

Live # Dead # Total # Viability (%) Control

974

127

1101

88.5

Raw Ramie

109

79.8

Raw Linen

354

398

88.9

Ramie wax only

16.7

Linen wax only

118

52.5

1:1

141

51.1

1:3

147

52.4

3:1

43.4

1:1

131

36.6

1:3

125

Ramie (Wax: Oil)

Linen (Wax: Oil)

3:1 57 89 146 39 Table 2. Effect of raw ramie and linen and coated ramie and linen on human skin cell viability. Using human skin cells, we measured the viability percentage for each fiber. Each of the fibers was tested in order to find the least toxic material of both the fiber and coating ratio. The raw linen material was the least toxic, with a viability percentage of 88.9%, and as for the coated fibers, the 1:3 ratio coatings for both fibers were the least toxic (Table 2). Overall, linen fiber showed to be less toxic than ramie fiber, especially when without any coating and with a 1:3 ratio coating.

Conclusion Ghost nets are big threats to marine ecosystems. They are still of use even after being abandoned at sea and take hundreds of years to decompose. Using biodegradable material, ramie, and linen, we used coatings to test their cytotoxicity and durability. When comparing the uncoated fibers to the coated fibers, the coated fibers had a much smoother surface that would potentially minimize any drag and erosion. The tensile strength results suggest that linen fiber is generally more durable than ramie fiber. The cytotoxicity test shows that the raw fibers were the least toxic and that for the coated fibers, the 1:3 ratio of linen was the least toxic. With these results, this study proposes a highly sustainable and beneficial alternative to plastic fishing nets due to their ability to biodegrade, posing fewer risks to marine ecosystems.

Acknowledgments I would like to thank my parents and my mentor for giving me this very unique and forever memorable experience. This research has been an enjoyable and inspiring journey, thanks to their support.

414

References (1) Richardson, K.; Hardesty, B. D.; Vince, J.; Wilcox, C. Global Estimates of Fishing Gear Lost to the Ocean Each Year. Sci. Adv. 2022, 8 (41), eabq0135. DOI: 10.1126/sciadv.abq0135. (2) Hardesty, B. D.; Roman, L.; Duke, N. C.; Mackenzie, J. R.; Wilcox, C. Abandoned, Lost and Discarded Fishing Gear “ghost Nets” Are Increasing through Time in Northern Australia. Mar. Pollut. Bull. 2021, 173 (Pt A), 112959. DOI: 10.1016/j.marpolbul.2021.112959. (3) Beneli, T. M.; Pereira, P. H. C.; Nunes, J. A. C. C.; Barros, F. Ghost Fishing Impacts on Hydrocorals and Associated Reef Fish Assemblages. Mar. Environ. Res. 2020, 161, 105129. DOI: 10.1016/j.marenvres.2020.105129. (4) He, L.; Xia, F.; Wang, Y.; Yuan, J.; Chen, D.; Zheng, J. Mechanical and Dynamic Mechanical Properties of the Amino Silicone Oil Emulsion Modified Ramie Fiber Reinforced Composites. Polymers (Basel) 2021, 13 (23). DOI: 10.3390/polym13234083. (5) Handika, S. O.; Lubis, M. A. R.; Sari, R. K.; Laksana, R. P. B.; Antov, P.; Savov, V.; Gajtanska, M.; Iswanto, A. H. Enhancing Thermal and Mechanical Properties of Ramie Fiber via Impregnation by Lignin-Based Polyurethane Resin. Materials (Basel) 2021, 14 (22). DOI: 10.3390/ma14226850. (6) *ĊEDURZVNL 7 -ĊĞNRZLDN , :LDWUDN % ,QYHVWLJDWLRQ RI WKH 3URSHUWLHV RI /LQHQ )LEHUV and Dressings. Int. J. Mol. Sci. 2022, 23 (18). DOI: 10.3390/ijms231810480. (7) Dunn, D. Linen: The New Frontier in Infection Control and Prevention. AORN J. 2022, 115 (4), 310–324. DOI: 10.1002/aorn.13643. (8) Wilmart, O.; Legrève, A.; Scippo, M.-L.; Reybroeck, W.; Urbain, B.; de Graaf, D. C.; Steurbaut, W.; Delahaut, P.; Gustin, P.; Nguyen, B. K.; Saegerman, C. Residues in Beeswax: A Health Risk for the Consumer of Honey and Beeswax? J. Agric. Food Chem. 2016, 64 (44), 8425–8434. DOI: 10.1021/acs.jafc.6b02813.

415

The Effect of Thigmomorphogenesis on the Growth Rate of Basils and Blue Sages Author 1

Full Name

Lee, Haryeong (Heidi)

HPrep Academy

(Last Name, First Name)

School Name

ABSTRACT: When harvesting plants or crops, natural phenomena such as wind and rain are some of the many factors that challenge the plant’s survival. These factors further impact the economy by damaging many crops on farms. To prevent this from happening, farmers can use thigmomorphogenesis. Thigmomophogenesis is when a plant’s growth is impacted by natural factors such as touching. When plants are given thigmomorphogenesis, they become resistant to natural phenomena, including winds or the movement of other animals. It is assumed that this method will increase the number of plants and be able to help farmers. This paper aims to figure out whether thigmomorphogenesis impacts the growth rate of basil and blue sage.

KEYWORDS: Basil, Blue sage, Growth, Plant, Thigmomorphogenesis

416

პ Introduction Many people, especially farmers, are concerned about the quantity and quality of their crops. One solution for farmers is to use thigmomorphogenesis by mechanically stimulating the plants. Thigmomorphogenesis is a touch-induced alteration in plant growth [1]. This can include actions such as wind, the rubbing of one plant against another, and the movement of animals against plants [3], [4]. This process helps plants to overcome environmental stressors and grow effectively. When a plant goes through thigmomorphogenesis, its stem becomes thicker and has deeper roots, preparing it to respond to environmental phenomena [5]. Also, it allows the plant to become disease resistant from subsequent pathogen encounters, decrease elongation, and increase in senescence, which is the aging of whole organisms [4], [7]. According to E. Wassim. et al. (2008), plants evolved senses, giving out and receiving stimuli such as touching. When the touch induces genes, they hold various processes, such as defense and cell wall modifications which allow elucidation of the mechanisms [6]. However, the process can also cause rapid gene expression alterations and impacts the plants’ appearance and flowering [8]. This change in the growth pattern of the plant results in a decrease in its reproductive potential by reducing the flower number and delaying the flowering time [9]. Even though there can be some drawbacks of thigmomorphogenesis, farmers can grow most of their crops successfully without suffering from various natural phenomena. This topic has been researched since the 1970s and this trend led this experiment to take place to figure out how thigmomorphogenesis affects the growth rate of basil and blue sages. The reasons for choosing these plants are that they can be used for medicinal purposes and that basil can be used for food. For this experiment, thigmomorphogenesis is performed by the experimental device called Arduino. Arduino is an electronics platform that codes the Arduino boards to read inputs, activate a motor, turn on an LED, or publish something online. To make this work, a wooden stick is attached to the motor to contact the plants while spinning. The plant's height and leaf size were measured three times a week (Monday, Wednesday, and Thursday). The hypothesis for this experiment is that plants that go through thigmomorphogenesis will grow better and be more stable than those that do not experience thigmomorphogenesis. This research paper aims to discuss the effects of thigmomorphogenesis on the growth rate of basil and blue sage. There are some reasons for this experiment's use of basils among various plants. Basils have various beneficial characteristics: they are fast-growing plants that can be harvested within six weeks. In addition, they are considered as an annual plant in temperate climates and reach heights of thirty to hundred-fifty centimeters. They grow best in well-drained soil with direct exposure to the sun. Basils can be grown indoors in a pot and even in a basement with fluorescent lights [10]. Additionally, basils are known as herbal medicine and provide people with health benefits in their diet. Specifically, they offer people some macronutrients such as calcium, vitamin K, and various antioxidants, which are essential for eliminating free radicals from the body [11]. Seventeen Tulsi trials conducted between 1964 and 2016 observed that basil causes a decrease in fasting blood glucose, improves lipid profiles, and lowers blood pressure in obese people. They have been used for many different diseases, such as arthritis, anorexia, influenza, asthma, and diarrhea [12]. Basils are also essential for dental products, cosmetics, and flavoring agents [13]. As basils provide people with so many benefits, they have high value for farmers [14]. Due to these characteristics of basil, it was considered to be a suitable plant for this experiment. Another plant that is used for this experiment is the blue sage, which has several medicinal properties that make it valuable for agricultural cultivation. Its name ‘sage’ means it has traditionally been used for medical purposes. The scientific name is ‘salvia azurea,’ which refers to the healer. Just like basil, it grows up to a hundred-fifty centimeters [15]. It usually blooms between July to September in various open habitats, including prairies and roadsides. There are approximately nine-hundred species of blue sage [16]. The blue sage is used for cleansing and disinfection purposes. It has antimicrobial prospects and helps people remove about ninety-four percent of airborne bacteria [17]. Moreover, some research

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has shown that sage can improve the memorization skills of young and healthy adults. Also, since sage has anti-inflammatory and antimicrobial effects, it is commonly used in dentistry [18]. Since blue sages are an effective tool when used for medical purposes, it is believed that increasing their population through thigmomorphogenesis would be beneficial. Therefore, in this research, we would like to use Arduino to artificially touch basil and blue sage and compare the growth rate. This research would like to analyze the difference by conducting a statistical analysis based on the results measured by Arduino.

II 0HWKRGV DQG 0DWHULDOV 2.1 Plants There are some steps to get through this experiment and obtain the result of how thigmomorphogenesis affects the growth rate of basils and blue sages. First, there should be plants to start the experiment; there are two kinds of plants: basil and blue sage. Four plants were used for the experiment: two basils and two blue sages.

2.2 Arduino When the plant is ready, there should be a material that can give thigmomorphogenesis to the plant. In this experiment, an Arduino was used to contact the plants. The process to operate the Arduino is as follows. First, prepare an Arduino set containing a motor, a main board, jumper wires, and cables. Secondly, code the main board using the Arduino IDE so that the motor would spin. It was coded that the motor rotates at an angle of 90 degrees for it to move for a second, pause for 5 seconds, and move for a second again. On the motor itself, it has a wire that has three holes. Three jumper wires connected the motor to the main board to make it rotate. To make the motor function, plug the yellow wire into 9, the red wire into 5V, and the brown wire into the ground (GND), as shown on the left. Connect the main board to the computer and run the code using the cable. After checking the motor moving, pause it for a second and attach a wooden stick to it so it spins together. Then, use the double-sided tape to place the Arduino next to the plant. Now, turn on the motor again and check if it touches only two plants. If not, place the motor again or add another wooden stick to make it reach further. When all the processes are followed, coding and placing the Arduino next to the plant is finished.

2.3 Measurements The last method is to record the plant's height and leaf size. The height of the plant was measured from the base of the stem to the top of the tallest leaf. The length of the largest leaf measured the leaf size. The growth rate of each plant was recorded by taking a photo three times a week. From the first day to the third day, the plant was not given thigmomorphogenesis, so the plant's height and leaf size could not be recorded. However, from day 4 to day 32, all plants’ growth rate is recorded, as shown in the table below.

On the table in Appendix, untouched basil (UB) and blue sage (UBS) are the ones not given thigmomorphogenesis. Contrastingly, touched basil (TB) and blue sage (TBS) are the ones given stress. As shown in the table, the day 10 leaf size of the untouched basil decreased dramatically. It is not that the size of the leaf decreased, but the leaf that was being measured was ripped off. Thus, another leaf had to be measured. Besides this leaf, other leaves were growing well even though they sometimes shrunk in size by 0.1 or 0.2 centimeters or remained the same.

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The variables for this experiment were temperature, humidity, the amount of sunlight, thigmomorphogenesis, and the amount of water. The controlled variables were temperature, humidity, the amount of sunlight, and the amount of water. The frequency for touching the plants was the same for both touched plants, but untouched plants were not touched at all except when there was wind, or there was contact between the plants. All of these variables are needed for the plant to survive in nature and even in smart farms.

,,, 9DULDEOHV 3.1 Temperature The temperature is a necessary variable for the plant to survive. One good example is that it supports the plant’s photosynthetic process. When the photochemical process becomes limiting, it affects a chemical process at high light intensities and a diffusion process at low light intensities. Additionally, cell growth, including cell elongation, has a high Q10, which shows that this is a chemically but not physically regulated circumstance [19]. Also, temperature allows plants to predict seasonal changes and therefore prevent detrimental effects of environmental change. It acts as a stimulus to regulate developmental alterations' timing and improve resistance to future temperature extremes. Plants can maintain their homeostasis, allowing buffering against common environmental disruptions which would disturb cellular functioning [20].

3.2 Humidity Humidity levels regulate the rate of transpirational water loss and stomatal aperture of plants, which controls the flow of gas in and out of the plant. Also, it controls photosynthetic rates, tissue temperatures, plant water potentials, and concentrations of Ca in certain tissues. In addition, humidity restricts water taken in by tissues through condensation and direct vapor uptake [21]. When plants transpire, the leaves become saturated with water vapor by the surrounding humidity. When the relative humidity levels are high, or there is a lack of air circulation, it is challenging for a plant to go through evaporation or extract nutrients from the soil. This causes the plant to rot if it happens for a long time. On the other hand, when there are low relative humidity levels, transpiration rates in a plant increase, requiring a grower to fertilize it [22].

3.3 Light Light is known to be a main part of photosynthesis since plants use carbon dioxide, water, and sunlight to produce glucose and oxygen. Furthermore, light signals give spatial, temporal, and seasonal information to plants. Plants calculate the quantity, quality, direction, and photoperiod of light and utilize this information to control various developmental processes during their lifecycle. In addition, light ensures the coordination of growth with light or dark cycles and reforms plant fitness by providing entrainment signals to the circadian rhythm [20].

3.4 Water Water is necessary for germinating seeds, and as the plant starts to grow, water acts as a carrier of mineral nutrients and food. Plant cells grow by increasing in volume; water is one of the main sources of this process. All processes of metabolism need a humid and wet place to function. Moreover, water

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serves an important role in various chemical reactions in plants. Thanks to its unique physical and chemical properties, water is the only thing that can play this role. Since H is necessary for temperature regulation as it does not heat or cool too quickly, it allows thermal properties in plants. Furthermore, water carries nutrients and solutes needed for the growth of plants, enabling solvent properties. It also permits biochemical reactions in plants by participating directly or making them occur in water [23].

ს 5HVXOWV DQG /LPLWDWLRQ When the leaf size of the touched and untouched basil is compared, the touched basil has about 1 cm larger leaf. However, there is little difference in size. This concludes that applying thigmomorphogenesis to basils slightly enlarges the leaf size. For the blue sage, there is a huge difference in the leaf size of the touched and untouched ones. The touched blue sage is about 2.5cm larger than the untouched blue sage. This shows that when the blue sage receives thigmomorphogenesis, it will have a larger leaf size than those that do not get touched. When comparing the height of the touched and untouched basil, the untouched basil is much taller than the touched one. This is likely because mold started to grow on day 22 at the lower stem of the touched basil, which negatively affected its growth rate. It seemed like the plant was not given enough nutrients or food due to the rotten stem. Most of its leaves were becoming brown, and on the last day of the experiment, the stem of it was almost cut in half. Since day 20, the touched basil’s height has reduced while the untouched basil grew rapidly. If the touched basil did not have a mold on its stem, the result would probably be different than it is now. While there was a massive difference in the leaf size of the plant, there is not much difference in the height of the touched and untouched blue sage. The increase in height is very consistent in both blue sages. The gap between the two plots at the beginning and the end are almost the same, showing that thigmomorphogenesis did not have much effect on the height of the blue sage.

Variable

Obs Mean

Std. Dev. Min Max

Day

3.815757 1

Touched1 Not0 26

.509902

Height

9.296154 5.136028 2

21.1

Leaf size

4.376923 1.207744 2.1

6.7

Temperature

27.76923 1.751975 25

31.7

Humidity

.5330769 .0501812 .43

.61

7DEOH 1 This table was created by the software called Stata. The table above is the summary of the growth of the basil, which indicates the variables and the minimum, maximum, and mean of the variables. The variables include day, touched or untouched, height, leaf size, temperature, and humidity. The minimum height for the basil is 2 cm, the maximum height is 21.1cm, and the mean is about 9cm. The smallest leaf size is 2.1cm, the biggest leaf is 6.7cm, and the average size is around 4 cm.

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Source

Model

32.9086436 5

Residual 3.5575102 Total

MS 6.58172873

20 .17787551

36.4661538 25 1.45864615 Number of obs = 26 F (5, 20) = 37.00 Prob > F = 0.0000 R-squared = 0.9024 Adj R-squared = 0.8781 Root MSE = .42175

Leaf size of untouched Coef.

Std. Err.

P>|t|

Day

.2682215

.0813599 3.30

0.004 .0985077

.4379352

Touched1 Not0

1.74502

.207938

0.000 1.311269

2.178772

Height

-.0485006 .061805

-0.78 0.442 -.1774236

.0804225

Temperature

.0472137

0.421 -.0725775

.1670048

Humidity

-.3560389 2.231053 -0.16 0.875 -5.009933

4.297856

_cons

.9564404

6.037747

8.39

.0574272 0.82

2.435952 0.39

95% Conf. Interval

0.699 -4.124867

7DEOH 2 Table 3 demonstrates the regression of the basil. As shown in the right top, the R-squared value of basil height is 0.9024, and when the value is closer to 1, it means that the model predicted the outcome of the dependent variable well. The table below the R-squared value shows the variables and how much they are related to the leaf size of the basil. The results exhibit that touching had the most impact while the temperature had the least.

Variable

Obs Mean

Std. Dev. Min Max

Day

3.815757 1

Touched1 Not0 26

.509902

Height

7.169231 2.540515 3.5

13.8

Leaf size

4.765385 1.09907

2.7

6.4

Temperature

27.92308 1.792943 25

31.7

Humidity

.5315385 .0515125 .43

.61

7DEOH 3

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This table shows the variables and results of the blue sage. The numbers for the day, touched or untouched, temperature, and humidity are the same as the basil’s table, but the height and the leaf size are different. The maximum height for the blue sage is 13.8 cm, the minimum height is 3.5 cm, and the mean height is about 7 cm. The maximum leaf size is 6.4 cm, the minimum is 2.7 cm, and the average is around 4 cm.

Source

Model

29.1586141 5

MS 5.83172281

Residual 1.04023209 20 .052011605 Total

30.1988462 25 1.20795385 Number of obs = 26 F (5, 20) = 112.12 Prob > F = 0.0000 R-squared = 0.9656 Adj R-squared = 0.9569 Root MSE = .22806

Leaf size

Coef.

Std. Err.

P>|t|

95% Conf.

Interval

Day

.2841469

.0257307

11.04

0.000

.2304735

.3378203

Touched1not0

.6757282

.101337

6.67

0.000

.4643429

.8871134

Height

-.033047

.039681

-0.83

0.415

-.1158202

.0497261

Temperature

.0241867

.0300228

0.81

0.430

-.0384397

.0868132

Humidity

.6808604

1.092476

0.62

0.540

-1.598006

2.959726

_cons

1.638142

1.28147

1.28

0.216

-1.034957

4.311241

7DEOH 4 This table is the regression for the blue sage. The R-squared value of the blue sage is higher than the value of the basil’s, which indicates that there is a stronger positive correlation between the treatment and growth rate of the blue sage, than that of the treatment and growth rate of the basil. As well as the basil, the blue sage’s leaf size was mostly affected by thigmomorphogenesis and was least affected by humidity and temperature. The result of this experiment is that thigmomorphogenesis has a larger impact on the leaf size of plants, compared to the height of plants, for blue sage and basil. Plants that were touched had larger leaf sizes than those that were untouched. This leads to the conclusion that thigmomorphogenesis would allow farmers who raise plants whose leaves are used effectively to be able to produce more plants only using small amounts of land. For example, the basil’s leaf is used both for food and medicinal purposes. When the basil is affected by thigmomorphogenesis, it will be able to create larger leaves and allow people to use them more frequently for the aforementioned purposes.

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One unexpected variable for the experiment was that there was a mold on the touched basil’s stem and it made the stem rot. It is clear that thigmomorphogenesis had an impact on this basil, likely, the mold would also have affected how the basil grew and the result of the experiment. Also, some limitation of this experiment was that there were not many variables. Thigmomorphogenesis was the only experimental variable and all the others were the controlled variable. This made the experiment have less R-square value compared to other people. If there were more experimental variables, the experiment would have been more reasonable and accurate. Furthermore, if the leaf of the untouched basil was not ripped off, it would have shown a more accurate result for the experiment.

ტ &RQFOXVLRQ DQG 'LVFXVVLRQ Overall, this research paper discussed the effects of thigmomorphogenesis on the growth rate of basils and blue sages. The Arduino was used to generate mechanical stimuli to plants. To characterize thigmomorphogenesis, I measured the height and leaf size of the plants three times a week. This experiment was held for about a month (from June 29th to July 27th) and the results were recorded. The result of this experiment on blue sage shows that the touched plant’s leaf size is significantly larger than untouched plants. However, the height of the plants did not vary. This suggests that thigmomorphogenesis can be used effectively for plants in which their leaf serves a necessary purpose and is consumed widely by humans. During experiments, I have observed damage on the stem of touched basils. Then, mold starts to grow around the damaged stem. It affected the result since the basil was not able to grow as it was supposed to grow. To get better statistical results, I need to do more experiments with basil and blue sage. In the future, thigmomorphogenesis can be used for plants whose leaves are used for beneficial purposes. One example is the basil as its leaves serve as food and are also used for medical purposes. As thigmomorphogenesis becomes more popular among people, farmers would be able to produce more plants that are resistant to environmental phenomena with better quality.

423

Appendix Basil and Blue Sage

Day #

Date

Height

/HDI Size

Day 1

June 26th (Mon)

X measured

Day 3

June 28th (Wed)

X measured

Day 4

June 29th (Thu)

UB: 3.5cm TB: 4.2cm UBS: 2cm TBS: 3.9cm

UB: 3cm TB: 2.9cm UBS: 2.1cm TBS: 3.2cm

Day 8

July 3rd (Mon)

UB: 3.5cm TB: 4.2cm UBS: 2cm TBS: 3.9cm

UB: 5.1cm TB: 4cm UBS: 3.1cm TBS: 4cm

Day 10

July 5th (Wed)

UB: 3.5cm TB: 4.2cm UBS: 2cm TBS: 3.9cm

UB: 3.5cm **The leaf that was being measured was ripped RII ĺ PHDVXUH DQRWKHU OHDI IURP QRZ RQ TB: 4cm UBS: 3.4cm TBS: 4.2cm

Day 11

July 6th (Thu)

UB: 3.5cm TB: 4.2cm UBS: 2cm TBS: 3.9cm

UB: 3.7cm TB: 4.1cm UBS: 3.5cm TBS: 4cm

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Day 15

July 10th (Mon)

UB: 3.5cm TB: 4.2cm UBS: 2cm TBS: 3.9cm

UB: 4.2cm TB: 4.8cm UBS: 3.5cm TBS: 4.5cm

Day 17

July 12th (Wed)

UB: 3.5cm TB: 4.2cm UBS: 2cm TBS: 3.9cm

UB: 4.3cm TB: 5.1cm UBS: 3.5cm TBS: 5cm

Day 18

July 13th (Thu)

UB: 3.5cm TB: 4.2cm UBS: 2cm TBS: 3.9cm

UB: 4.4cm TB: 5.2cm UBS: 3.6cm TBS: 4.3cm

Day 22

July 17th (Mon)

UB: 7.8cm TB: 6.9cm UBS: 9.1cm TBS: 11cm

UB: 4.7cm TB: 5.7cm UBS: 3.7cm TBS: 5.8cm

Day 24

July 19th (Wed)

UB: 9cm TB: 6.6cm UBS: 10.2cm TBS: 11.1cm

UB: 4.9cm TB: 5.8cm UBS: 3.7cm TBS: 5.9cm

Day 25

July 20th (Thu)

UB: 9.4cm TB: 7.1cm UBS: 10.3cm TBS: 12.5cm

UB: 5.3cm TB: 5.9cm UBS: 3.8cm TBS: 6.2cm

Day 29

July 24th (Mon)

UB: 10.2cm TB: 7.2cm UBS: 10.4cm TBS: 12.7cm

UB: 5.5cm TB: 6.3cm UBS: 3.9cm TBS: 6.3cm

Day 31

July 26th (Wed)

UB: 13.7cm TB: 8.4cm UBS: 17.9cm TBS: 17.9cm

UB: 5.5cm TB: 6.4cm UBS: 4.1cm TBS: 6.5cm

Day 32

July 27th (Thu)

UB: 13.5cm TB: 7.8cm UBS: 18.4cm TBS: 21.1cm

7DEOH 5

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References [1] J. Braam and E. W. Chehab, “Thigmomorphogenesis,” Curr. Biol., vol. 27, no. 17, pp. R863– R864, Sep. 2017, doi: 10.1016/j.cub.2017.07.008. [2] C. Coutand, S. J. Mitchell, S. Puijalon, and G. Monshausen, Eds., Mechanical Signaling in Plants: From Perception to Consequences for Growth and Morphogenesis (Thigmomorphogenesis) and Ecological Significance. in Frontiers Research Topics. Frontiers Media SA, 2017. doi: 10.3389/978-2-88945-074-9. [3] J. M.J., “Thigmomorphogenesis: The response of plant growth and development to mechanical stimulation.” Jun. 1973. [Online]. Available: https://link.springer.com/article/10.1007/BF00387472 [4] J. M.J. and F. S., “Thigmomorphogenesis: the effect of mechanical perturbation on plants.” Feb. 1993. [Online]. Available: https://link.springer.com/article/10.1007/BF00027213 [5] Infinite Spider, “Thigmomorphogenesis.” Infinite Spider, Nov. 17, 2015. [Online]. Available: https://infinitespider.com/thigmomorphogenesis/ [6] E. W. Chehab, E. Eich, and J. Braam, “Thigmomorphogenesis: a complex plant response to mechano-stimulation,” J. Exp. Bot., vol. 60, no. 1, pp. 43–56, Nov. 2008, doi: 10.1093/jxb/ern315. [7] B. Eric et al., “Mechanical stress acclimation in plants: Linking hormoness and somatic memory to thigmomorphogenesis.” Jan. 05, 2022. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/pce.14252 [8] E. Darwish et al., “Touch signaling and thigmomorphogenesis are regulated by complementary CAMTA3- and JA-dependent pathways,” Sci. Adv., vol. 8, no. 20, p. eabm2091, May 2022, doi: 10.1126/sciadv.abm2091. [9] T. Frank W. and J. Mordecai J., “Thigmomorphogenesis: Field and laboratory studies of Abies fraseri in response to wind or mechanical perturbation.” Feb. 1986. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1399-3054.1986.tb02411.x [10] M. H. Sigaye, “Fresh Herbage and Essential Oil Yield of Sweet Basil (Ocimum basilicum L.) as Affected by Mineral Fertilizers,” Los Angel., vol. 10, no. 389. [11] B. Yvette, “Health benefits of basil.” Jul. 13, 2023. [12] M. H. Shahrajabian, W. Sun, and Q. Cheng, “Chemical components and pharmacological benefits of Basil ( Ocimum basilicum ): a review,” Int. J. Food Prop., vol. 23, no. 1, pp. 1961– 1970, Jan. 2020, doi: 10.1080/10942912.2020.1828456. [13] K. W. Singletary, “Basil: A Brief Summary of Potential Health Benefits,” Nutr. Today, vol. 53, no. 2, pp. 92–97, Mar. 2018, doi: 10.1097/NT.0000000000000267. [14] A. Garibaldi, M. L. Gullino, and G. Minuto, “Diseases of Basil and Their Management,” Plant Dis., vol. 81, no. 2, pp. 124–132, Feb. 1997, doi: 10.1094/PDIS.1997.81.2.124. [15] B. Christopher David, “Blue Sage (Salvia azurea var. grandiflora.” 2023. [Online]. Available: https://www.fs.usda.gov/wildflowers/plant-of-the-week/salvia_azurea.shtml

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Safety System for Aircraft Water Landing in Emergency Situations Author 1

Author 2

Lesbekova Amina

School Name

Nazarbayev Intellectual School of Astana

Full Name

Murat Almas

Nazarbayev Intellectual School of Astana

Full Name (Last Name, First Name)

(Last Name, First Name)

School Name

Abstract Even with the strengthening of security measures in aviation, there are still unsolved problems related to the safety of passengers and aircraft, among which the complex problem of emergency landings on water stands out. This study introduces a safety system, drawing inspiration from automotive airbags, and incorporating machine learning techniques to address the challenge of emergency water landings. The system incorporates multiple automatic inflatable pontoons placed under the aircraft fuselage. Considering the location of the pontoons, the paper presents calculations of pontoons’ volume, their physical characteristics, the required amount of sodium azide and potassium nitrate for controlled inflation and the time of inflation of the pontoons. The financial impact of system implementation was calculated and accounted for 0.056% of the total aircraft cost. Interviews, source analysis, empirical experimentation, and machine learning algorithms methods were used in the investigation. Methods used, therefore, yield insights into complex dynamics, including aircraft water entry bank angles and immersion depths during water landings. The study underscores the need for the safety system's adoption, positioning it as a vital measure to safeguard lives and substantial aviation investments. Keywords: aircraft safety system, aviation, water landing, ditching, airbags, aerospace engineering, machine learning.

Introduction Despite the increased level of safety and precautions in the aviation industry, there are a number of neglected and currently unresolved problems for which it is not possible to ensure the safety of passengers or aircraft. One of these is the problem of aircraft water landing in emergency situations [1]. Firstly, in some situations, water landing may be the only way to save human lives. However, due to the lack of necessary equipment for aircraft, pilots tend to avoid landings on water, putting passengers' lives at risk. One proof of this is the landing on 15 January 2009, when Captain C.B. Sullenberger decided to ditch US Airways Flight 1549's Airbus A320 into the Hudson River due to a collision with a flock of birds only after he realized there was no other option. An investigation by the National Transportation Safety Board concluded that his decision to ditch in the Hudson had been appropriate [2]. This example demonstrates that water landings are very dangerous but may be necessary to save lives. Another example is the landing on October 15, 1956 of a Boeing 377 Stratocruiser flying from Honolulu to San Francisco when two of its four engines failed over the Pacific Ocean [3]. Overall, the aircrafts are required to land on water in the cases of bird strike, engine failure, terrorist attack, attempted hijacking, and running out of fuel. This shows that in a variety of the emergency situations, pilots may have to make on-water landings to ensure passenger safety.

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Secondly, the integrity of an expensive aircraft is almost impossible to maintain in current emergency situations. Nowadays it is almost impossible to restore a ship after landing. For example, an Airbus A320 that was grounded on the Hudson River was the only aircraft pulled out of the water after collision with water [4]. Taking into account the enormous cost of one plane, it’s hard to imagine what losses airlines incur during such accidents. For example, the AirBus A380 cost $489 million as of 2017 [5]. The problem is therefore pressing with regard to the economic damage caused by an emergency landing of an aircraft on the water. Thirdly, an aircraft can last no more than a few minutes [6]. For this reason, there is a risk that passengers and crew may not have enough time to evacuate the aircraft and that the vessel will inevitably sink before the emergency services arrive at the scene of the accident. For example, in 2022, a Tanzanian passenger plane made an emergency landing in Lake Victoria. At least 19 people died as a result. One of the reasons for the deaths was the fact that people did not manage to get out of the plane before it completely drowned [7]. Fourthly, The International Civil Aviation Organization (ICAO) establishes safety regulations and guidelines for air navigation. These regulations often prioritize keeping aircraft within proximity to airports to ensure better access to emergency services if needed. This practice can lead to more convoluted flight routes [8]. The increased distance traveled due to convoluted air routes leads to longer flight durations. This not only makes flying longer but also more expensive. These costs include fuel consumption, maintenance, crew salaries, and other operational expenses associated with extended flight times [9]. The energy consumption of aircraft increases several times due to such a tortuous route, which causes more carbon dioxide emissions into the atmosphere, causing irreparable damage to the environment. For example, convoluted European flight paths generate some 10% more CO2 emissions than if they were direct [10]. Besides, the aviation industry accounts for around 2.5% of global CO䈻 emissions, but 3.5% when we take non-CO䈻 impacts on climate into account [11]. The additional fuel burned during longer flights due to convoluted routes contributes to this environmental impact. Fifthly, an important problem is the ineffectiveness of existing measures to ensure passenger safety during a plane's splashdown. The main method of solving the problem at the moment is the use of swim waistcoats [12]. The disadvantage of this solution is that not all passengers can correctly use lifejackets, which can further complicate the evacuation process. For example, one of the reasons why many people died in the Ethiopian Airlines Boeing crash was the improper use of lifejackets [12]. Some of the passengers inflated them immediately. When the plane began to submerge, the waistcoats lifted the passengers to the ceiling and people were simply trapped with no chance of escape. Furthermore, during an interview with an experienced pilot, Anatoly Kulakov, it became clear that the presence and integrity of life jackets on board are not checked as thoroughly as required, in many cases the issue is ignored, which may increase the danger of the flight to passengers' lives and underlines the inefficiency of this method of solving the problem.

Background Information Defining the aims of the work and the objectives of the work The aim of the work is to develop a safety system for aircraft landings in emergencies based on the car airbag mechanism that will help reduce casualties during emergencies, as well as maintain the safety of the vessel. The objectives we aim to achieve throughout our project are: 1. Determine the optimal pontoon volume required to minimize impact forces during water landings, ensuring the aircraft's buoyancy and stability until rescue, through comprehensive theoretical calculations considering aircraft size and water conditions.

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2. Calculate the precise amount of reactants necessary for controlled nitrogen inflation of airbags during water landings, based on theoretical calculations that ensure rapid and effective deployment. 3. Identify optimal attachment locations for airbags and establish deployment timings through a combination of rigorous experimental testing and insights gathered from expert interviews. 4. Build, train, and save a machine learning model through convolutional neural network (CNN) for binary image classification. The objective is to create a model that can classify images of water bodies and non-water areas for the adoption in the Safety System for Landing an Aircraft on Water in Emergency Situations. 5. Conduct an economic analysis using theoretical calculations to evaluate the cost-effectiveness of implementing the proposed safety system, considering potential savings in aircraft salvage and repair processes. 6. Perform a thorough SWOT analysis to assess the strengths and weaknesses of the proposed safety solution, providing a comprehensive evaluation to guide further enhancements and refinements.

Airbags in cars Airbags are designed to prevent the head, neck and chest of the driver/passenger from hitting the dashboard, steering wheel or windscreen in a frontal collision [13]. They are often triggered in the event of a collision with another vehicle or a solid object, such as a tree/ Such an airbag is a multi-component system. Firstly, it includes the cushion itself, made of nylon (0.45-0.55 mm thick) coated on the inside with talcum powder to keep the surfaces "adhered" [14]. The nylon is coated with a layer of silicone or rubber to strengthen the tightness. Also, a gas generator is included to fill the cushion with gas [14]. Sensors that react to the impact (SRS system) bring the cushion into operation [13]. The most modern and advanced systems are also equipped with an electronic control unit [14]. The SRS system comprises three main components, the impact sensors at the front of the vehicle, the control unit (otherwise known as the SRS unit) and the squibs [13]. The impact sensors at the front of the vehicle are triggered when an impact occurs at a speed greater than 22 km/h [14]. The control unit receives the signal from the sensors and directs it, depending on whether it is better to deploy the airbag to the side or front (depending on the type of crash). Sensors, usually not less than three copies, are installed in car interiors and in doors. Eventually, the gas generators themselves become operational [13]. Electronic systems are also equipped with a capacitor which provides energy for the transmission of the signal from the sensor to the squib. The gas generator is essentially the squib. It is the most complex and sophisticated part of the SRS system mechanism. The solid propellant, usually in the form of small tablets, NaN3 - sodium azide, is burned by an electrical pulse applied by the impact sensors [15]. This decomposition reaction releases a lot of nitrogen gas, which quickly inflates the airbag. The combustion of this substance is very fast, but there is no explosion. Nitrogen makes up 45 percent of the mass of the combustion products. The remaining 55 percent are residual gasses. Carbon monoxide and carbon dioxide, water vapor and particulate matter are filtered out before entering the cushion. As a result, only nitrogen ends up in the cushion [15]. The cushion has a filling time of 30 to 55 milliseconds [16]. After that it remains in an unfolded state for about a second. Nitrogen, harmless for people, escapes through openings into the interior of the vehicle. This is the smoke that you see in the vehicle after the airbag has been deployed. The airbag deflates, making room for the breathing and movement of the person it protects.

Experimental Part Calculations of the volume of the airplane submerged in water

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To calculate the volume of the safety pontoons, it is necessary to calculate the volume of the submerged part of the aircraft fuselage. By experimentally calculating the volume of the airplane model at maximum and minimum immersion, it was determined: 93.2 ml was the volume of the submerged part in water and 630 ml was the volume of the entire airplane, respectively. Thus, 93.2

(1) 630 × 100% ࡨ 14. 8% - is the percentage of the airplane part of its total volume submerged in water. From the data on the Airbus A380 aircraft [17] - the length of the fuselage is 72.7 m, width - 7.15 m, height - 8.40 m. We can calculate the volume: ՌՎ՝՛ =

ՐՎ՝՛՟Վ՝՛ = 60.06 m ƫ

(ՁՎ՝՛)Վ՚՗Ֆ՜ = 4 ՟Վ՝՛ՐՎ՝՛ = 15. 015ƫ m2 ԿՎ՝՛ = (ՁՎ՝՛)Վ՚՗Ֆ՜(ՔՎ՝՛ ࡠ 2ՌՎ՝՛) = 15. 015ƫ(72. 7 ࡠ 2 * 60. 06) = 858. 86ƫ ࡨ 2698 m3 Thus, if the volume of the fuselage is 3500m3, then the volume of the airplane submerged in water equals to: (4) 2698 * 14. 8% ࡨ 400 m3 In order to prevent flooding of the aircraft or at least increase the time the aircraft remains on the water surface, it is important to prevent water from entering the aircraft in the event of depressurisation, i.e. the fuselage of the aircraft must be above water. For this purpose, the volume of the pontoons must be equal to or greater than the volume of the part of the aircraft that is submerged in water in the absence of depressurisation. Consequently, the volume of the safety pontoons must be equal to 400 m2. It is worth noting that, according to Stanislav Alexeyevich (engineer), river water and sea water (or rather their densities) can affect the necessary filling of pontoons with nitrogen. It is worth considering that in seawater the required immersion volume will be about 2% less than in freshwater, 3

and will be about 345. 3 Օ for Airbus A380. This is because the density of saltwater is greater than that of fresh water, 1020 kg/m3. However, due to the fact that the volume of pontoons required to land an aircraft on fresh water is sufficient to keep the aircraft on salt water, this factor was not taken into account in this work. In the following chapters, based on the results derived in this chapter, an experiment and calculations will be carried out to derive more accurate parameters of the safety pontoons.

Aim of the experiment This experiment was carried out in order to determine the most effective arrangement of the safety pontoons on the aircraft at various angles of heel of the aircraft diving into the water. The effectiveness of the pontoon arrangement was evaluated based on the depth of the model's submergence in the water upon impact with it, that is, the deeper the model was submerged in the water, the less effective it was. A reason for that, is if the aircraft sinks to a shallower depth, the force with which the water acts on the aircraft is reduced.

Hypothesis As the angle of the aircraft sinking into the water increases, the volume of pontoons needed to effectively maintain and reduce the depth of the plane sinking into the water will have to increase.

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Despite the high costs (both economic and physical - some of the weight of the aircraft will have to be diverted to the reactors to fill the airbags) of implementing a safety system to land aircraft in water, the approach may be the only way to save human lives and a costly aircraft.

Variables A separate experiment was conducted for each pontoon arrangement (Fig. 1-4) and then the data from each of the 4 experiments were compared to each other. Name of the variable

How is it varied?

Independent Variable

Bank angle of aircraft model entry into the water

With the help of a protractor, the bank angle was measured at the water entry point. At the range from 0-80 ± 1°C

Dependent Variable

Immersion depth of an airplane model fitted with 400 ml pontoons

It is recorded using a phone underwater and a ruler with a length of 30.00 ± 0.1 cm. Variable was measured in cm.

Control Variable

Arrangement combination

Different combinations of balloons were attached to the fuselage according to the hypothesis stated (Fig. 1-4)

Total volume of safety pantoons should be 400ml

It was measured using the Archimedes’ Law by putting the balloons into the flask in ml. t the volume of water that flows back.

Table 1. Variables

Materials 1. Airbus A380 model with the mass of 280g and volume of 630 ml - 1 pc. 2. Scale - 1 pc. 3. Sealant - 1 pc. 4. Torque/hot glue - 1 pc. 5. Cylindrical flask - 1 pc. 6. Water - 300,2 l. 7. Balloons - 30 pcs. 8. Water reservoir with the volume of 300L and free surface area of 1.5m2 - 1 pc 9. 30 cm long ruler with a graduation value of 1 mm - 1 pc. 10. Zip-trays - 5 pcs. 11. Phone (camera) - 2 pcs. 12. Roll of adhesive tape - 1 pc.

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13. Two-sided adhesive tape roll - 1 pc. 14. Roll of thread - 1 pc. 15. A pair of gloves - 2 pcs. 16. Respirator masks - 2 pcs. 17. Pump - 1 pc.

Method 1. Seal the aircraft using a sealant, ensuring all windows, gaps, and openings on the surface of the aircraft are carefully sealed: a. Wear a mask and gloves during this process; b. Allow the sealant to dry completely. 2. Inflate a water reservoir with a volume of 300L using a pump. 3. Place a ruler inside the water reservoir in a way that its graduations are visible when the phone is submerged. 4. Inflate 5 balloons of 50ml each, 7 balloons of 100ml each, and 2 balloons of 150ml each. Measure the volume of each balloon using a cylindrical flask. 5. Tape two 50ml balloons to the wings of the aircraft using double-sided tape. Attach the remaining 50ml (1) and 100ml (1) balloons to the aircraft using string. 6. Place the phone in a ziplock bag and activate camera 1. Submerge the handset in the water reservoir so that the divisions on the ruler are visible. Experimenter 1 positions themselves 1.2 meters away from the pool in a chair. Set up a tripod and camera 2 to capture angles of the aircraft's descent into the water relative to the water surface. 7. Experimenter 2 initiates 20 flight attempts of the aircraft, aiming to make it visible on both camera 1 and camera 2. Detach all balloons after each attempt. 8. Glue 50ml balloons onto the aircraft using double-sided adhesive tape. Attach the remaining 150ml balloons using string. 9. Experimenter 2 launches the aircraft 20 times, ensuring visibility on both camera 1 and camera 2. Remove all balloons after each attempt. 10. Attach 4 balloons using double-sided tape along the wings of the aircraft. Attach the remaining two balloons using string. 11. Experimenter 2 sends the aircraft flying 20 times, ensuring visibility on both camera 1 and camera 2. Remove all balloons after each attempt. 12. Glue 4 balloons to the wings using double-sided tape. Attach the remaining balloon using string. 13. Experimenter 2 launches the aircraft 20 times, aiming for visibility on both camera 1 and camera 2. Remove all balloons after each attempt. 14. Turn off both cameras. Record the results obtained from the flights and their corresponding arrangements.

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Fig. 1

Fig. 2

Fig. 3

Fig. 4

Analysis of results Immersion depth, ± 0.1 ɫm Angle interval, ± 1°

0 - 20

Arrangement 1

5.5

7.0

5.5

#4 6.5

Arrangement 2

Uncert Mean ainty #1

Uncert Mean ainty

6.0

6.1

6.0

5.8

5.0

6.5

5.8

0.8

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5.5

0.8

20 - 40 6.9

7.5

6.5

6.0

7.0

6.8

0.8

5.9

5.5

6.5

7.0

5.5

6.1

0.8

40 - 60 5.5

7.5

4.5

7.5

7.3

6.0

8.0

7.0

7.5

6.5

60 - 80 8.5 10.0 11.5

8.0

9.0

8.5

6.8

7.0

8.0

7.4

7.5

0.9

Table 2. Dependence of the immersion depth of an airplane model fitted with 400 ml pontoons on the bank angle of its entry into the water. Immersion depth, ± 0.1 ɫm Arrangement 3

Angle interval, ± 1°

Arrangement 4

Uncer Mean tainty

7.5

6.8

6.4

6.2

6.5

6.7

0.7

6.2

6.9

6.5

7.2

7.4

6.8

0.6

20 - 40 7.4

7.0

6.5

6.8

7.8

7.1

0.7

7.5

7.0

7.7

6.9

6.5

7.1

0.6

40 - 60 7.6

9.1

6.4

8.7

7.5

6.0

9.2

7.5

8.0

7.5

60 - 80 12.2 10.0 9.0

9.4

11.5

10.0

9.0

11.5

12.5

0 - 20

Table 3. Dependence of the immersion depth of an airplane model fitted with 400 ml pontoons on the bank angle of its entry into the water. As Tables 2 and 3 show, the following trend is observed with 400 ml cushion volume: . Regardless of the angle at which the aircraft enters the water, the aircraft sinks to a shallower depth when the No.2 pontoons are positioned. Consequently, if the aircraft sinks to a shallower depth, the force with which the water acts on the aircraft is reduced.

Combustion of sodium azide and potassium nitrate Combustion of sodium azide occurs according to the reaction equation: 2ԼՉԼ3(՛) ͫ 2ԼՉ(՛) + 3Լ2(Տ), Ֆ(Լ2) = ՄԼ /ՄՕ = 400000/22. 4 = 17857 mol; 2

Լ2: ԼՉԼ3; 3 : 2; 17857 mol : Ֆ(Լ2); Ֆ(Լ2) =

17857 × 2 = 11904 mol; (which is the same for ԼՉ) 3

Օ(ԼՉԼ3 ) = Ֆ × Ի = 11904 × 65 = 773760 = 773. 76 kg

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and, in order to neutralize the released sodium, potassium nitrate (ԹԼԽ3) is used, with which it reacts. 10ԼՉ(՛) + 2ԹԼԽ3(՛) ͫ Թ2Խ(՛) + 5ԼՉ2Խ(՛) + Լ2(Տ); ԼՉ : ԹԼԽ3; 10 : 2; 25075 mol : Ֆ(ԹԼԽ3); Ֆ(ԹԼԽ3) =

11904 × 2 = 2380, 8 mol; 10

Օ(ԹԼԽ3) = Ֆ × Ի = 2380, 8 × 101 = 240460, 8 = 240, 5 kg. Thus, based on the calculated data, it turns out that the required amount of sodium azide to inflate the airbags for the Airbus A380 aircraft at full load (560 tons) is 773.76 kg, and the amount of potassium nitrate - 240.5 kg.

Determination and calculation of airbag parameters and airbag deployment time Based on the parameters of the Airbus A380 [17], the following calculations were made: Safety pontoons under the fuselage: ՉՎ = 27. 87m ՊՎ = 2. 63 m ՄՎ = 110m3 ԯՎ = ՉՎ × ՊՎ = 27. 87Օ × 2. 63Օ = 73. 3m2 3

ՐՎ = ՄՎ ÷ ԯՎ = 110Օ ÷ 73. 3Օ = 2. 5m Minimum amount of pontoons = ՉՎ ÷ ՐՎ = 27. 87Օ ÷ 2. 5Օ ࡨ 11 Չ՗Վ ՗ՖՍ ՘՗Ֆ՜՗՗Ֆ = ՉՎ ÷ ՉՕ՗՝Ֆ՜ ՗Վ ՘՗Ֆ՜՗՗Ֆ՛ = 27. 87Օ ÷ 11 = 2. 53m Մ՗Վ ՗ՖՍ ՘՗Ֆ՜՗՗Ֆ = ՉՎ × ՐՎ × ՊՎ = 1. 5Օ × 2. 63Օ × 2. 53Օ = 9. 9m3 Safety pontoons under the wings on the plane: Չ՟ = 14. 4 m; Պ՟ = 2. 5 m; Մ՟ = 90 m3 ԯ՟ = Չ՟ × Պ՟ = 14. 4 × 2. 5 = 36 m2 Ր՟ = Մ՟ ÷ ԯ՟ = 90 ÷ 36 = 2. 5 m Minimum amount of pontoons = ՉȄ ÷ ՐȄ = 14. 4 ÷ 2. 5ࡨ 6m Չ՗Վ ՗ՖՍ ՘՗Ֆ՜՗՗Ֆ = ՉȄ ÷ ՉՕ՗՝Ֆ՜ ՗Վ ՘՗Ֆ՜՗՗Ֆ՛ = 14. 4 ÷ 6 = 2. 4m

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Մ՗Վ ՗ՖՍ ՘՗Ֆ՜՗՗Ֆ = ՉȄ × ՐȄ × ՊȄ = 2. 4 × 2. 5 × 2. 5 = 15 m3 In order to distribute the number of reactants per squib under the fuselage or under the wing, a proportion can be used: ՠՓՏ = (773, 76 * 9, 9)/400 = 19, 15 kg of sodium azide per 1 squib under the fuselage Further, the next chapter describes the inflation process in more detail, where we explained why there should be 10 squibs inflating 1 pillow: 19, 15/10 = 1, 915kg of sodium azide per 1 squib per 0.99 m3 under the fuselage So, the required amount of potassium nitrate per 1 squib per 0.99 m3 would weigh 0.595 kg. The total mass of reactants per 1 squib under the fuselage is 2.510 kg. Similarly, for 1 squib under the wing on 1.5 m3, the mass of sodium azide is 2.902 kg, and of potassium nitrate - 0.902 kg. The total mass per 1 squib under the wing is 3.803 kg. Taking into account the fact that a 67-liter bag opens in 30 milliseconds [21], we can calculate that the speed of opening of the safety pontoons is equal: For the safety pontoons under the wings: 18m3=18000L ՜67Ժ=30 ms= 0.03 s ՜15000Ժ =

15000 ×0.03 67

= 6. 7s

For safety pontoons under the fuselage: 9.9m3=9900L ՜9900Ժ =

9900 ×0.03՛ 67

= 4. 4 s

However, 10 squibs will be used to inflate each safety pontoon at once, which will therefore reduce the inflation time by a factor of 10: ՜15000Ժ = 6. 7 ÷ 10 = 0. 67 s ՜9900Ժ = 4. 4 ÷ 10 = 0. 44 s Given the fact that the density of nylon-graphene fabric is 1300 kg/m3, the mass of fabric required to create safety pontoons under the fuselage: ƬՎՉՊ՚ՑՋ = 1300 kg/m3 ՉՎ = 2. 53 m ՊՎ = 2. 63 m ՐՎ = 2. 5 m ՐՎՉՊ՚ՑՋ = 0. 00055 m

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ՁՎ՚ՍՍ ՛՝՚ՎՉՋՍ = 2(ՉՊ + ՊՐ + ՉՐ) = 2(2. 53 × 2. 63 + 2. 63 × 2. 5 + 2. 53 × 2. 5) = = 38. 65 m2 ՄՎՉՊ՚ՑՋ = Ձ Վ՚ՍՍ ՛՝՚ՎՉՋՍ × ՐՎՉՊ՚ՑՋ = 38. 65 × 0. 00055 = 0. 021 m3 ՕՎՉՊ՚ՑՋ = ƬՎՉՊ՚ՑՋ × ՄՎՉՊ՚ՑՋ = 1300 × 0. 021 = 28 kg

Weight of fabric to create safety pontoons under the fenders Չ՟ = 2. 4 m3 Պ՟ = 2. 5 m3 Ր՟ = 2. 5 m3 ՁՎ՚ՍՍ ՛՝՚ՎՉՋՍ = 2(ՉՊ + ՊՐ + ՉՐ) = 2(2. 4 × 2. 5 + 2. 5 × 2. 5 + 2. 4 × 2. 5) = = 36. 5 m3 ՄՎՉՊ՚ՑՋ = Ձ Վ՚ՍՍ ՛՝՚ՎՉՋՍ × ՐՎՉՊ՚ՑՋ = 36. 5 × 0. 00055 = 0. 0201 m3 ՕՎՉՊ՚ՑՋ = ƬՎՉՊ՚ՑՋ × ՄՎՉՊ՚ՑՋ = 1300 × 0. 0201 = 26 kg

Principle of operation of the safety system for water landing aircraft Attachment plate In this paper we propose the implementation of an attachment plate (see Figure 6), made of titanium, which performs a function similar to that of the SRS unit in car airbags. Car airbags deploy when an impact sensor detects a collision strong enough to trigger them. The sensor sends an electrical signal to trigger a chemical reaction that fills the airbag with harmless gaseous nitrogen [14]. However, the attachment plate proposed in the paper has a number of modifications: Firstly, 10 squibs are mounted on the attachment plate at once, which will considerably reduce the time of inflating safety pontoons. On a car, there is only one squib attached that transports the signal, which is why this can be considered a significant change. Swift and efficient deployment of safety pontoons is crucial to minimize the impact forces during water landings, increase the chances of successful aircraft evacuation, and improve passengers' survival rates. Secondly, this plate is made of titanium, which means that it will combine both high lightness and durability [18]. The attachment plate needs to withstand the impact forces and stresses associated with water landings. It will experience significant forces during deployment, and its durability ensures that it can withstand these forces without deformation or failure. A durable attachment plate is less likely to suffer from wear and tear over time, reducing the risk of malfunction during critical moments. This ensures that the safety pontoons deploy as intended in emergency situations. Thirdly, aircrafts are designed to be as lightweight as possible to optimize fuel efficiency and overall performance. Any additional weight added to the aircraft must be carefully considered. A lightweight attachment plate helps mitigate the impact of adding safety systems on the overall weight of the aircraft. Excess weight can affect the aircraft's flight characteristics, fuel consumption, and maneuverability. A lightweight attachment plate contributes to maintaining the aircraft's optimal performance and handling.

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Fig. 6 1 - squibb locations 2 - fastening plate

Fastening method The idea is to position the airbags, pontoons, in the lower part of the fuselage and under the wings of the aircraft. To do this, a recess must be made in the lower part of the fuselage and under the wings (see Fig. 2). The attachment plate is inserted in this recess. The compressed safety pontoon is then attached to the attachment plate using special hooks and clips. The structure is then sealed using a special flap that follows the shape of the fuselage to ensure that the structure does not affect the streamlining of the aircraft.

Location of the pontoons In the course of an interview with Stanislav Gorkovenko, Engineering Technician of the AN-24 civil aircraft, it was suggested that when this system is implemented, the pontoons should be located in four basic positions: under the nose of the aircraft, under the tail section and under the wings. In the experimental part of the work some possible combinations of pontoon positions were tested on the model of the Airbus A380 aircraft. After all the tests and an evaluation of the feasibility of their implementation, the best combination of safety pontoons has been concluded (see figure 2).

Sensors Based on the ship's sensor, the pontoons will unfold and fill with gas a few moments before impact with water. In contrast to airbags in cars, several sensors must be involved in order to activate the pontoons on an aircraft: 1. Speed indicator: a sensor that indicates the speed of the aircraft relative to the air environment [19]; 2. Vertical speed indicator: an indicator that shows the vertical speed of the aircraft [20]; 3. Cameras or radars: these sensors will be located in the lower part of the fuselage and will determine what surface is to be collided with: whether the surface is solid or liquid; whether the surface is only a puddle of water or a sea/lake/ocean.

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The only limiting factor for the application of the mentioned sensors is the fact that nowadays there are no cameras or radars that can be used for the intended purpose. This is what we are trying to tackle in this research paper as well.

Machine learning modeling through convolutional neural networks for surface identification system Recognizing the limitations of current sensor technology, we introduce a solution that leverages machine learning algorithms to accurately identify and analyze the water landing surface. This model is developed through comprehensive training on a diverse dataset, inclusive of distinct surface types and conditions, specifically referencing the "Satellite Images of Water Bodies" dataset authored by Francisco Escobar [21]. The code was written on the kaggle.com platform. The integration of this model into an operational system enables real-time processing of incoming data streams. Employing convolutional neural networks (CNNs), the architecture systematically analyzes images through successive convolution and pooling layers, culminating in densely connected components for precise binary classification. Methodical optimization demonstrates the model's aptitude in accurately discerning water bodies, thereby enhancing landing precision for aviation applications. The code begins by importing the necessary libraries, including tools for data preprocessing, model building, and training. The dataset directory path is specified, and image dimensions (img_height and img_width) as well as the batch size for processing are defined. Data generators are then created using the ImageDataGenerator class from Keras. These generators efficiently load and preprocess images in batches, while also splitting the dataset into training and validation subsets. The training and validation data are loaded using these generators, and the images are resized to the specified dimensions. The subset parameter is employed to differentiate between training and validation data.

Fig. 7

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Fig. 8 The CNN model is constructed using the Keras Sequential API. It comprises a series of convolutional (Conv2D) layers, which learn hierarchical features from the images. These convolutional layers are followed by max-pooling layers that reduce the spatial dimensions of the feature maps. The final layers consist of fully connected (Dense) layers. Dropout regularization is applied to the first dense layer to mitigate overfitting. The last dense layer uses the sigmoid activation function to yield binary classification results (water or non-water).

Fig. 9 The model is compiled using the Adam optimizer, which adapts the learning rate during training, and binary cross-entropy loss, suitable for binary classification tasks. The accuracy metric is specified to assess model performance.

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Training of the model occurs using the fit method. The model is trained on the training data using the train_generator and validated using the validation data from the val_generator. The number of training steps per epoch and validation steps are determined based on the dataset size and batch size. Finally, the trained model is saved to a file named "water_body_model.h5". This allows the model to be loaded and utilized for making predictions on new images in the future, without needing to retrain from scratch. In summary, this code demonstrates the complete pipeline of constructing, training, and saving a CNN-based machine learning model for binary image classification, specifically to classify satellite images with or without water bodies. Finally, this model illustrates the accuracy of the system being close to 1.

Fig. 10

Fig. 11

Safety system activation If the aircraft safety system receives a signal from cameras that the surface over which it is flying is water, and the vertical speed indicator shows a sharp increase in the vertical speed of the aircraft, the system calculates the distance from the water to the fuselage at which the safety pontoons should open

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according to the following steps: Ձ = ՝՜ + 2 Չ՜ , where time is 0.44 seconds (inflation time per safety pontoon), based on the aircraft's sink rate indicated by the speed indicator. It should be noted that depending on the identified surface type and nature, the system orchestrates a symphony of aerodynamic modifications and control inputs. These adjustments encompass a spectrum of factors, including descent angle, landing gear deployment, and wing configuration. For instance, if the model categorizes the surface as a calm lake, it should prompt the aircraft to adopt a gentle descent angle and ensure a controlled touchdown. In contrast, when facing a turbulent ocean, the system should dictate a steeper angle of approach and recommend retracting the landing gear to minimize impact forces. By tailoring these adjustments to the specific surface characteristics, the system optimizes the chances of a safe and secure water landing. The safety system (the airbags themselves) will be located inside the lower fuselage and, in the event of an electrical signal from a sensor, will fill with gas and deploy. This will reduce the dive depth of the aircraft and also secure it, which may later provide a more economical path to repair. Aircraft are usually sent out for decommissioning after (if) they can be salvaged after landing in the water [8]. More often than not, most aircraft sink in emergency water landings/falls [22]. The use of air pontoons for an aircraft will successfully keep it on the surface of the water for long periods of time, providing efficiency and saving millions of dollars for companies.

Airbag fabric material Nylon 66 is often used in airbags in cars. However, we propose the use of Nylon-Graphene composite, which has several advantages over Nylon 66, and in particular a significant increase in strength with a minimal loss of elasticity. The maximum tensile strength of Nylon 66 is about 50-60 MPa, which is quite high, but according to the calculations below, this is not enough, as the pressure the gas exerts on the nylon fabric in pontoons will be equal (considering that the pressure inside airbags when deployed in cars is 1.25 atm): ԯՋ՚՗՛՛ ՛ՍՋ՜. = ԾՍ՚ՑՕՍ՜Ս՚ * ՜ՐՑՋՓՖՍ՛՛ ՎՉՊ՚ՑՋ = 4 * (2. 4 + 2. 5 + 2. 5) * 0. 0007 = 0. 021m3 ԴՉՑ՚ ՗Ֆ ՜ՐՍ ՎՉՊ՚ՑՋ = Ծ * ՁՎ՚ՍՍ ՛՝՚ՎՉՋՍ = 125000 * 36. 5 = 4562500 N; Ɵ=

ԴՉՑ՚ ՗Ֆ ՜ՐՍ ՎՉՊ՚ՑՋ ԯՋ՚՗՛՛ ՛ՍՋ՜.

4562500 = 217261904 0.021

ࡨ 217. 3 MPa;

Graphene itself is an excellent material to solve this problem. But as it is inelastic, the best solution would be a nylon-graphene composite, where more nylon is there to maintain elasticity and less graphene, as its presence multiplies the strength. From a scientific paper that was written by Jay Yang Han et al. (2022), which first described the results of the strength limit of Graphene-Nylon 12: from 310.4 MPa to 462.3 MPa, we can understand that the use of this particular material is important for this situation. [23]. Such a dramatic jump has been created by only a small amount of graphene in nylon - 0.15 wt%. This large difference in mechanical tensions can be attributed to the fact that graphene in its pure form has an astounding 1100 GPa. Thus, the use of this particular material as a fabric for pontoons will be the most optimal solution. The production of graphene powder is also increasing.

Calculations of the cost of implementing a safety system for water landing aircraft The average cost of an airbag control module is $46 [24]. Consequently, the cost of safety pontoons is equivalent: Ա՗՛՜400000Ժ =

400,000×46 67

= $274, 627

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The Airbus A380 was worth $489 million at the time of 2017. This implies that the price of the plane will increase by: $ 274,627 × 100% =0.056% $489,000,000

Results and Discussion In order to more fully evaluate the effectiveness and necessity of a safety system for water landing aircraft, a SWOT analysis was conducted in which the proposed solution was evaluated in terms of various factors. Strengths: From a societal standpoint, the introduction of the proposed safety system for aircraft landings in emergencies holds significant promise in terms of enhancing passenger and crew safety. By providing pilots with a reliable mechanism to execute water landings when circumstances demand it, the project addresses a critical gap in aviation emergency response. This system's potential to minimize the loss of life during air accidents underscores its inherent strength, aligning with a core mission of safeguarding human lives through innovative design and technology. Additionally, the projected reduction in casualties and injuries can positively impact public confidence in air travel, fostering a sense of security among passengers. Weaknesses: One of the significant weaknesses of our project lies in the absence of established certification for the safety system. Another notable limitation is our focus on the Airbus A380 for our safety system's integration. This exclusivity restricts the immediate applicability of the solution to other aircraft models, potentially hindering its widespread adoption. Real-world operational environments in aviation are incredibly diverse, encompassing a wide range of weather conditions, lighting, and terrain characteristics. Ensuring that our safety system performs consistently and accurately across these diverse conditions demands rigorous testing and validation, which is also one thing we lack. Also, the effectiveness of our machine learning model heavily depends on the quality, diversity, and representativeness of the training dataset. Any limitations in the dataset's diversity or availability might result in biased or inaccurate predictions. At this stage our code does not include parameters such as adjusting to the water entry bank angle of the plane and distance towards the water surface. Opportunities: Within the economic landscape, the adoption of the proposed safety system presents a strategic opportunity for airlines to demonstrate a strong commitment to passenger safety while maintaining fiscal prudence. The calculated cost per aircraft unit for implementing the safety system, estimated at approximately 0.056%, suggests a reasonable investment for the potential life-saving benefits it provides. This economic feasibility offers a compelling value proposition, positioning airlines to differentiate themselves as safety-conscious carriers. Furthermore, the integration of cutting-edge safety measures could positively impact brand reputation and customer loyalty, translating into long-term economic gains. Threats: Economically, the requirement for regular renewal of pontoons introduces an ongoing operational consideration. While the initial implementation costs might be justifiable, the sustainability of this safety system could be challenged by the recurring costs associated with maintaining, inspecting, and replacing the pontoons. Manufacturers and operators may question the allocation of resources toward maintaining a system designed for rare, albeit critical, emergency scenarios. The perceived imbalance between costs and benefits could potentially hinder long-term adoption and undermine the system's intended impact. It's crucial to address these concerns and communicate the enduring value of the

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safety system.

Conclusion This study presents a solution aimed at redefining aviation safety measures, drawing inspiration from automotive airbag technology and incorporating advanced machine learning techniques. Through the integration of these methods, the proposed safety system offers a solution to the ongoing challenge of emergency water landings in aviation. Despite the evolution of security measures, this challenge remains significant. The incorporation of advanced techniques represents a substantial advancement in addressing the inherent risks associated with such situations. The study's central focus involves careful calculations and empirical experiments to determine the optimal pontoon volume necessary to minimize impact forces during water landings. This involves precise quantities of reactants, specifically 773.76 kg of sodium azide and 240.5 kg of potassium nitrate, to ensure efficient inflation of the airbags. An integral aspect contributing to the system's effectiveness is the innovative design of the attachment plate, crafted from lightweight yet strong titanium. This design innovation enhances the reliability and operational efficiency of the proposed safety solution. Additionally, the study employs cutting-edge machine learning techniques, particularly a Convolutional Neural Network (CNN), to introduce a fresh approach to identifying water surfaces during water landings. This addresses the limitations posed by sensor constraints, allowing real-time binary classification of water bodies. The significance of this development lies in its improvement of landing precision, a crucial factor in enhancing aviation safety. An in-depth economic analysis underscores the practical feasibility of implementing the system. The associated costs, accounting for a minor 0.056% of overall aircraft expenses, highlight the cost-effectiveness of the proposed safety system. This economic perspective emphasizes the practical value of the safety solution in terms of potential savings in salvage and repair operations, strengthening its case as a strategic investment in aviation safety. Empirical findings and comprehensive calculations reveal the tangible benefits of strategically positioned safety pontoons. These placements result in reduced aircraft submersion depth upon impact, thereby mitigating the force of water impact. This underscores the importance of thoughtful safety component design and placement in optimizing the outcomes of emergency water landings. However, the study's conclusions also bring attention to ongoing operational considerations, such as the need for periodic pontoon renewal. Such factors underscore the necessity for a balanced evaluation of the safety system's long-term sustainability, achieving a harmonious balance between operational feasibility and safety enhancement.

References [1] https://www.businessinsider.com/why-its-hard-for-planes-land-on-water-2019-10 [2] https://www.britannica.com/topic/US-Airways-Flight-1549-incident [3] https://timesofindia.indiatimes.com/world/rest-of-world/they-went-down-how-boeing-737-pilots-survi ved-hawaii-ditching/articleshow/84087509.cms [4] https://airandspace.si.edu/albums/visit-miracle-hudson-aircraft [5] https://pilotpassion.com/how-much-does-an-airbus-plane-cost/ [6] https://executiveflyers.com/do-airplanes-float-on-water/ [7] https://www.reuters.com/world/africa/precision-air-plane-crashes-into-lake-victoria-tanzania-state-me dia-2022-11-06/

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[8] https://icao.int/Pages/default.aspx [9] https://www.icao.int/MID/Documents/2017/Aviation%20Data%20and%20Analysis%20Seminar/PPT 3%20-%20Airlines%20Operating%20costs%20and%20productivity.pdf [10] https://www.swissinfo.ch/eng/business/reform-europe-s-airspace-to-cut-emissions--say-swiss-flight-e xperts/48565476 [11] https://ourworldindata.org/co2-emissions-from-aviation [12] https://simpleflying.com/aircraft-water-landing/ [13] https://doi.org/10.1504/IJCAT.2000.000235 [14] https://www.swicofil.com/consult/industrial-applications/technical-applications/airbags [15] https://www.scientificamerican.com/article/how-do-air-bags-work/ [16] https://cen.acs.org/safety/chemicals-make-airbags-inflate-changed/100/i41 [17] https://www.modernairliners.com/airbus-a380 [18] https://monroeengineering.com/blog/pros-and-cons-of-titanium/ [19] https://www.electronicsforu.com/market-verticals/sensors-strength-aviation-aerospace [20] https://skybrary.aero/articles/vertical-speed-indicator [21] https://www.kaggle.com/datasets/franciscoescobar/satellite-images-of-water-bodies?resource=downlo ad

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Optimizing the shape of the blade for improved efficiency in Savonius-type wind turbine Author 1

Author 2

Nam, Dohyun

School Name

Gyeonggi Science High School for the Gifted

Full Name

Bae, Yohan

Gyeonggi Science High School for the Gifted

Full Name (Last Name, First Name)

(Last Name, First Name)

School Name

ABSTRACT: This study explored a method to search the shape of the blade for increased efficiency of a Savonius turbine at a relatively low wind speed (5݉/‫ )ݏ‬for urban wind power generation. A genetic algorithm was used to find the optimal curve, and each gene consists of points that form the curve shape. The fitness function was the square of the angular velocity of the blade obtained through CFD (computational fluid dynamics) simulation as it converged, as the output coefficient could not have been calculated through Betz’s law, due to the limitation of the simulation. Based on the system, a new generation was born with various genetic operations applied. The geometric structure and environmental structure had been fixed, but they could be varied by the requirement, searching for the optimal shape of the Savonius turbine with different shapes or introduced to parametric settings.

KEYWORDS: Renewable energy, Vertical-axis wind turbine (VAWT), Savonius turbine, Genetic algorithm, Computational Fluid Dynamics (CFD)

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Introduction Research on renewable energy had progressed rapidly as global warming and climate change were rated as general issues and future tasks, heading for net zero emission. A particular solution to the problem is wind power. It is generated through wind generators often gathered in massive-scale of wind farms. They are usually large horizontal-axis wind generators, which can only be used in remote areas where the wind blows consistently (in direction and intensity); stability of generation is required, and there is also a noise problem. On the other hand, vertical-axis wind generators have the disadvantage of having a relatively low output coefficient, but they can generate power stably even though the air current is inconsistent. The study explored a small wind generator, mainly targeted to be used in urban areas to increase its accessibility. The model is a Savonius-type turbine, one of the vertical axis wind generators. The shape of its wing was analyzed to enhance the efficiency of the turbine in a particular environment, with a genetic algorithm.

Theoretical Background Vertical axis wind turbine Vertical Axis Wind Turbine (hereinafter referred to as VAWT) has a generator axis and wind direction perpendicular to each other (Figure 1). Depending on the shape of the blade, it is called Savonius type, Darius type, H type, Gyromill type, etc. In particular, the Savonius-type turbine was used in this research, which is shaped like semi-cylinders facing each other; their shapes have changed over time with efficiency. It is the second turbine from the left of Figure 1, and some versions of the turbine have spiralshaped wings.

Figure 1. HAWT and various types of VAWT [1] The Savonius turbine is rotated by net drag received by the blade. Its magnitude varies depending on the degree to which the blade is curved, the physical feature such as mass, the moment of inertia, and ultimately the output coefficient of the blade varies [1, 2].

Betz’s law Betz's law calculates the energy conversion efficiency of wind turbines [3]. The output coefficient is the rate at which a wind turbine converts wind energy into mechanical energy(rotation). Its notation is ‫ܥ‬௣ and can be calculated with Equation 1 by Betz's law. ‫ܥ‬௣ = (1/2)(1 + ܽ െ ܽଶ െ ܽଷ )

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(1)

Figure 2. Physical modeling of wind turbine In equation (1), ܽ is the ratio of the output wind speed to the input wind speed, which corresponds to ‫ݒ‬ଶ /‫ݒ‬ଵ in Figure 2. In other words, if the output wind speed is obtained from the given input, ‫ܥ‬௣ is calculated. Theoretically, ‫ܥ‬௣ is the largest at 59.3% with ܽ = 1/3. Practically, some horizontal-axis wind turbines have an output coefficient close to this value [3].

Genetic algorithm A genetic algorithm (referred to as GA, hereinafter) is a computational optimization technique for finding solutions with insufficient information, mimicking the process of natural evolution. Various operations such as evaluation, crossover, and mutation exist. The first generation was made with initialization. Each gene is evaluated with fitness function, and they are selected by the score with specific criteria. A new individual is created through the crossover of the two selected genes, and some undergo mutation, in order to avoid the locally optimal solution. These processes are iterated, making generation after generation, eventually getting close to the solution, just like evolution. This is just the structure of GA, and operations and fitness functions need to be designed. Ideally, the fitness scores of the generations increase as the algorithm is iterated, just like the evolution of creatures.

Method Analysis System I Analysis System I was a prototype, utilizing a 3D design program Blender to create objects. 25 points were selected in the first quadrant in the ‫ ݔ‬െ ‫ ݕ‬plane, forming a Bezier curve. The "Screw" function was provided, allowing the entire curve to be twisted up (Figure 4). However, the file format provided by Blender was not supported by any CFD program and cannot be written.

Figure 4. The blade is designed with Blender The fitness function was based on the CFD program of Autodesk. But, apart from which physical value was used as the function, the program was slow in computing, and it was necessary to find a new methodology for fitness determination and object creation.

Analysis System II

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The new analysis system was based on the CFD of Ansys. A program called Fluent could run fluid dynamics simulations and create objects that can be internally simulated and is much faster than Autodesk. The design of the gene must be preceded before expressing genetic operations. A single gene represented the wing’s shape, the curve drawn with 25 points expressed in polar coordinates (Figure 5). The wing was copied to constitute a four-leaf blade, which had higher ‫ܥ‬௣ than a three-leaf blade with a high wind speed condition. [4]. Twenty genes form a single generation.

Figure 5. Illustration of the blade with 25 points The 25 coordinates of the points were selected by designating ߠ to each ‫ݎ‬, and the radius formed an arithmetic sequence from – 4 to 20. The pseudocode of the algorithm is shown below. gene = array for ݅ = 0 ‫ ݋ݐ‬24 ‫ݎ‬௜ାଵ = 4 + (20 െ 4)/24 × ݅ ߠ௜ାଵ = random value from (ߠ௜ , ߨ) add (‫ݎ‬௜ାଵ , ߠ௜ାଵ ) to gene End for After the wing was formed, each of them was simulated using Fluent. The Geometry designed objects for simulation (Figure 6, 7) using Python script. The code generated the wing and rotated it to form a four-leaf blade. The material was Aluminium-1060-H12 with a density of 0.002705݃/݉݉ଷ , and it was used to calculate the mass and the moment of inertia of the blade. Output wind speed could be derived from the simulation, and ‫ܥ‬௣ could be then calculated. It was the fitness function of the blade.

Figure 6. Ansys Fluent Interface

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Figure 7. Blade made from Geometry (Python script)

Pre-simulation A blade with a semicircular wind was simulated (Figure 8). It is 40cm in diameter and 1m in height. The input wind speed was 5݉/‫ݏ‬, and the angular velocity and output wind speed over time are shown in Figures 9 and 10.

Figure 8. Semicircular wing blade

Figure 9. ߱ െ ‫ ݐ‬graph (Angular Velocity Graph)

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Figure 10. ‫ݒ‬ଶ െ ‫ ݐ‬graph (Output Wind Speed Graph) The output wind speed was always calculated to be 5 m/s, which was equal to the input value (Figure 10). There was a problem with the method of calculating output wind velocity, and ‫ܥ‬௣ was meaningless. Thus, a new method was needed to calculate the output coefficient, and it was concluded that ‫ܥ‬௣ is proportional to the power supplied to the generator. ‫ܥ‬௣ is the ratio of mechanical energy extracted from the air current, and it was assumed to be constant; The power supplied to the generator is proportional to the mechanical energy of the blade, which is proportional to ߱ଶ as the blade is plugged into the shaft of the generator and other constants are consistent, due to controlled geometric structure. Also, the angular velocity of the blade was assumed to converge exponentially, which is physically reasonable: Figure 9 is the result of the simulation of a semicircular blade with very small inertial moment and mass, and the angular velocity must converge to a specific value. Let the value be ߱଴ , then ‫ܥ‬௣ = ߱଴ଶ , and it was derived from the trend line analysis with the equation of ߱(‫߱ = )ݐ‬଴ െ ‫ି ݁ܣ‬஻௧ .

Figure 11. ߱ െ ‫ ݐ‬graph of a particular gene

Figure 12. Trend Line Analysis

Restriction of chromosome Among the first generation, some genes were almost blocked at the center (Figure 13). As a result of the simulation, ߱଴ was significantly smaller than that of other blades. This phenomenon occurred similarly to other blades that were blocked at the center.

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Figure 13. A particular gene of the first generation

Figure 14. ߱ – ‫ ݐ‬graph of the gene in Figure 13. Initially, the angular velocity increased and then suddenly decreased to zero. Analyzing the animation of the process, the blade initially turned in one direction and stopped, turning the other way. This phenomenon was repeatedly discovered later but ߱ eventually converged. In this case, the peak value decreased, and the blade would stop after an infinitely long period. With the velocity contour, which displays the vector field of fluid velocity, it was evident that the wind speed in the center area remained almost zero (Figure 15).

Figure 15. velocity contour In other words, the gap between the wings was practically impervious. The center gap must be perforated to receive the maximum net drag, which operates the Savonius turbine. Therefore, the

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algorithm for generating the first generation must be modified.

Modified algorithm for Initialization The primary method of randomly corresponding ߠ to ‫ ݎ‬of an arithmetic sequence had la imitation: The probability that all 25 ߠ were ideally evenly distributed without arbitrarily limiting the selection range was extremely slim, so the center gap was prone to be blocked. In addition, it was difficult to give out a specific relationship between ߠ and ‫ ݎ‬to have the center pierced. The algorithm had been changed. First, the blade changed from four leaves to three leaves. The Fourleaf blade was prone to have its wings overlapping, and genetic diversity would be damaged if only the appropriate genes were selected. Also, 5݉/‫ ݏ‬is classified as high wind speeds in urban areas, and ‫ܥ‬௣ of a three-leaf blade is greater than that of four-leaf [4,5]. Also, upper and lower limits for the random selection of points were set to avoid the intersection of the wings, so that the center gap would not be clogged (Figure 16).

Figure 16. Area for selecting points of each wing 25 ߠ formed decreasing arithmetic sequence from ߨ to 0 and ‫ ݎ‬was corresponded with a previous value associated to avoid excessive bending (i.e., selecting a value larger than the previous value multiplied by a specific number). The expressions for the upper and lower limits were as follows. ‫)݌( ܥ‬: ‫݌(ݎ‬, ߠ) = 4 × 5(ఏିగ)(ఏି௣గ)/௣గ

మ

(2)

Equation 2 originated from ‫݌ݔ݁ = ݎ‬൫݂ (ߠ)൯ with boundary conditions of ݂(0) = ݈݊20 and ݂(ߨ) = ݈݊5 since inner radius was 5ܿ݉ and outer radius was 20ܿ݉ as a quadratic form. The problem with this method was that some points had extremely large curvature. The principle of simulation in CFD is to create an object in Geometry (Figure 6) and divide the region in Mesh to calculate the physical quantity for infinitesimal time at each point. Around the points with large curvature, the mesh size was significantly small, resulting in a floating-point exception (an error occurring from dividing with 0, due to the small size of the mesh).

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Figure 17. Dimension of the blade In conclusion, the curve should be smooth without blocking the center gap. The moving average was supposed to smoothen the curve, but the gap between adjacent ߠ was too large and it was possible that ‫ ݎ‬to be beyond the original range set by ߠ. Instead, clusters of points near each of the original points were randomly selected, and the average value of ‫ ݎ‬was set as the final value for the gene. Subsequently, 25 points were selected, and the object was fabricated according to the specification shown in Figure 17. The red line is “inlet” where a wind of 5݉/‫ ݏ‬blows in, and it

Final version of Analysis System The genetic operation consists of selection, crossover, and mutation. Selection extracts a single gene with the probability proportional to its fitness value (Roulette algorithm was used). In this case, each gene was selected according to ߱଴ଶ . The process is illustrated in Figure 18.

Figure 18. Selected genes: ‫݌‬ଵ . ‫݌‬ଶ Crossover mixes two genes, generating a new individual. If the intersecting points existed between ‫݌‬ଵ and ‫݌‬ଶ , two genes were combined at the first intersecting point. If the two genes do not intersect, a ߠ was arbitrarily chosen to mix the two sets of points based on it. Figure 19 shows the process, and new progeny ݂ଵ was born: the yellow curve.

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Figure 19. After the crossover Mutation gives genetic diversity to the new generation, avoiding locally optimal solutions. A gene to be mutated was selected randomly and ‫ ݎ‬of each point was changed based on ICDF: inverse cumulative distribution function. A number was selected randomly between 0 to 1, and ‫ ݎ‬was differed by the corresponding value of ICDF, changing ݂ଵ to ݂ଵᇱ . 20 genes were generated, forming a next generation.

Result And Discussion

Figure 20. Mutation of ݂ଵ

First generation Number 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Mass (݇݃) 20.62 20.92 21.02 22.05 20.34 21.20 21.01 21.56 20.74 22.30 20.57 20.47 21.67 20.69 21.17 22.19 20.92 21.19 20.65 20.59

߱଴ (‫݀ܽݎ‬/‫)ݏ‬ Moment of Inertia (݇݃ × ݉ଶ ) 0.3910 42.51 0.4027 48.63 0.4122 33.92 0.4259 36.10 0.3885 49.21 0.3954 40.64 0.4165 21.95 0.4247 21.15 0.3928 49.94 0.4328 21.87 0.4022 25.63 0.3968 58.54 0.4001 45.53 0.3959 36.88 0.4269 28.57 0.4380 30.56 0.4027 32.24 0.4236 25.45 0.3916 43.59 0.4073 34.27 Table 1. Results of the first generation

fitness 1807 2365 1151 1303 2422 1652 482.0 447.2 2494 478.1 656.9 3427 2073 1360 816.5 933.9 1040 647.9 1900 1174

Second generation Number 0 1 2 3 4

Mass (݇݃) 20.02 20.64 20.65 20.47 20.34

Moment of Inertia (݇݃ × ݉ଶ ) 0.3723 0.4024 0.3922 0.3968 0.3885

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߱଴ (‫݀ܽݎ‬/‫)ݏ‬ 61.39 34.89 44.47 27.04 34.01

fitness 3769 1217 1977 731.3 1156

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

20.62 22.05 21.15 22.19 20.92 20.64 20.56 20.62 22.30 20.47 20.62 20.64 20.74 20.59 21.65

0.3910 0.4257 0.4255 0.4380 0.4027 0.4024 0.4032 0.3910 0.4326 0.3968 0.3910 0.4024 0.3928 0.3881 0.3977 Table 2. Results of the second generation

42.67 41.92 46.16 67.37 68.40 28.73 40.50 40.11 30.06 59.20 38.40 28.77 35.58

1820 1757 2131 4529 4679 825.4 1640 1608 903.4 3505 1475 827.7 1266

42.74

1827

Figure 21. ߱଴ distribution of the two generations

Discussion Due to temporal limitation, only the two generations had been simulated. Overall, ߱଴ distribution had shifted with enhanced output coefficients. Though iterations were insufficient, rapid changes were not shown: The initialization process already enhanced the whole generation, which might have saved time for meaningless generations full of center-blocked blades.

Conclusion A blade of a Savonius type with a large output coefficient must have a permeable center area so that air can flow through smoothly. Otherwise, the angular velocity undergoes damped vibration, reaching a stationary state. In addition, the curve must be smooth enough to avoid the floating-point exception, and the fewer the number of points with large curvature, the larger the converging value of angular velocity. When generating the first generation, fitness value must be prior to genetic diversity, in order to shorten the process. Comparing Tables 1 and 2, the algorithm seemed to work properly because the overall fitness has increased; however, if the final convergence value is very large, only the small change was visible in the initial analysis stage, and it was unknown which of the two cases that the increments corresponded to. Another possibility was that the initialization was well designed so that primary blades were already close to the optimal solution. Therefore, more iterations were required in order to see a proper trend. It was predicted that the degree of curvature or the orientation of the curve was expected to affect, and the ideal shape of the blade was a semicircular shape, which has none of the points with

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an obtuse angle, along with tolerable maximum curvature. With additional analyses, it was shown that anticipating ߱଴ with the trend line was appropriate. A few genes were simulated with the initial condition of ߱ = ߱଴ , and the graph showed that the angular velocity was consistent: it already converged, and the anticipation was precise.

Figure 22. ߱ – ‫ ݐ‬graph of a gene with ߱ = ߱଴ as an initial condition Designing initialization and the whole system took up too much time so only two generations were made and analyzed. With further iterations, the generation might apparently progress toward an optimized solution. Also, Ansys itself had restrictions in that 3D simulations took too long to analyze, and the helical-shaped blades were excluded from the simulation. With better simulating programs, variations in the shape of the blade could be applied to the system. Furthermore, environmental parameters could be modified, such as setting wind speed as a function of time.

References [1] Yun, Dae-Jhoong & Lee, Young-Tae & Yang, Hyun-Bong & Lim, Heechang. (2013). Development Study on Vertical Axis Helical Savonius Wind Turbine. Journal of the Korea Society For Power System Engineering. 17. 10.9726/kspse.2013.17.2.005. [2] Deok-Hun Kang, Won-Sik Shin, Jang-Ho Lee.(2014).Experimental study on the performance of urban small vertical wind turbine with different types.The KSFM Journal of Fluid Machinery,17(6),6468. [3] Dan Zhao, Nuomin Han, Ernest S. C. Goh, John Edward Cater, Arne Reinecke (2019), Wind Turbines and Aerodynamics Energy Harvesters. [4] Wenehenubun, F. & Saputra, A. & Sutanto, H. An experimental study on the performance of Savonius wind turbines related with the number of blades. Energy Procedia 68, 297-304 (2015). [5] Yong-Du Jun, Sang-Yeon Bae.(2015).Domestic Small Wind Turbine Power Generation - Way to Improve its Efficiency. Korean Journal of Air-Conditiong and Refrigeration Engineering,(),1067-1069. [6] Soo-Yong Cho, Chae Whan Rim, Sang-Kyu Choi, Jin-Gyun Kim, Chong-Hyun Cho.(2017).Utilization of 2.5-D CFD on the Performance Prediction of Vertical Axis Wind Turbine.New & Renewable Energy,13(1),4-16.

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Study on Enhancing the Accuracy and Sensitivity of Identifying Parasites Using an Object Detection Model Author 1

Full Name

Seo, Brendan

Wissahickon High School

(Last Name, First Name)

School Name

ABSTRACT: Parasitic infections constitute a significant global public health issue, and identifying the species of parasites in a sample is essential to resolve or prevent the problems caused by parasites. However, the current studies on parasite identification need further discussions for further development. For example, existing screening methods performed at the Sokoine University of Agriculture are based on manual microscopic examination, prone to human error, and often struggle to provide sufficient volumetric throughput and sensitivity. Here we demonstrate the capabilities of the deep learningbased object detection model, Fast Rcnv3, trained with 6,513 microscopic images that the International Parasite Resource Bank has produced. This model differentiated parasite eggs of 6 species within the 726 microscopic images with an accuracy of 93.84% and a sensitivity of 97.54%. This unique model can potentially be applied for sensitive and timely diagnosis of neglected tropical diseases caused by parasitic infections in developing countries.

Keywords: Parasite Identification, Object Detection, Convolutional Neural Networks (CNNs)

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1. Introduction Most countries have been suffering from parasitic diseases, and numerous species of parasites negatively affect human health and the global population. Intestinal parasitic infection causes several morbidities, such as diarrhea, malnutrition, digestive disorders, and anemia, and it is common in tropical countries such as Tanzania. Common ways to diagnose parasitic infection and identify parasite are blood tests, fecal exams, and endoscopy [1]. However, these methods cannot be effectively used in some countries because there are insufficient clinicians to give medical treatment and inaccurate results from human mistakes. This study is conducted to investigate the novel method of identifying parasite egg species with modern AI (Artificial Intelligence) technology.

Figure 1: Parasite Resource Education Training Seminar at Sokoine University, Tanzania I recently visited Tanzania for a student internship program on identifying parasite eggs at Sokoine University under the collaboration with International Parasite Resource Bank, and I was curious about productive ways to distinguish the species of parasites. It is difficult to identify the species of parasites and count the number of eggs on the glass slide. Thus, I noticed it would be more efficient if AI detection programs were applied during the process of parasite identification. Since AI detection is designed to increase performance efficiency [2], applying it to identify parasite eggs on the digital image is optimal approach to enhance the efficiency and efficacy of parasite identification. Among AI frameworks, TensorFlow is one of the most effective frameworks can be applied to parasite egg identification. TensorFlow supports object detection models that can identify which of a known set of objects might be present and provide information about their positions within the image [3]. The object detection algorithm can find the number of eggs and their locations, and researchers can use this information to reduce the time and effort that required for parasite identification. We experimented to solve the problem of identifying parasite eggs with the unaided eye by using object detection algorithm to identify sample images of six species of parasite eggs. The test result revealed that AI detection technology have a potential to support parasite identification and to assists scientists in studying parasites.

2. Current Parasite Recognition Technology and Method in Tanzania Tanzania has populations infected by different species of parasites. However unfortunately, Tanzania receives less support from most technologically advanced countries, so making solving parasite-related problems difficult. Tanzanian medical facilities need efficient ways to diagnose

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parasitic infection and identify parasites. This study demonstrates overall procedures of parasite recognition at Sokoine University, Tanzania. I used the blood collection method and floatation, sedimentation techniques for the experiment. Clinicians primarily use microscopes in their laboratories to observe and monitor the parasites under the glass slides. Then they summarize their results to identify the species of parasites or diseases. However, they usually study with limited assistance and equipment in their laboratories, making it hard to perform with high accuracy and sensitivity.

Figure 2: Collecting blood and fecal samples from a goat in Tanzania

2.1. Procedures for a sample collection from the small ruminants Since the small ruminants is one of the main sources of zoonotic parasitic infections in Tanzania, blood samples and fecal samples were collected from small ruminants. Being restrained, the head of the goat must be turned at a 30-degree angle to the side by holding the animal under its jaw to allow easy vein access. Then, the collector must figure out the vein's location by applying pressure with the thumb or fingers below the halfway point of the shaved area. The pressure would cause the vein to pop up and make it visible. The collection site is disinfected with three alternating scrubs of 70% alcohol and betadine (povidone-iodine). The insertion site was swabbed with alcohol to remove any bacteria that might have entered the area during the blood drawing. Before inserting the needle into the vein, the plunger must be pulled back to break the seal in a new syringe, and then the plunger would be depressed completely to express any air drawn into the syringe. The needle can be inserted into the vein using a 6-cc syringe, 20-gauge by one-inch or less needle, and vacutainer. The needle must be gently moved until blood is easily pulled back into the syringe. Once the sample has been obtained, pressure from the vein and needle must be removed. Blood flow must be stopped by applying firm pressure on the collection site with sterile gauze to achieve hemostasis.

2.2. Blood samples processing Blood smears were conducted in thick and thin layers prepared on the glass. A drop of blood was drawn onto the clean slide. A clean spreader slide, held at a 45° angle, toward the drop of blood on the specimen slide. After the blood spreads along the entire width of the spreader slide, a tilted slide was pushed forward rapidly and smoothly while holding the spreader slide at the same angle. A drop of blood was drawn onto the glass slide for a thick blood smear. Using the corner of a clean slide, a drop of blood was spread in a circle move on the slide. The drop was spread to the size of a dime (diameter 1-2 cm). After the thin and thick films were completely dry before staining, they

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were Fixed with Ethanol (absolute) and let dry completely before staining. Fresh whole blood was stored in anticoagulants (EDTA, sodium citrate, ACD, or heparin).

2.3 Fecal sample collection Fecal samples are directly drawn from the rectum. It is both practical and hygienic to take a fecal sample per rectum with a plastic glove. When a sufficient quantity of feces has been collected, the glove must be turned inside out and served as a container. After carefully tied and correctly labeled with all the necessary data, the sample must be preserved with 70% ethanol and 10% formalin.

2.4 Fecal sample processing The sedimentation and flotation method are common for processing fecal samples in order to detect parasites within the sample. These methods allow for detecting parasitic elements such as eggs, larvae, oocysts, and cysts. And following steps were performed by the doctors and scholars at Sokoine University of Agriculture, Tanzania. (a)

(b)

(c)

(d)

(e)

(f)

Figure 3 (a): fecal samples were homogenized in the collection tube using a disposable spatula; (b) The suspension was strained through a fine sieve; (c) The filtrate was stored in a tube; (d) The mixture was centrifuged for 10 minutes at 35000rpm. The ring of floating detritus and then the

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formalin was decanted. The sedimentation process was repeated more than twice to clarify the sediment; (e) microscopic examination of the parasites’ egg; (f) Bench aid for clarification of shape and size of parasite eggs likely to be observed from the fecal samples.

3. Parasitic Egg Recognition Using AI Technology 3.1 Summary of vision recognition by using AI detection Vision recognition can be used in parasite specie identification due to its ability to detect multiple objects in an image with the program with object detection algorithms. AI detection system allows a program to automatically recognize the elements in the sample, which means that scientists do not have to observe the total sample by themselves, and it also helps to analyze and monitor large amounts of microscopic images accurately and quickly [4]. However, the level of detection varies depending on the modality of the model.

3.2 Comparison of classification, segmentation, and object detection

Figure 4: Types of object recognition tasks.

3.2.1 Classification Classification is a process of assigning labels to images according to their classes [5]. It is a straightforward method and requires less time than others, but it has some limitations for using advanced research. It faces many challenges that make it less effective than other methods: intraclass variation and scale variation. First, intra-class variation makes detecting different elements in the same class difficult, so even if the different parasites are in the image, the result will only show that the object's class is a parasite. Next is scale variation, a common problem that the program cannot recognize the different sizes of the same objects.

3.2.2 Segmentation Segmentation finds the locations of an object by using the actual edge, not a bounding box with pulling layers, unlike object detection. Image segmentation is also a challenging problem that requires dealing with complex and diverse scenes, varying illumination, occlusion, noise, and scale [6].

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3.2.3 Object detection Object detection can detect multiple objects in an image, and it uses a bounding box to figure out the location of the objects. I used object detection in this study because it is the most efficient way for parasite identification. In this study, I especially used transfer learning method to demonstrate parasite identification, and I applied the backbone model with the one of the successful object detection models, Faster R-CNN. Compared tasks

Classification

Detection

Segmentation

Multiple object detection

impossible

possible

Visualization level

poor

high

very high

Data training production cost

high

very high

high

poor

Identification speed

Table 1: Comparison of pros and cons between classification, detection, and segmentation models

3.3 Pipeline of Faster R-CNN

Figure 5: Pipeline of Faster R-CNN Faster R-CNN allows scientists to detect objects in the proposed regions, requiring RPN (Region Proposal Network) to generate them [7]. It consists of a CNN with the part that allows the region proposal layer to make proposed regions. Non-Maximum Suppression (NMS) takes the list of proposals sorted by score and does not generate results that show overlapping over the same object [8]. Spatial pyramid pooling networks (SPP-Nets) extract a single feature map from the entire image only once and pool the features of region proposals for the image, which allows the network to

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perform faster than R-CNN [9]. While running an R-CNN on 2000 region proposals from an image individually, Faster R-CNN needs only once to pool the features of all 2000 proposals.

3.4 Training and test results The number of 7,248 microscopic images of 6 species of parasites (Toxascaris leonine, Toxascaris canis, ancylostoma caninum, Clonorchis sinensis, Toxocara cati, Spirometra decipiens) and labeled annotation data were provided by International Parasite Resource Bank. Among the images, 90% were used for training and validation, and 10% for testing the model. Parasite

Total

Training & Validation

Test

Toxascaris leonine

1205

1084

121

Toxascaris canis

1205

1084

121

ancylostoma caninum

1205

1084

121

Clonorchis sinensis

1204

1083

121

Toxocara cati

1210

1089

121

Spirometra decipiens Total Sum

1210 7,248

1089 6,522

121 726

Table 2: The number of microscopic images per parasite species used for training, validation and testing of the model During the training and validation, training set and validation set were split with the ratio of 80:20 respectively and randomly divided within the 90% of the total images. The batch size was set to 1, epoch was formed to 10, and learning rate was set to 0.001. As a result of training and validation the Mean Average Precision (mAP) were converged around 92.54% under the threshold of 0.75 IoU (Intersection over Union) and 98.22% under the threshold of 0.5 IoU.

Figure 6: Mean Average Precision (mAP) of the model during the training and validation with the threshold of IoU 0.5 and 0.75 respectively. Under the threshold of 0.6 IoU, the trained model has been tested with 726 images (the 10% of

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total images) which were not used in the training and validation process. As a result of the testing, the confusion matrix was derived as Table 3. The result showed an accuracy of 93.84% and a sensitivity of 97.54% for 6 species of parasites.

Prediction

Positive

Negative

Positive

914

Negative

Actual value

Table 3 Confusion Matrix of the trained model with the threshold of 0.6 IoU

Figure 7: Example of object detection of the trained model within the microscopic image

4. Conclusion The study discussed Tanzania’s issues with parasitic diseases and the current parasite identification technology being used at Sokoine University. I collected samples and used the conventional concentration method to observe parasite eggs within the sample, and it was difficult and took several minutes to detect the species of parasites. This study’s main expectation was that using an object detection algorithm for parasite egg identification would result in high accuracy and sensitivity. The result showed an accuracy of 93.84% and a sensitivity of 97.54% for six parasite species, which showed potential for the model to be

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used for supporting parasite identification. Most regions in Tanzania do not have sufficient medical facilities so that diseases can spread rapidly throughout the country. The government asks medical experts to investigate unidentified conditions, but many scholars in Tanzania do not try to prevent or find the primary reason for the spreading of diseases [10]. AI detection is necessary for improving the efficiency and efficacy of diagnosis and detection of parasites and medical treatment. If scientists can implement AI detection techniques, it would be beneficial for them in the case of early detection of parasitic infections. Suppose they continue to study and use modern AI detection technology for parasite identification, their effort will contribute highly to resolve the problems caused by parasites.

5. Discussion The experiment was successfully performed, but there needs to be further study to highlight the advantages of the algorithm. The study still needs to be investigated by more scientists because the test result should be generalized to use in actual experiments. Lastly, scientists must study sufficient amounts for precise application in the future. There should be more investigation into major elements that affect the results, such as backbone model and hyperparameter. The backbone model is a primary feature extractor responsible for input data features and crucial for the performance and quality of neural networks (CNNs) [11]. Ideal backbone models can improve the generalization of a model and affect the speed of CNNs. However, poor models cause overfitting, and highly complex backbones with multiple layers require longer training times and slower inference. It is essential to choose the proper backbone models for each algorithm based on the type of data, available computational resources, and the complexity of the task for efficient performance. Hyperparameter optimization is necessary to find the loss and accuracy of a function and needs to be investigated to compare the difference between training models [12]. Overall, further investigation will lead to the development of parasite studies more innovatively.

Acknowledgment This research would not have been successful without my advisor, Dr. Baraka Ndosi, of the International Parasite Resource Bank. I would like to express my sincere gratitude for his advice and data, and also for other experiment participants at Sokoine University.

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References [1] “Diagnosis of Parasitic Diseases,” CDC (Centers for Disease Control and Prevention), 2023. [2] Stuart A. Thompson. “How Easy Is It to Fool A.I.-Detection Tools?” The New York Times, 2023. [3] “Object detection: TensorFlow Lite.” TensorFlow, 2023. [4] Bobbi Pritt, M.D. “Use of Artificial Intelligence and Digital Slide Scanning for Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens.” Mayo Clinic Laboratories, 2023. [5] Abdur Rafaey. “Main Challenges in Image Classification.” Towardsdatascience, 2020. [6] “What are some of the latest trends and challenges in image segmentation with neural networks?” Linkedin, 2023. [7] Ahmed Fawzy Gad. “Faster R-CNN Explained for Object Detection Tasks.” Paperspace, 2020. [8] Javier Rey. “Faster R-CNN: Down the rabbit hole of modern object detection.” Tryolabs, 2018. [9] Shilpa Ananth. “Fast R-CNN for object detection.” Towardsdatascience, 2019. [10] “Tanzania: Authorities investigate mysterious illness that killed five.” Africanews, 2023. [11] “What Is the Backbone in a Neural Network?” Saturn Cloud, 2023. [12] Pier Paolo Ippolito. “Hyperparameters Optimization” Towardsdatascience, 2019.

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Applying Nano Drug Delivery System for Respiratory Diseases Author 1

Full Name

Song, Minkyung (Katie)

BC Collegiate

(Last Name, First Name)

School Name

ABSTRACT: Nanotechnology-based drug delivery systems are a rapidly emerging field in which particles in the nanoscale range are used to diagnose, treat, or prevent diseases (Mayazen et al., 2022). As drug carriers, nanoparticles can increase drug stability, bioavailability, or duration of action by preventing early degradation or metabolism of drug molecules. They can also deliver drugs site-specific that, unlike conventional therapeutic agents, does not disrupt non-target cells and reduce side effects (Mitchell et al., 2020). This paper will suggest how the application of nanotechnology in drug delivery will improve current treatment methods and propose potential nano-based drug delivery systems for the medication for three respiratory diseases: lung cancer, asthma, and idiopathic pulmonary fibrosis. Biological, chemical, and physiological aspects, including pathophysiological conditions of diseases, biochemical properties of drug molecules, pharmacokinetics and pharmacodynamics of conventional drugs, types of nanoparticles, administration method, and disease targeting type, are considered to suggest the optimal nanomedicine for each respiratory disease. By applying a nano-drug delivery system on FDA-proven drugs, the efficacy of conventional medications would dramatically increase with fewer side effects and doses and advanced disease treatment systems.

KEYWORDS: Nanotechnology, Drug delivery system, Nanomedicine, Respiratory disease

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BACKGROUND Chronic lung diseases such as asthma, tuberculosis, COPD, and lung cancer are among the leading causes of death worldwide, accounting for over 3 million deaths yearly. As such, the advent of new therapeutic techniques and improving current strategies have been the subject of extensive research to address the situation. Advances in nanotechnology, in particular, for disease diagnosis and treatment, have received significant attention in recent years. It is widely presumed that the application of nanotechnology in medical fields (referred to as nanomedicine) will revolutionize how we practice medicine. This paper will discuss how nanoparticles can enhance the delivery of drugs in patients with respiratory diseases and address the limitations of conventional pharmaceutical treatments.

Nanotechnology manipulates matter on an atomic or molecular scale to produce devices, structures, and materials for industrial purposes. It is a promising scientific field that promotes advances in various sectors, including medicine, consumer products, energy, and manufacturing ("Nanotechnology," 2023). Nanomaterials are sized from 1 to 100 nanometers (nm), a microscopic unit equal to 10-9 meters. Changing the size of a particle at this scale can alter chemical and physical properties such as the melting point, fluorescence, chemical reactivity, solubility, and magnetic permeability. Developing and utilizing these properties of nanoparticles is at the heart of this new technology.

&RQYHQWLRQDO PHGLFLQH SULPDULO\ QDWXUDO SURGXFWV VL]HG WR ȝP DQG GUXJ GHOLYHU\ DUH DVVRFLDWHG with major limitations, including poor bioavailability, in vivo instability, poor absorption in the body, low target specificity, and probable side effects (Patra et al.). Nanotechnology is a potential tool to address these issues, increasing targeting accuracy and drug efficacy. Nano-based drug delivery system, abbreviated as nano-DDS, is the formulation of a device that allows therapeutic substances to selectively reach its disease site without exposure to non-target organs ("Modification of Drug Release," 2015). Indeed, nanostructures remain in the blood for a prolonged duration and allow the release of drugs in accordance with the specified dose. These structures are small enough to facilitate easy uptake of the drugs by cells, compared to conventional drug particles that are much larger. Hence, they can directly treat the abnormal cells with increased precision and reduce adverse effects.

PATHOPHYSIOLOGY OF RESPIRATORY DISEASES Lung cancer, asthma, and pulmonary fibrosis are three of the most prevalent and fatal respiratory diseases. Lung cancer develops when abnormal cells in the lung proliferate at an uncontrollable rate. Over time, they form solid tumors that damage respiratory functions and interfere with basic breathing processes. Moreover, the tumors may metastasize, spreading into other body parts. Lung cancer occurs due to genetic damage in the airways of the respiratory systems, 85 percent of which is caused by smoking and the rest caused by inhaling harmful chemicals or genetic mutations. Although the mortality rate differs based on the type of extent of metastasis, lung cancer alone accounted for more than 2.2 million deaths in 2020 ("Lung Cancer Statistics," 2022).

Asthma is defined as the inflammation and narrowing of the lung's airways. Usually beginning in childhood, the severity of the condition can vary from moderate to life-threatening ("What Is Asthma?," 2022). It begins with exposure to a specific irritant or allergen, such as cold air or pollen. Bronchial hypersensitivity leads to inflammation and increased mucus production, and airflow obstruction. The WHO reported that approximately 262 million people had asthma worldwide, and 455,000 died in 2019 ("Asthma").

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Pulmonary fibrosis is a chronic, progressive lung disease characterized by the scarring of lung tissue. An idiopathic injury in the alveolar epithelium causes type 1 alveolar cells to release TGF-beta. Consequently, type 2 alveolar cells transform into myofibroblasts, which in turn secrete specific collagen to increase the structural strength of the lungs. As type 2 alveolar cells proliferate rapidly, the interstitial layer between capillaries and alveoli thickens, inhibiting gas exchange. Symptoms of pulmonary fibrosis include shortness of breath, dry coughs, and nail clubbing. The average life expectancy of fibrosis patients is two to five years after diagnosis. There is currently no cure for idiopathic pulmonary fibrosis, but only treatments for relieving symptoms and slowing down its progression.

KEY CONSIDERATIONS FOR THE DEVELOPMENT OF NANOMEDICINE Numerous aspects of medicine and disease are to be considered before designing the right drug treatment for the specified condition. The key considerations are the physiology of the target disease and the drug, the pharmacokinetics and pharmacodynamics of the drug molecules, the type of drug carrier used, and the method of administration.

Physiology of Target Diseases and Drugs Understanding the pathophysiology to its full extent is crucial since therapeutics aim to hinder the progress of the disease and relieve the symptoms. Different pathological conditions all call for specific drugs that interact with specific organ functions. Another critical factor is the biochemical properties of drug molecules, such as hydrophobicity, degradability, and solubility. For example, hydrophilic drugs can freely dissolve into the blood, but large hydrophilic macromolecules cannot readily diffuse into the cell membrane. Hydrophobic drugs travel within the blood by being bound to a protein. Highly degradable drugs do not go through early degradation and have greater bioavailability.

Pharmacokinetics of Drug Molecules The pharmacokinetics of drug molecules is concerned with how the body interacts with the administered medication for the duration of exposure. The three critical aspects of pharmacokinetics are bioavailability, protein binding, and half-life. Bioavailability is the extent and rate at which the drug enters the blood and accesses the disease site. This determines how much of the drug administered is actually absorbed and exerts its therapeutic effect. Protein binding is the degree to which the substances are attached to the proteins in the bloodstream. The less bound the drug is, the more efficiently it can diffuse through the membranes of target cells. Depending on the drug's affinity for proteins, a portion of it is protein-bound; the remaining unbound portion interacts with the target cells. It also highly affects the drug's biological half-life: the time it takes for the drug concentration in the blood plasma to be reduced by 50 percent. Medicines with a long half-life can maintain therapeutic levels in the body for a prolonged period. Short half-life medication can start working more quickly after administration and have a lower risk of drug accumulation over time. The ideal half-life of an oral drug administered daily is 12 to 48 hours (Smith et al., 2017).

Pharmacodynamics of Drug Molecules The drugs' biochemical and physiological effects (termed pharmacodynamics) are an essential feature of drug delivery. Drugs can modulate enzyme activity by enhancing or inhibiting targeted processes. Also, drugs may interfere with the ligand-protein binding to the receptor to disrupt signaling processes. If the drug is an antagonist, it prevents the ligand from binding to the receptor, blocking the response

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that would have occurred if the receptor were activated. If the drug is an agonist, it directly activates the receptor and triggers a response similar to the natural ligand that usually binds to the receptor.

Drugs target disease sites either actively or passively. Passive targeting depends on the natural pathophysiological features of the target site to interact with the drug. It is generally useful for conditions with inflammation, such as solid tumors. Conversely, active targeting involves ligands attached to drug carriers, which can identify specific receptors on the surface of target cells. It is generally appropriate for delivering drugs for specific types of cells, such as cancerous tissues.

Types of Nanoparticles and Administration Method Some of the most commonly employed nanomaterials for drug delivery are groups of organic nanoparticles known as liposomes, micelles, quantum dots, and polymeric nanoparticles shown in Figure 1.

Figure 1. Four types of nano drug carriers.

Liposomes are vesicles of spherical form composed of a phospholipid bilayer and a hydrophilic aqueous core. Liposomes can engulf both hydrophilic and hydrophobic drugs (Patra et al., 2018) and effectively maintain bioavailability as the hydrophobic layer protects the drugs from premature release. Liposomes minimize targeted therapies and toxic side effects, enhance the bioavailability of hydrophobic antitumor drugs and drug solubility, and increase the blood circulation time of the drug molecules.

Polymeric micelles are made of amphiphilic block copolymers that together form a core-shell structure. Their primary components are the hydrophobic core, which renders micelles suitable for delivering hydrophobic drugs, and a hydrophilic outer shell, which allows for high bioavailability and avoids premature drug release (Croy & Kwon, 2006).

Quantum dots are long semiconductor crystalline nanoparticles with unique electronic properties. By increasing the surface area for absorption, quantum dots enhance drug bioavailability and dissolution (Jacak L. et al., 2013). They can work with targeting ligands such as peptides to recognize and bind to specific cells or tissues.

Polymeric nanoparticles are composed of natural biopolymers such as peptides or polysaccharides. They are decomposable, metabolizable, and easy to functionalize due to their high affinity to specific

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drugs and other targeting ligands (Patra et al., 2018).

Drugs can be administered via intravenous injection, oral intake, or inhalation. Intravenous injection results in the greatest bioavailability of 100 percent, while oral intake is most likely to prevent the early breakdown of compounds.

NANOMEDICINE FOR RESPIRATORY DISEASES Encapsulating drugs in nanoparticles can provide a safe and efficacious platform for targeted drug delivery for the following diseases.

Lung Cancer Lung cancer develops when abnormal cells grow at an extremely rapid rate and form tumors that damage or disrupt basic respiratory functions. Several known chemotherapeutic treatments for lung cancer are cisplatin and carboplatin. Their mechanisms are similar in that they facilitate slowing down cell proliferation by interfering binding of cyanine and guanine in DNA replication (Pison. et al., 2006). An injection into the vein administers both and may trigger side effects like bone marrow suppression as they are also distributed to healthy human tissue. However, considerably fewer adverse effects arise from carboplatin, such as reduced nephrotoxicity.

Figure 2. Nanomedicine for lung cancer.

The use of nanomedicine can bring about remarkable improvements in the delivery and therapeutic effects of carboplatin. Due to the hydrophilic nature of carboplatin, the aqueous core of the liposome would be most appropriate for encapsulating the anti-lung cancer drug. The surrounding hydrophobic shell, as shown in Figure 2, prevents the drug molecules from being released before exposure and thus increases bioavailability and half-life potentially up to ten-fold (Liu et al., 2022). Active targeting would be more advantageous than passive targeting as drugs can directly bind to tumor cells while preventing any damage to healthy tissues. Active targeting requires the coupling of a specific ligand in the target cell and its receptor in the drug carrier. A potential biomarker of lung cancer cells is the Programmed Death Ligand 1 (PD-L1), a protein located on the surface of certain cells, including tumor cells. If its receptor PD-1 can be embedded in liposomes, the nano-drug carrier would be able to specifically interact and get rid of cancerous cells in the lungs.

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Asthma Asthma is characterized by the inflammation and narrowing of the airways that lead to chest tightness and breathlessness. Some of the medications for asthma on the market are albuterol and budesonide. Albuterol works by causing the relaxation of bronchial smooth muscles, resulting in improved airflow of the lungs. It is classified as a beta-2 adrenergic agonist and has a half-life of 3.8 to 6 hours. Budesonide is a corticosteroid medication that is usually administered via inhalation for asthma treatment. It reduces the inflammation in the airways and prevents further emergence of asthma symptoms. With a half-life of 2 to 3.6 hours, budesonide may have side effects such as nose irritation, dryness in the mouth, and swelling of the face.

Figure 3. Nanomedicine for asthma. Using nano-drug carriers can largely improve the delivery system by enhancing the half-life and bioavailability by preventing the drug from degrading in the intestinal duct environment before entering the circulatory system. If the budesonide is administered, the polymeric micelle, as shown in Figure 3, would be appropriate for the purpose of increasing bioavailability. Also, passive targeting would be more favorable in this case as this strategy is generally useful for targeting inflammatory conditions. The drug would be administered via pills because it would facilitate the prevention of the disease, not only the short-term relief of the symptoms. As for the dosage, the budesonide pills would be taken originally at 9 mg/day, but with nano-drug delivery, it could be reduced to 5 mg/day.

Pulmonary Fibrosis Pulmonary fibrosis is an idiopathic disease that involves the scarring of lung tissues. Although there are no currently available treatments for this condition, certain drugs can slow down the progress of fibrosis. For instance, nintedanib is a small-molecule tyrosine kinase inhibitor that targets fibroblast growth factor receptors. When tyrosine-kinase is inhibited, cellular metabolism, proliferation, and growth of immune cells can be suppressed. By inactivating the excess fibrotic activities, nintedanib can slow down the production of platelet-derived growth factor, fibroblast growth factor, TGF-ß, VEGF, and excess ECM fibrin that lead to fibrosis (Mirshafiey et al., 2014). The drug is administered orally and has a considerably low bioavailability of 4.7 percent. Its half-life lasts for 10 to 15 hours.

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Figure 4. Nanomedicine for pulmonary fibrosis.

A potentially beneficial nanocarrier for this disease is the lipoprotein, a protein nanoparticle with high biodegradability, non-immunogenicity, long circulation half-life, and the ability to target naturally. Figure 4 shows a diagram of the nintedanib encapsulated in the protein nanoparticle. Administering nintedanib by inhalation would enable direct exposure of the medicine to the lung tissue and prevent the drug from entering the intestinal tract environment and causing early degradation. Passive targeting would enhance the interaction between nintedanib and tyrosine-kinase since the localization of drug molecules among fibrotic regions would be more effective in slowing down fibrosis rather than specifically targeting single cells. The drug carrier would also compensate for the low bioavailability of nintedanib and could further increase its half-life by up to 72 hours.

CONCLUSION AND DISCUSSION As research has shown so far, nanotechnology is causing a considerable stir not only in the science and technology world as a whole but also in the medical field. In particular, in the case of the respiratory system, the tissue is microscopic and quite complexly connected, making it difficult for the drug to reach a location that requires accurate treatment (Luo M. et al., 2021). Nonetheless, nanoparticles have unique properties that help them overcome such limitations, precisely delivering drugs to specific sites while maximizing bioavailability and minimizing toxicity. Nanotechnology is revolutionizing not only the management of lung diseases but an extensive scope of illnesses and medical applications. However, to realize the full potential of nano-based drug delivery systems, unexpected side effects and challenges in the implementation process are problems that must be addressed. Although such concerns will be the subject of further inquiry in the future, nanomedicine has already begun to create major breakthroughs in biomedical fields. Nano-based drug delivery is anticipated to transform the treatment landscape and pave the way for the emergence of safer, more effective therapies for various diseases.

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REFERENCES 1. Centers for Disease Control and Prevention. (2023, June 14). Nanotechnology. Centers for Disease Control and Prevention. https://www.cdc.gov/niosh/topics/nanotech/default.html#:~:text=Nanotechnology%20is%20t he%20manipulation%20of,energy%2C%20materials%2C%20and%20manufacturing. 2. Patra, J. K., Das, G., Fraceto, L. F., Campos, E. V., Rodriguez-Torres, M. del, Acosta-Torres, L. S., Diaz-Torres, L. A., Grillo, R., Swamy, M. K., Sharma, S., Habtemariam, S., & Shin, H.-S. (2018). Nano-based drug delivery systems: Recent developments and future prospects. Journal of Nanobiotechnology, 16(1). https://doi.org/10.1186/s12951-018-0392-8 3. Hong, S., Choi, D. W., Kim, H. N., Park, C. G., Lee, W., & Park, H. H. (2020, June 29). Protein-based nanoparticles as drug delivery systems. Pharmaceutics. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7407889/ 4. Mazayen, Z. M., Ghoneim, A. M., Elbatanony, R. S., Basalious, E. B., & Bendas, E. R. (2022, January 15). Pharmaceutical nanotechnology: from the bench to the market. SpringerOpen. https://fjps.springeropen.com/articles/10.1186/s43094-022-00400-0 5. Lung cancer statistics: World cancer research fund international. WCRF International. (2022, April 14). https://www.wcrf.org/cancer-trends/lung-cancer-statistics/ 6. U.S. Department of Health and Human Services. (n.d.). What is asthma?. National Heart Lung and Blood Institute. https://www.nhlbi.nih.gov/health/asthma 7. Centers for Disease Control and Prevention. (2023, June 30). Asthma. Centers for Disease Control and Prevention. https://www.cdc.gov/nchs/fastats/asthma.htm 8. Smith, D., Di, L., Maurer, T & Beaumont, K. (2017). Relevance of half-life in drug design. Journal of medicinal chemistry. https://pubmed.ncbi.nlm.nih.gov/29112446/ 9. Croy, S. R., & Kwon, G. S. (2006). Polymeric micelles for drug delivery. PubMed. https://pubmed.ncbi.nlm.nih.gov/17168771/ 10. Jacak, L., Hawrylak, P., & Wojs, A. (2013). Quantum dots. Springer Science & Business Media. 11. Pison, U., Welte, T., Giersig, M., & Groneberg, D. A. (2006). Nanomedicine for respiratory diseases. European journal of pharmacology, 533(1-3), 341-350. 12. Wikimedia Foundation. (2023a, June 4). Cisplatin. Wikipedia. https://en.wikipedia.org/wiki/Cisplatin 13. Wikimedia Foundation. (2023b, May 28). Carboplatin. Wikipedia. https://en.wikipedia.org/wiki/Carboplatin 14. Liu, P., Chen, G., & Zhang, J. (2022). A review of liposomes as a drug delivery system: Current status of approved products, regulatory environments, and future perspectives. Molecules, 27(4), 1372. https://doi.org/10.3390/molecules27041372 15. Wikimedia Foundation. (2023e, July 12). Budesonide. Wikipedia. https://en.wikipedia.org/wiki/Budesonide 16. Wikimedia Foundation. (2023d, June 20). Nintedanib. Wikipedia. https://en.wikipedia.org/wiki/Nintedanib 17. Shukla, S. K., Nguyen, V., Goyal, M., & Gupta, V. (2022). Cationically modified inhalable nintedanib NIOSOMES: Enhancing ... Future Medicine. https://www.futuremedicine.com/doi/10.2217/nnm-2022-0045 18. Mirshafiey, A., Ghalamfarsa, G., Asghari, B., & Azizi, G. (2014, July). Receptor tyrosine kinase and tyrosine kinase inhibitors: New hope for success in multiple sclerosis therapy. Innovations in clinical neuroscience. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4204472/ 19. Luo, M. X., Hua, S., &amp; Shang, Q. Y. (2021). Application of nanotechnology in drug delivery systems for respiratory diseases. Molecular Medicine Reports, 23(5), 1-17. 20. Drug delivery system. Drug Delivery System - an overview | ScienceDirect Topics. (n.d.). https://www.sciencedirect.com/topics/nursing-and-health-professions/drug-delivery-system 21. Doroudian, M., MacLoughlin, R., Poynton, F., Prina-Mello, A., & Donnelly, S. C. (2019,

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October 1). Nanotechnology based therapeutics for lung disease. Thorax. https://thorax.bmj.com/content/74/10/965 22. Le, J. (2023, July 21). Drug bioavailability - clinical pharmacology. MSD Manual Professional Edition. https://www.msdmanuals.com/professional/clinicalpharmacology/pharmacokinetics/drug-bioavailability 23. YouTube. (2019). Pharmacodynamics - Part 1: How Drugs Act on the Body. YouTube. Retrieved August 4, 2023, from https://www.youtube.com/watch?v=PhfhMBO-w9Q. 24. YouTube. (2022). Liposomal Delivery Systems in Cancer Therapy - Creative Biolabs. YouTube. Retrieved August 4, 2023, from https://www.youtube.com/watch?v=OxSDfCXNxo8.

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The Investigation of Bacteria Species in Communal Cutlery Trays in High School Settings Author 1

Full Name

Yi, Chaekyoung

Singapore American School

(Last Name, First Name)

School Name

ABSTRACT: The purpose of this descriptive research is to investigate the bacteria species present in a communal source that many individuals are exposed to daily -- cutlery trays. In order to meet the goals of this research, the researcher obtained swab samples of various cutlery tray surfaces across two different cutlery trays at an international high school cafeteria. Then, the samples were cultured and microorganisms that exhibited bacterial characteristics were analysed using colony morphology to determine the species. Furthermore, one of the samples was analysed concurrently at an accredited laboratory to add credibility to the findings of this paper. The findings indicated that eight different bacterial species could be identified from the collected samples. The species include: S. aureus, E. coli, B. subtilis, P. fluorescens, Mycobacterium spp., Pseudomonas spp., S. marcescens, and E. cloacae. The bacteria species identified carry the potential of causing serious bacterial infections in humans. This study emphasizes the species of bacteria humans surround themselves with daily and sheds light on the need to investigate the bacterial contamination of communal sources such as cutlery trays to ensure the health of the consumers.

KEYWORDS: Bacteria, bacterial contamination, bacterial infections, colony morphology, cutlery trays, high school cafeteria

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INTRODUCTION School facilities often use cutlery trays or bins to conveniently distribute necessary cutleries to consumers, including students and faculty. Often, the cutlery trays are placed right before or after the cashier counter for consumers to access. As cutlery trays divide crockeries by type (e.g. spoons, forks, knives, chopsticks, etc.), consumers can easily identify and get a hold of the appropriate cutlery according to their meal of choice. However, the usage of communal cutlery bins may pose a problem for consumer health. Although cutlery bins are convenient for the mass distribution of crockeries in communal settings, a single consumer can be in contact with multiple pieces of cutlery at once. Unfortunately, “communityassociated sources are one such source that is significant in harbouring and [spreading] antibioticresistant microorganisms” (Zehra, 2020). Bacteria can attach to contacted surfaces, detach, and contaminate food as it transfers from different surfaces (Vogel et. al., 2007; Fuster-Valls et. al., 2008). As cutleries are directly introduced to the human body during food consumption, if contaminated by bacteria, they may increase the risk of various bacterial infections (Park et. al., 2014). Furthermore, in Singapore, in 2020, the total number of students and faculty at educational institutions, including Primary, Secondary, Junior College (JC), and Centralized Institutes (Pre-U), was 420,726 and 33,129 respectively (Ministry of Education Singapore, 2021). The large population of people exposed to this potential problem suggests that it would be beneficial to investigate the different bacteria present in the shared cutlery trays in school cafeterias. Therefore the question, “What bacteria species are present in the communal cutlery trays at an international school in Singapore?” arises.

LITERATURE REVIEW Past literature explored the prevalence of bacteria species in communal settings, specifically in restaurants and school settings, and the survival of bacteria on different surfaces. These literature can provide a comprehensive understanding of bacterial contamination in communal settings and identify areas for future research.

Bacterial Contamination in Restaurant Settings Bacterial infections from bacterial contamination is a noticeable source of public health concern worldwide. Restaurant settings are commonly studied to locate sites of bacterial contamination (Jeong, 2005; Gámez et. al., 2016). An examination of microorganisms in the facilities and utilities of restaurants by Jeong evaluated the hygiene of three Korean restaurants in Busan, South Korea (Jeong, 2005). According to this study, sources that are reused and shared among many customers were found to have high counts of bacteria (Jeong, 2005). For instance, table surfaces, cutlery trays, and water jugs were observed to have hundreds to thousands of bacteria (Jeong, 2005). On average, 2.56 million Escherichia coli (E. coli) were detected within the cutlery trays of three different Korean restaurants (Jeong, 2005). These findings affirm that cutleries within the cutlery trays can be contaminated by bacteria from the cutlery trays even after sanitation (Jeong, 2005). The study by Jeong further suggests that bacterial contamination and hygiene of cutlery trays require more attention (Jeong, 2005). Additionally, in a different study conducted by Gámez et. al., the researchers investigated the bacterial contamination of restaurant menus (Gámez et. al., 2016). The study identified restaurant menus shared between many customers as a potential source of bacterial contamination, with E. coli and Staphylococcus aureus (S. aureus) being the most commonly identified bacteria (Gámez et. al., 2016). While the findings of this study cannot be generalized to school cafeteria settings in Singapore, it suggests that commonly shared sources should be investigated with a focus on commonly observed

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bacteria such as S. aureus and E. coli.

Bacterial Contamination in School Settings School settings can also be a significant source of bacterial contamination, especially with students and faculty in close proximity within shared spaces such as cafeterias. Past studies have focused on investigating bacterial contamination in school settings (Jeong et. al., 2002). A study conducted across four elementary school food service operations in Busan, South Korea identified a great number of E. coli among the sampled sites, including school water fountains and kitchen utensils (Jeong et. al., 2002). However, researchers like Harrigan suggested that utensils that come in direct contact with foods should not have any E. coli bacteria (Harrigan, 1998). As these findings do not align with the hygiene standards that should be maintained in school settings, the researchers of the study on elementary school food service operations in South Korea suggested conducting regular microorganism evaluations to reduce bacterial contamination in school cafeteria settings (Jeong et. al., 2002). Accumulating research indicates that the most commonly observed bacteria in communal settings are E. coli and S. aureus (Jeong, 2005; Jeong et. al, 2002; Park et. al., 2014). E. coli is a bacteria commonly found in the intestinal tracts of the human body and its count is often used as a marker for faecal contamination (Senkbeil et. al., 2019). S. aureus is a bacteria commonly found on human skin and can easily develop as a pathogenic strain (Lowy, 1998). This literature review reveals that communal settings, such as school facilities and restaurants, and frequently shared resources can be sources of bacterial contamination. Therefore, it is reasonable to assume that communal cutlery trays at an international school in Singapore could also be a source of bacterial contamination.

Bacterial Survival on Stainless Steel Surfaces Stainless steel (SS) surfaces commonly form cutleries due to their reputation for being durable and convenient during sanitation practices. However, despite its reputation, SS surfaces can still harbour microorganisms and do not carry any antibacterial properties (Page et. al., 2009). For instance, according to a microbiological evaluation report of the facilities and utilities of Korean restaurants by Jeong, kitchen utensils made out of SS had microorganism contamination and were contaminated with a great number of bacteria (Jeong, 2005). One factor that affects bacteria' survival on SS surfaces is their roughness. With frequent usage, SS surfaces can be worn down with scratches and become rough. As noted in a study by Carpentier and Cerf, rough SS surfaces can facilitate bacterial attachment and growth (Carpentier et. al., 2011). Rough surface areas provide crevices for bacteria to attach to and challenge the cleaning and disinfection of SS surfaces (Carpentier et. al., 2011). Another factor that affects bacteria’ survival is the presence of organic materials on SS surfaces. For example, if organic materials like food particles or biofilm are present on SS surfaces, bacterial growth, and survival may be promoted as bacteria will gain nutrients and moisture from those materials (Boscher et al., 2016; Lopes et al., 2006). Unfortunately, both factors may be present in the communal cutleries and contribute to the survival and growth of bacteria as the cutleries are constantly reused and shared between a large population of people.

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Bacterial Survival on Plastic Surfaces Plastic surfaces are ubiquitous in many settings and are frequently used as a material to create cutlery trays. A number of recent studies have extensively investigated bacterial survival on plastic surfaces (Benoit et al., 2010). One factor that affects bacteria' survival on plastic surfaces is their roughness. Bacteria can easily adhere to rougher plastic surfaces that provide more attachment sites, ultimately facilitating bacteria colonization and growth (Benoit et al., 2010). Another factor that affects bacterial survival is the presence of nutrients from organic materials such as biofilms (Benoit et al., 2010). Bacterial growth and survival can be promoted with nutrients on plastic surfaces (Benoit et al., 2010). Plastic surfaces are commonly present in communal cutlery trays in school settings and may possess the identified factors relevant to the survival and growth of bacteria.

Purpose of Study Most communal settings such as schools use cutlery trays as convenient and effective measures of distributing necessary cutleries to consumers. However, such shared resources can ultimately culture different microorganisms and even harbour pathogens, facilitating bacterial infections (Zehra, 2020). It is clear that bacterial contamination is prominent in communal settings or sources (Gámez et. al., 2016). This calls for the need to inspect the bacteria species that are present in commonly shared resources in school settings. This literature review highlights the significance of examining bacterial species found in shared environments to understand the potential of bacterial contamination. While recent studies have focused on bacterial contamination in general school settings and kitchen facility settings, extensive research is required to investigate the different bacteria species present in specific communal sources used by school communities.

METHODS To appropriately answer the research question investigating bacteria species present in communal cutlery trays, a descriptive study design was incorporated. A qualitative method was used to strategically assess the species of bacteria present in the cutlery trays. As qualitative research involves collecting data in a natural setting where the roots of the research problem underlie and organizing collected data into trends that fit the theme of the research, this method was used to investigate the research question and explore the different species of bacteria present in communal cutlery trays in a high school setting (Creswell et. al., 2017). The desired qualitative data regarding the characteristics of different bacteria colonies were collected by gathering samples from communal cutlery trays and culturing the samples for analysis. Recording bacteria colony characteristics was required to enable the researcher to deduce and determine the bacteria species present in communal cutlery trays. Furthermore, in order to add credibility to the research, bacteria identification tests were conducted at an external accredited laboratory in Singapore.

Collection of Samples First, the relevant location of where the sampling will take place was selected. The cafeteria at International School A in Singapore was chosen because it is expected to serve more than 1200 customers daily. The large number of consumers that utilize communal cutlery trays enabled the findings of this research to be applied to a larger population, facilitating the generalization of the study.

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The cafeteria at International School A includes four stalls. The cutlery trays from the largest stall with the most number of consumers were chosen. Second, a time period relevant to the inquiry was selected. At International School A, high school students have different lunch schedules based on the day of the week (e.g. Monday, Tuesday, Wednesday, Thursday, or Friday) and their grade (e.g. Grade 9, 10, 11, or 12). Refer to Figure 1 for an organized table of the students’ lunch schedules who attend International School A.

Figure 1. Sample Lunch Schedule of High School Students at International School A. The sample was collected after the lunch period to determine the species of bacteria that would be present in the cutlery trays after usage. Therefore, the sample was collected from 12:05 P.M., beginning five minutes after the lunch period, on Tuesday when the majority of the students and faculty would have accessed food from the cafeteria instead of engaging in extracurricular activities. Third, the surfaces that would be sampled as evidence to answer the research question were selected. The selected stall has two cutlery bins (Cutlery Tray A and Cutlery Tray B). Three samples from the top surface of each of the cutlery trays were collected. Refer to Figure 2 for a diagram of the cutlery trays used at International School A and what is defined as a top surface.

Figure 2. General Diagram of Cutlery Trays Used at International School A.

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Additionally, for each cutlery bin, three pieces of cutlery in total, one piece each based on type (spoon, fork, and/or knife) available, were selected to sample. Simple random sampling was used to select which cutleries to sample. The criteria for selecting cutleries for sampling are as follows: at least one of the major surfaces of the cutlery, the head or the stem, must be clearly visible from a bird’s eye view. Then, the cutleries that fit the standards were numbered from left to right, starting at number one. This procedure was repeated for each cutlery type within the same tray. A random number generator was used to pick one specific cutlery per type to sample. Refer to Figure 3 for the cutleries that met the selection criteria and how the cutleries were numbered in this study.

Figure 3. Labelled Cutleries from Cutlery Trays at International School A. In order to avoid the contamination of the collected samples with foreign bacteria, sterile pieces of equipment were used. For all selected sampling surfaces, a sterile cotton collection swab was gently rubbed against the surface for 20 seconds each. A new swab was used for every sampled surface. The researcher wore sterile gloves and dental masks during the process. In a study by Jeong on the bacterial contamination of facilities and utilities at Korean restaurants, samples were collected using sponges sterilized by the researcher himself (Jeong, 2005). However, for the purpose of this study, a presterilized collection swab, sterilized by the manufacturer, was used to limit confounding variables such as the possibility of inaccurate sterilization of collection equipment.

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Preparation of Samples Each collection swab was immediately rubbed against a growth medium in a diagonal and zig-zag direction upon collection to minimize the risk of contamination when transporting samples. Nutrient agar was selected as a growth medium for this study as a variety of microbes can grow on this medium (Moats, 1981; Basavaraju et al., 2022; Gnanamani et al., 2017). By holding the lid of the Petri dish at an angle, the agar was minimally exposed to the environment during the plating process. After repeating the procedure for all eleven samples, the Petri dishes were placed inside an incubator with the lid facing upwards within five minutes. According to a study on optimal incubation temperature adherence, “temperature is a key physicochemical factor that affects the bacterial environment” and pathogens that can cause harm to humans generally grow the best in temperatures similar to that of the KXPDQ KRVW ႏ- ႏ *XWLHUUH] HW DO 7KHUHIRUH WKH LQFXEDWRU ZDV VHW WR PDLQWDLQ ႏ IRU 48 hours.

Observation of Data After incubation, the Petri dishes were removed from the incubator and examined based on bacteria colony morphology. A Leica EZ4 stereo microscope was used during the examination process. Detailed photographs of the bacteria colonies were taken. Some characteristics of the bacteria colonies taken into account include form, margin, colour, and arrangement. This data was later used to analyse different bacteria species present in communal cutlery trays.

External Analysis of Collected Data In addition to culturing bacteria and studying bacteria colony characteristics, one of the eleven samples collected was sent to an accredited laboratory in Singapore to validate that E. coli, S. aureus, or Salmonella was present in the sampled cutlery trays. The eleven collected samples were labelled from numbers one to eleven and a number was chosen using a random number generator. The sample that corresponded to the chosen number was sent to an external laboratory. The confirmation test only involved three aforementioned bacteria species; according to prior studies, those species were the most commonly observed bacteria in schools and eating establishments (Jeong, 2005; Jeong et. al, 2002; Park et. al., 2014). At the laboratory, the presence of E. coli and S. aureus was inspected by plate count using 3M Petri-film. The presence of Salmonella was inspected by a detection test using 3M Petri-film. The deployed method enabled the exploration of bacteria present in the cutlery trays in a high school setting.

RESULTS The following section documents the cultured bacteria from samples of the communal cutlery trays at International School A to identify the various bacteria species present.

Microorganism Culture For each sample collected from the communal cutlery trays at International School A, various microorganisms were cultured on a growth medium. The cultured colonies of certain sample locations covered more surface area of the Petri dish than other sample locations. For example, while the microbiological culture of the knife sample of cutlery tray B covered a great majority of the surface area of the Petri dish, the microbiological cultures of the spoon sample of cutlery tray B covered barely any surface area of the Petri dish. Figure 4 compares the image of the cultured microbiological colonies.

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Figure 4. Microbiological Culture of Spoon and Knife Samples from Cutlery Tray B.

Cultured Colony Morphology From the various bacteria colonies, representative colonies with distinct colony characteristics were chosen. Cultivated bacteria were organized based on their colony morphology, including colony form, colour, opacity, size (mm), margin, and surface. Figure 5 shows an example of a representative colony, coded as colony A. This colony exhibited an irregular form, creamy white coloration, translucent opacity, a size of less than 0.5mm, a filiform margin, and a smooth surface. However, bacteria species could not be successfully speculated with this information. Table 1 organizes the colony characteristics and speculated species of all 21 different colonies.

Figure 5. Colony A Observed Under a Stereo Microscope.

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Colony Code

Colony Form Colour

Opacity

Size (mm)

Margin

Surface

Speculated Species

Irregular

Translucent <0.5

Filiform Smooth

Rhizoid

Translucent 1

Entire

Smooth

Spindle

Opaque

<0.5

Entire

Smooth

Circular

Yellow

Opaque

Entire

Smooth

S. aureus

Irregular

Opaque

0.5

Lobes

Smooth

Circular

Opaque

1.5

Entire

Smooth

E. coli

Circular

White

Translucent 1.5

Entire

Smooth

Circular

Light yellow

Translucent 2

Wavy

Smooth

Irregular

Opaque

1.5

Curled

Smooth

Bacillus subtilis

Circular

Opaque

Wavy

Smooth

Pseudomonas fluorescens

Circular

Light yellow

Opaque

Wavy

Smooth

Mycobacterium spp.

Irregular

Yellow

Translucent 1.5

Wavy

Smooth

Pseudomonas spp.

Punctiform

White

Translucent <0.5

Wavy

Smooth

Irregular

Yellow

Translucent 3.5

Filiform Smooth

Irregular

Translucent 4

Filiform Smooth

Circular

Red

Translucent <0.5

Entire

Smooth

Serratia marcescens

Irregular

Yellow

Translucent 1

Wavy

Rough

Enterobacter cloacae

Irregular

Opaque

Curled

Smooth

Circular

Orange

Opaque

Entire

Smooth

Irregular

Light yellow

Opaque

Wavy

Smooth

Irregular

Light orange

Translucent 4.5

Wavy

Smooth

Table 1. Representative Colony Characteristics and Speculated Species. “CW” was used as an abbreviation to note colonies that exhibited creamy white coloration. “IC” was used as an abbreviation for the word inconclusive to note representative colonies from which the researcher could not derive suspected bacterial species. In total, there were 21 species of bacteria that each exhibited unique colony characteristics. However, only eight could be identified with speculated bacterial species. The identified bacterial species from the communal cutlery trays include: S. aureus, E. coli, Bacillus subtilis (B. subtilis), Pseudomonas fluorescens (P. fluorescens), Mycobacterium spp., Pseudomonas spp., Serratia marcescens (S. marcescens), and Enterobacter cloacae (E. cloacae). This identification directly sheds light on the research question that investigates the bacteria species found in communal cutlery trays.

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In addition, the external laboratory report of the confirmation test that was conducted for the presence of specific bacteria species like E. coli, Salmonella, and S. aureus can be found in Table 2. Those three bacteria species were selected for a confirmation test because of their common presence in communal settings (Jeong, 2005; Jeong et. al, 2002; Park et. al., 2014). Location

Bacteria Species

Colony Forming Unit Per Swab

Cutlery Tray B Surface 2

E. coli

<10

Salmonella

S. aureus

<10

Table 2. External Laboratory Report for Bacteria Species. Table 2 confirms the presence of selected bacteria like E. coli, Salmonella, and S. aureus in communal cutlery trays. While there was no Salmonella found, there were less than ten colony-forming units of E. coli and S. aureus per swab. The results of this report were in agreement with the findings of speculated bacteria species.

DISCUSSION All samples of the cutlery trays at International School A included a variety of bacteria species. Although the eight identified species of bacteria are typically harmless, they may cause bacterial infections in humans and further develop into pathogenic strains (Akashi et. al., 1994; Yassin et. al., 2012; Liu et. al., 2021). This may be escalated as communal sources or settings facilitate pathogen growth (Zehra, 2020). Some strains of E. coli can cause serious infections, including urinary tract infections, gastrointestinal infections, and pneumonia (Akashi et. al., 1994). Although very rare, B. subtilis can cause opportunistic infections in immunocompromised individuals (Yassin et. al., 2012). P. fluorescens can occasionally cause infections such as pneumonia in humans (Liu et. al., 2021). Mycobacterium spp. is responsible for a majority of deaths from infectious diseases (Cohen et. al., 2003). Pseudomonas spp. can cause a range of infections in humans, including pneumonia, sepsis, and urinary tract infections (Gales et. al., 2001). Species of bacteria like S. marcescens can cause pneumonia, urinary tract infections, and bloodstream infections in humans (Buffet-Bataillon et. al., 2009). E. cloacae may also cause urinary tract infections, pneumonia, and bloodstream infections in humans (Edlin et. al., 2013). Many of the identified bacteria species, such as S. aureus and E. coli, are found in humans (Lowy, 1998; Jang et. al., 2017). This finding aligns with how numerous consumers from International School A come in physical contact with the cutlery tray. For instance, S. aureus, one of the identified then confirmed species, is commonly found on the skin and mucous membranes (nasal area) of humans (Lowy, 1998). People with S. aureus may have touched or sneezed on the cutlery trays, transferring the bacteria to the cutlery trays. In addition, E. coli, another identified then confirmed species, can often be located in the human digestive tract (Jang et. al., 2017). Therefore, it also acts as a general indicator of faecal contamination (Senkbeil et. al., 2019). The observation of suspected E. coli may be due to consumers accessing cutlery trays without sanitizing their hands after using the restrooms. Furthermore, the microbiological cultures of samples from infrequently accessed parts of the cutlery tray covered a greater surface area of the Petri dish than cultures of samples from frequently accessed parts of the cutlery tray. For example, pieces of cutlery such as knives are rarely used by consumers as the cafeteria at International School A seldom serves food that requires the usage of knives. The cultured

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colonies from cutlery tray B knife samples covered a great majority of the Petri dish it was cultured on. On the other hand, spoon samples from the same tray covered barely any surface area of the Petri dish it was cultured on. This difference in surface area of microorganism culture may be due to how quickly regularly used cutleries are circulated and then frequently washed, in comparison to infrequently used pieces of cutlery. For instance, Antibacterial liquids such as dish soap can control microorganism counts and play a significant role in reducing the risk of bacterial contamination (Holah et. al., 2006).

LIMITATIONS While bacteria studying bacteria colony characteristics and utilizing colony morphology can enable the researcher to identify the bacteria with suspected species, this method also has many limitations. For instance, the researcher must manually assort the characteristics of bacteria colonies (e.g. colour, margin, opacity, etc.). During this process, the researcher may have unknowingly introduced bias as parts of the identification process solely relied on the researcher’s perception. As this limitation makes the study more prone to errors, it may affect the level of certainty regarding the findings of this research. Manually sorting qualitative data may also be time-consuming and labour-intensive, potentially limiting the scope of the study and the type of data collected. Furthermore, nutrient agar, the growth medium used to culture bacteria from different samples to collect data for the study, was not a very popular choice among other researchers when culturing rather uncommon and specific bacteria species like S. marcescens (Negut, 1973). Therefore, it discouraged the accurate comparison of bacterial colony characteristics with existing data on bacteria cultures. This is also why many representative colonies could not be identified.

CONCLUSION The goal of this study was to investigate the bacteria species found on communal cutlery trays at International School A. A range of bacteria species was identified in the cutlery trays, including: S. aureus, E. coli, B. subtilis, P. fluorescens, Mycobacterium spp., Pseudomonas spp., S. marcescens, and E. cloacae, using colony morphology. If developed into a pathogenic strain, the identified bacteria may negatively impact the health of humans through bacterial infections. Furthermore, the delimitations of this study set grounds for new research. In future investigations, researchers may incorporate different methods of bacteria identification tests to confirm the presence of certain species. For instance, after culturing samples, one may carry out Gram staining to further specify whether or not colonies are gram-positive or negative. Additionally, through extracting bacteria DNA, researchers will be able to confirm the bacteria species through 16s rRNA sequencing. Furthermore, the findings of this descriptive research may be an indication that cafeterias or mass dining establishments that use communal cutlery trays to distribute cutleries should use different methods of distributing cutlery to minimize bacterial contamination. The results of this study will hopefully inform researchers to explore the bacteria present in other communal sources as the impact of this topic on human health is considerable.

ACKNOWLEDGEMENT I acknowledge the following sources of support for this study: financial reimbursement from the Singapore American School Quest program.

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Contrastive Learning of visual representations for Plant Disease Recognition Author 1

Full Name

Yoon, Seung Wook

Hankuk Academy of Foreign Studies

(Last Name, First Name)

School Name

: : : :

ABSTRACT: Problem: Plant disease recognition plays a crucial role in agricultural management, enabling early detection and targeted treatment to mitigate yield losses. Recent advancements in deep learning and computer vision have demonstrated great potential for automating the detection process through visual representations. However, these methods yield suboptimal results for non-tomato diseases due to their heavy reliance on public datasets predominantly composed of tomato images. As a consequence, the models trained on such biased datasets exhibit limited generalization capability when applied to other plant species. Approach: To address this problem, I propose a novel framework that utilizes contrastive learning to learn robust and discriminative visual representations for the identification of plant diseases. In this research paper, I investigate the application of contrastive learning for plant disease recognition by leveraging large-scale datasets of plant images. Results: Through extensive experiments, I evaluate the effectiveness of the proposed method in capturing subtle disease-related patterns and differentiating between healthy and diseased plants. The results clearly demonstrate that contrastive learning outperforms traditional supervised learning methods and achieves state-of-the-art performance in plant disease recognition tasks.

KEYWORDS: Contrastive Learning, Artificial Intelligence, Plant Disease

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1. INTRODUCTION 1.1 Problem Definition In recent years, the severity and frequency of plant diseases have intensified as a result of climate change, leading to profound economic consequences for farmers' livelihoods and community food security. This issue is projected to deteriorate further with time. A notable example is the Sainsbury Laboratory's findings, which indicate that global crop losses from late blight alone reach a staggering £3.5 billion per year [1]. Consequently, it is imperative to prioritize the development of sustainable and efficient plant disease management strategies to safeguard the integrity of our agricultural system and promote its overall health. The rapid advancements in technology hold immense potential to transform the approach of farmers towards plant disease management. Among the promising avenues, the development of automated systems stands out, enabling accurate differentiation between healthy and diseased plants and empowering farmers to take proactive measures for crop protection. Machine learning techniques have emerged as a favored area of research, with numerous studies proposing their utilization in creating efficient and user-friendly plant disease management systems. The successful implementation of such technologies has the capacity to greatly boost crop productivity, thereby benefiting farmers and society as a whole. Despite the extensive research conducted on plant disease detection, the majority of studies have been confined to a limited number of plant species. Early investigations, in particular, heavily concentrated on recognizing diseases in tomato plants due to their global prominence as the most widely cultivated vegetable [1]. Moreover, many plant disease-related datasets, such as Plant Village, exhibit a significant bias towards tomato plants, further reinforcing the focus on this specific crop [2]. However, this narrow research scope poses challenges in extrapolating findings to other plant species. Therefore, it is imperative to broaden the scope of research to encompass a more diverse range of plants and develop robust and adaptable plant disease detection methods that can be applied across various species.

1.2 Previous Method In this chapter, I will examine several previous methods proposed for plant disease detection. Tim et al. [3] introduced a shallow network based on LeNet, demonstrating a disease detection accuracy of 95%. This research showcased the applicability of machine learning models in plant disease recognition. Karthik et al. [4] presented a more accurate model based on ResNet, achieving an accuracy of 98%. The improvement in accuracy was attributed to the deeper network architecture compared to previous approaches. However, despite their success on the Plant Village Dataset [2], both methods tend to yield suboptimal results when applied to real-world samples. To address this issue, Liu et al. [5] proposed a novel ResNet-based model that utilized a privately collected dataset specifically designed for real-world applications. Additionally, Abbas et al. [6] introduced a superior model with an accuracy of 99.5%, which could be effectively utilized in realworld scenarios. Their approach involved leveraging GANs (Generative Adversarial Networks) to generate the dataset, contributing to the model's enhanced performance. However, the aforementioned research exhibited a bias towards detecting diseases in tomato leaves. The model demonstrated high accuracy only when tomato leaves were used as input. Conversely, when inputting other crops such as cabbages or carrots, the model produced arbitrary results instead of accurately classifying the diseases. This issue persisted even when the diseases were identical. For instance, the model's accuracy significantly declined when late blight tomato leaves were replaced with late blight carrot leaves. The fact that the model's accuracy decreases simply because the type of plant

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changes is perplexing, considering that the visual manifestation of diseases in plants tends to be similar. This indicates that the existing models are excessively biased towards a particular plant and cannot be effectively deployed in environments where multiple crops are cultivated. This bias stems from their inability to capture the visual characteristics of diseases and instead primarily focus on the specific shape of tomato leaves. The conventional approach to addressing this problem would be to gather a comprehensive plant disease dataset for each individual crop. However, this method is both timeconsuming and expensive. Collecting such a vast dataset is practically infeasible due to the countless number of crop varieties present worldwide.

(a)G

(b) Figure 1. Comparison between the previous approach and the proposed framework (a): Previous models have demonstrated high accuracy in detecting disease on “Tomato leaves”, but their performance on other types of crop leaves has been found to be relatively low (due to the fact that these models have been heavily biased towards the color and shape of tomato leaves). and (b): The proposed method is crop-agnostic, exhibiting high accuracy in detecting diseases across various plant species. This is achieved by disentangling the features of the input image, allowing the model to capture disease-related patterns in diverse plant types effectively.

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1.3 Proposed Method To address the aforementioned problem, I proposed a novel contrastive learning-based crop-agnostic plant disease recognition framework. To the best of my knowledge, this is the first attempt to detect plant diseases irrespective of the plant species. The proposed framework comprises linear layers and a feature extractor, typically implemented using convolutional neural networks. In the initial step, the image set is fed into the feature extractor, converting it into a feature map. The vector value of this feature map is then subjected to contrastive learning, involving a comparison process. When one image of a plant contains a disease while the other does not, but the model extracts a similar vector value, a high loss is observed. This training process enables the model to detect diseases without being influenced by the specific plant species, effectively eliminating biases. The main contributions of the proposed method are threefold. 1. To the best of my knowledge, this paper first proposed the need for crop-agnostic disease recognition and an end-to-end unified plant disease recognition framework. 2. To achieve this, the proposed method is trained based on contrastive learning to learn useful presentation of crop disease and disentangle the disease-related latent variables. 3. Through comprehensive experiments, the paper shows the superiority of the model by showing the high accuracy to detect plant disease. In the experiment, the proposed method is compared with existing state-of-the-art methods. In order to apply the disease detection model in real agriculture, the model should be crop-agnostic. In other words, the model should be able to recognize the disease without being interrupted by the type of plant. Even if the blight is on a tomato leaf or carrot leaf, the model should detect that the plant is infected by blight.

2. RELATED WORK 2.1 Plant Disease Plant diseases can arise from a range of unavoidable factors, including environmental conditions, pests, and even human activities [7]. With climate change leading to fluctuating precipitation and sunlight patterns, plants in specific regions are experiencing heightened stress levels due to the shifting environment. These stressors manifest as diseases that hinder plant growth. Despite the diverse causes of diseases, their characteristics remain consistent regardless of the plant species. In other words, the same diseases exhibit identical traits across all plants. For instance, powdery mildew is a fungal disease characterized by the development of white, powdery growth on plants. It can affect a wide range of plants, including grapevines, apples, pears, and cucumbers, particularly in humid or wet environments. Late blight, on the other hand, is another fungal disease that primarily affects tomatoes and potatoes when conditions are wet or humid. Similarly, Early blight, caused by the fungus Alternaria, is often spread by wind, rain, or insects. It is important to note that there are minimal visual distinctions between Late blight and Early blight in tomatoes and potatoes. As shown in Figure 2, diseases of the same type do not exhibit visual variations based on the plant species they afflict. However, existing methods for classifying plant diseases have demonstrated a strong bias towards diseases occurring in tomatoes, posing scalability challenges for other plant types. Consequently, although diseases may display similar characteristics across various plants, the model

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exhibits high accuracy exclusively for tomatoes. The primary objective of this research is to address the aforementioned issue and develop a method that overcomes these limitations.

Tomato

Potatoes

(a) Early Blight

Pepper bell

Tomato

Soybean

(b) Bacterial Spot

Apple

Figure 2. Example of Plant Disease Image (a): Early blight in plants is caused by a fungus that attacks leaves and stems, typically dark brown or black, with a yellow halo surrounding them. (b) The bacterium that attacks leaves and fruit causes Bacterial spots. Dark brown or black spots with a yellow halo are their main visual characteristics.

2.2 Image Classification Image classification refers to the technique of categorizing input samples into predefined categories. In the medical domain, an image classification model can predict whether a given cell image exhibits tumor characteristics or represents a healthy cell without any tumor [8]. Another application of image classification is in digit recognition, where the technique enables computers to accurately interpret and classify numerical digits. By employing image classification, a model can effectively categorize a dataset of numbers ranging from 0 to 9 into their respective classes [9].

Figure 3. Diagram of image classification model Figure 3 shows the architecture of the image classification model used in this research. The output of the network corresponds to the predicted category or class of the input image determined by the classifier. The aim of this research is to apply image classification techniques for the classification of various plant diseases. A comprehensive explanation of the architecture employed in this study can be found in Chapter 3.1.

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2.3 Contrastive Learning Contrastive learning is a machine learning technique that strives to enhance the model's ability to distinguish between positive and negative examples. In the context of image classification, a positive example refers to a similar image, while a negative example pertains to a different image. For instance, in the case of leaf images, positive examples would correspond to healthy leaves, while negative examples would represent leaves with diseases. Contrastive learning involves encoding each image into a high-dimensional vector representation and subsequently comparing the vector values to assess their similarity. The loss function penalizes the model when the encoded vectors differ from the vector of the positive example, encouraging the model to learn to separate positive and negative instances.

Figure 4. Concept Diagram of Contrastive Learning (http://ai.stanford.edu/blog/understanding-contrastive-learning/) Contrastive learning has been implemented in various well-known approaches, among which SimCLR [10] stands out. SimCLR employs a combination of data augmentation and contrastive learning during the training process. It trains the model by encoding the images into vectors and comparing them. The overall concept of contrastive learning is illustrated in Figure 4. Taking inspiration from these approaches, the proposed method leverages contrastive learning to train the feature extractor of the classification network, aiming to obtain improved representations of plant disease samples. The detailed process is elaborated further in Chapter 3.3, providing a comprehensive explanation of the methodology.

3. APPROACH 3.1 Overall Architecture

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(a)

(b) Figure 5. Overall architecture of the proposed framework (a): Contrastive learning (Feature Extractor) and (b): Supervised learning (Plant Disease Recognizer)

The proposed framework consists of two distinct phases. The initial phase involves contrastive learning, where the feature extractors are trained to acquire enhanced representations for each disease across different plant species. As illustrated in Figure 5, an image set of a specific plant is fed into the feature extractor, which then generates feature vectors for each image sample. These feature vectors encapsulate the similarities and differences in the visual characteristics of the images. During the contrastive learning phase, the feature extractor aims to produce similar feature vectors for input image samples belonging to the same plant disease category, regardless of the plant species. Conversely, when the feature extractor generates dissimilar feature vectors for disease-infected plants

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and healthy plants, which share the same species, a high loss value is incurred. This process ensures that the feature extractor is trained to mitigate biases associated with plant species. In the subsequent phase, supervised learning is conducted to train the Plant Disease Classifier, which serves as the final output of the proposed framework. The classifier is trained to provide scores for each plant disease category, employing labeled data to enhance its predictive capabilities.

3.2 Contrastive Learning Images typically comprise various features, including color, shape, background, and illumination. The feature extractor, typically implemented using convolutional neural networks, aims to extract these intertwined features from the input images. However, not all of these features are relevant to plant disease recognition. For instance, the background or shape of plants does not directly correlate with plant disease. Unfortunately, these diverse features become entangled in the feature map, which hinders the precise recognition of plant disease types by the trained model. To address this issue and enhance the robustness of the plant disease framework across different plant species and diseases, it is essential to disentangle these features from the images. Specifically, the feature maps of plant images with the same disease should exhibit similarity, while those extracted from images with different diseases (or healthy images) should show dissimilarity. In summary, the primary objective of the proposed method is to achieve accurate classification results by obtaining improved representations of various plant species and diseases. This entails disentangling the essential features that provide disease-related information from the multitude of features present. The process of finding a better representation is crucial for developing a high-accuracy framework. To achieve this, the proposed method employs contrastive learning in the feature extraction process, where the input images are transformed into feature maps. Contrastive learning helps ensure that similar images yield similar feature vectors, while dissimilar images produce dissimilar feature vectors.

3.2.1. Feedforward process

(a)

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(b) Fig 6. Example of batched input for contrastive learning (a): Example of batched input image set, and (b): Extracted feature vectors from the input batched plant samples In Figure 6, an example of a batched input image set for contrastive learning is depicted. The image set consists of tomato leaves with late blight (labeled as A), potato leaves with late blight (labeled as B), healthy tomato leaves (labeled as C), and healthy potato leaves (labeled as D). These images are then passed through the feature extractor, which converts them into embedding vectors representing the essential features of the inputted images. The main objective of contrasting learning is to maximize the similarity between the vectors extracted from belonging images to the same category. During contrastive learning, once the embedding vectors are obtained from the feature extractor, they are subjected to a similarity comparison process. The goal is to ensure that embedding vectors from images of the same category are more similar to each other compared to vectors from images of different categories. This is achieved by maximizing the similarity between embedding vectors from the same category and minimizing the similarity between embedding vectors from different categories. To quantify the similarity, various metrics can be used, such as cosine similarity or Euclidean distance. Cosine similarity measures the cosine of the angle between two vectors, while Euclidean distance calculates the straight-line distance between two points in the embedding space. By applying these similarity metrics, the contrastive loss function can be defined to capture the relationship between the embedding vectors. I will explain the concept of the contrastive loss function that aims to optimize the similarity between the extracted embedding vectors of belonging images to the same category in the following chapters.

3.2.2. Loss function for contrastive learning The loss function utilized in contrastive learning is computed based on the co sine similarity function as shown in Figure 7 for same category image pairs. This loss function is referred as the “Normalized Temperature Scaled Cross Entropy (NT-Xent)” loss function [10]. We can measure the similarity between the embedding vectors of same catagorized images and encourage them to be closer together in the embedding space by applying the NT-Xent loss function. This facilitates the learning process and enhances the discriminative power of the trained model.

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Fig 7. Example of similarity calculation by cosine similarity

When the model extracts vector values from images, the similarity between two vectors is higher when the angle between them is smaller. A smaller angle, approaching 0 degrees, indicates a higher degree of similarity, while a larger angle, closer to 180 degrees, suggests a greater dissimilarity. To measure this similarity, cosine similarity is commonly used because the cosine value is largest at 0 degrees and decreases as the angle approaches 180 degrees. Equation 1: cosine similarity function

The equation illustrates how the cosine similarity function operates. In this equation, zi and zj represent the embedding vectors extracted from images Ii and Ij, respectively.

Figure 8. shows how the softmax function works.

Once the similarity between each pair is calculated, the softmax function can be employed as a loss function to maximize the similarity among similar or identical categories as shown in Figure 8. Equation 2: NT X-ent loss function

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Finally, equation 2 represents the NT-Xent loss function, which calculates the loss between two images. In this function, the numerator represents the similarity between the two images. As the vectors of the two images become more similar, the value of the numerator increases. On the other hand, the denominator consists of the sum of the similarities between a positive image and other negative images. The overall probability increases when the similarity with the positive image pair is high, and the similarity with the negative image pairs is low. Since the NT-Xent loss function is a variation of cross-entropy function, the output loss value decreases as the probability increases.

3.3 Supervised Learning (Plant Disease Recognizer) Figure 5(b) illustrates the second phase of the proposed method, which involves classifying the type of plant disease using the Plant Disease Recognizer (PDR). The PDR consists of two linear layers, providing a simple yet effective architecture. To train the PDR, two experiments are conducted. The first method is fine-tuning, where both the feature extractor and the PDR weights are updated simultaneously. In contrast, the second method freezes the feature extractor while updating only the weights of the PDR. The experiments demonstrate that the fine-tuning method yields more accurate results. This is because, during the training process, the feature extractor is optimized to minimize the loss, thereby improving the overall performance of the PDR. Equation 3: Cross-entropy loss function Lce = -ln P Where P denotes the probability calculated from the model. The loss value is then calculated by the cross-entropy loss function Lce.

3.4 Implementation Details The proposed framework is trained using the Adam optimizer [11]. The NT-Xent loss function and cross-entropy loss function were both employed, as mentioned previously. The initial learning rate was set to 0.0001, and a learning rate decay of 1/10 was applied every 40 epochs, with decay occurring at epochs 40 and 80. The training process consisted of 100 epochs, with a batch size of 512. For the feature extractor, ResNet [12] is used, along with two linear layers for the Projection Head and PDR components.

4. EXPERIMENTAL RESULTS 4.1 Dataset The proposed framework in this research utilizes the PlantifyDr dataset [2] for model training. With 10 different plant types, Apple, Bell pepper, Cherry, Citrus, Corn, Grape, Peach, Potato, Strawberry, and Tomato, this dataset consists of over 125,000 representing images. This dataset offers a diverse and extensive collection of images, enabling comprehensive training and evaluation of the framework with a wide coverage of 37 plant diseases. The dataset is split into an 8:2 ratio, with 80% used for training and 20% used for testing.

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Figure 9. Snapshot of PlantifyDr dataset [2] Figure 9 above illustrates the dataset samples color distributions and geometric variations which is presenting significant challenges for plant disease classification. The dataset contains a wide range of color variations and distinct geometric structures, highlighting the complexity and intricacy involved in accurately identifying and categorizing plant diseases.

Figure 10. Plant type distribution of PlantifyDr dataset

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Figure 11. Category distribution of PlantifyDr dataset

As shown in Figure 10, the PlantifyDr dataset suffers from a significant imbalance issue, with Tomato dominating the dataset. With the Healthy and Bacterial Spot categories overwhelmingly dominating the sample distribution, figure 11 reveals the presence of a category imbalance issue within the dataset. As the model could be biased towards the majority classes, this uneven category poses challenges for accurate disease recognition which is potentially neglecting the detection and classification of rarer or less represented categories. To address this problem the proposed method utilizes contrastive learning, which helps mitigate the impact of class imbalance and improves the overall effectiveness of disease recognition. Detailed experimental results demonstrate the efficacy of the proposed approach in addressing the class imbalance issue and achieving superior performance compared to traditional supervised learning methods in the next chapter.

4.2 Comparison This chapter provides a comprehensive overview of the experimental process conducted to validate the effectiveness of the proposed method. The evaluation metric employed in this study is accuracy, a commonly used measure for assessing the performance of image classification tasks. To compare the performance of the proposed method with a supervised learning-based approach, an accuracy evaluation was conducted using the PlantifyDr dataset. To conduct a pair comparison, two approaches were employed: a supervised learning approach using Resnet34 as the baseline, and the proposed method, which involves contrastive learning as explained in Chapter 3. Both approaches utilized the same network architecture design and hyper parameter settings.

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Accuracy baseline

66.71 %

Proposed method

72.96 %

Table 1. Comparison of accuracy on the PlantifyDr dataset (experiment 1) The performance of the proposed method is compared with a state-of-the-art approach to assess its effectiveness in the context of plant disease classification tasks. The baseline model achieved an accuracy of 66.71%, while the proposed method surpassed it with an accuracy of 72.96%. Notably, the proposed method incorporates contrastive learning techniques, as explained in Chapter 3. The significant performance improvement observed in the proposed method clearly indicates its superiority over the state-of-the-art approach. This outcome underscores the potential of the proposed method as an advanced solution for addressing class and category imbalance problems in plant disease classification tasks.

Accuracy baseline

60.29 %

Proposed method

70.07 %

Table 2. Comparison of accuracy on the PlantifyDr dataset without Tomato samples (experiment 2) In order to assess the ability of the proposed method to address class imbalance problems, a second experiment is conducted. In this experiment, both the baseline model and the proposed method are evaluated on the dataset that excluded all the tomato samples. The results, as shown in Table 2, indicate that the proposed method maintained comparable accuracy (with a decrease of 2.89%) to the results of the first experiment. However, the baseline model experienced a significant drop in accuracy (decreasing by 6.42%), highlighting its susceptibility to class imbalance issues. These findings provide clear evidence that proposed method effectively contributes to problems of mitigating class imbalance.

Accuracy baseline

64.78 %

Proposed method

72.36 %

Table 3. Comparison of accuracy on common disease category (experiment 3) Furthermore, Black Rot, Bacterial Spot, Early Blight, Late Blight, and Healthy are all the comparison that is conducted on the common disease categories. The goal of this experiment is to evaluate whether the proposed method maintains comparable accuracy for categories that represent a significant portion from the dataset. The results indicate that the proposed method maintains comparable accuracy to the findings of the first experiment as shown in Table 3. The proposed method exhibits good generality and not biased towards certain categories, shown from the outcome.

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(a)

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The confusion matrix of the three experiments is illustrated in Figure 12. The confusion matrix is a tool commonly used to analyze the characteristics of a classification model which provides insights into the correct classification ratio for each category (represented by the diagonal components). All three confusion matrices exhibit prominent diagonal components, indicating a strong generality in accurately classifying diverse plant disease categories as shown in Figure 12.

5. CONCLUSION Throughout this research paper, aiming to improve the accuracy and generalization of visual representations across various plant species, I have explored the use of contrastive learning for plant disease recognition. I have proposed this approach about novel framework that leverages the power of contrastive learning. Since the purpose was to learn robust and discriminative visual representations for plant disease recognition. Achieving the state-of-the-art performance in accurately identifying and differentiating between healthy and diseased plants, this proposed approach surpassed traditional

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supervised learning methods. These findings provide insights into the potential of contrastive learning in the field of plant disease recognition which are valuable. I encourage further research in exploring alternative self-supervised learning techniques which explores larger and more diverse datasets, and investigating the transferability of learned representations across different crops. I believe that the proposed research contributes to the advancement of plant disease recognition by harnessing the power of contrastive learning. The development of more accurate, robust, and widely applicable disease recognition models the proposed method shows the way, therefore revolutionizing agricultural practices and positively impacting global food production.

REFERENCE [1] https://www.statista.com/statistics/264065/global-production-of-vegetables-by-type/ [2] Singh, Davinder, et al. "PlantDoc: A dataset for visual plant disease detection." Proceedings of the 7th ACM IKDD CoDS and 25th COMAD. 2020. 249-253. [3] Tm, Prajwala, et al. "Tomato leaf disease detection using convolutional neural networks." 2018 eleventh international conference on contemporary computing (IC3). IEEE, 2018. [4] Karthik, R., et al. "Attention embedded residual CNN for disease detection in tomato leaves." Applied Soft Computing 86 (2020): 105933. [5] Liu, Jun, and Xuewei Wang. "Tomato diseases and pests detection based on improved Yolo V3 convolutional neural network." Frontiers in plant science 11 (2020): 898. [6] Abbas, Amreen, et al. "Tomato plant disease detection using transfer learning with C-GAN synthetic images." Computers and Electronics in Agriculture 187 (2021): 106279. [7] Mehta, Chandra Mohan, et al. "Compost: its role, mechanism and impact on reducing soil-borne plant diseases." Waste management 34.3 (2014): 607-622. [8] Seetha, J., and S. Selvakumar Raja. "Brain tumor classification using convolutional neural networks." Biomedical & Pharmacology Journal 11.3 (2018): 1457. [9] Cohen, Gregory, et al. "EMNIST: Extending MNIST to handwritten letters." 2017 international joint conference on neural networks (IJCNN). IEEE, 2017. [10] Chen, Ting, et al. "A simple framework for contrastive learning of visual representations." International conference on machine learning. PMLR, 2020. [11] Kingma, Diederik P., and Jimmy Ba. "Adam: A method for stochastic optimization." arXiv preprint arXiv:1412.6980 (2014). [12] He, Kaiming, et al. "Deep residual learning for image recognition." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016.

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Identification of Exoplanet Candidates using CNN Models based on Light Curve Author 1

Author 2

Full Name

You, Dongho

School Name

Hansung Science High School

Full Name

Kim, Hwan

Korean Minjok Leadership Academy

(Last Name, First Name)

School Name

ABSTRACT: Our research is based on utilizing CNN models to identify the exoplanet candidates via their light curves. We present the light curves of CP (Confirmed Planet) and FP (False Positive) objects in the database collected by the Kepler, K2, and Tess missions and the model of Convolutional Neural Network (CNN), distinguishing light curves through distinct features of the graph. Finally, we aim to identify the PC (Planet Candidates) that are yet to be verified though likely to be CPs. We obtained the phase-folded light curves of 1169 CPs and 1117 FPs from the data archive and converted them into gray images of the fixed size (256×256) for CNN modelling. As a result, the CNN model shows about 89.9% accuracy in distinguishing CPs and FPs. We expect that our investigation can later be adapted for verifying follow-up planet candidates through the light curves.

KEYWORDS: Convolutional Neural Network(CNN), Exoplanets, Planet Candidate(PC), Confirmed Planet(CP), False Positive(FP), Kepler Input Catalog(KIC)

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1. Introduction In the current literature, the prominent discovery method of exoplanets is the transit method: detecting the luminosity change when a planet passes by its host star. However, scientists must identify false positives such as eclipsing binaries and variable stars because their signals can be similar to those of exoplanets. Thus, developing methods of efficiently classifying exoplanets into categories of confirmed exoplanets and false positives is one of the leading objectives in exoplanetary science. This leads us to implement a machine learning technique (generation of CNN Model) to automate the sorting process of exoplanet candidates. We believe that this mechanism can later be adapted as a widely acceptable tool for determining whether the candidates are genuine exoplanets. As the CNN Model highly depends on the preexisting data set, we used the data from the Kepler, K2, and TESS missions as the training data set of our CNN model. In this paper, we present how we calibrated the preexisting data into usable sources to train the CNN model and its results.

2. Theoretical Background 2.1 Exoplanet An exoplanet is an out-of-solar system celestial object that orbits around a star other than our sun. Exoplanets, unlike stars, do not emit enough light, making them challenging to detect. Despite various methods of exoplanet discovery, one famous and simplest way is using the light curve. When exoplanets pass between the star and the Earth, the light curve of the star which the planet orbits changes periodically. This change, unlike the change of the eclipsing binaries or the variable star, shows a distinct shape, allowing us to distinguish those objects by just analyzing their light curves. The Kepler, K2, and TESS missions are the most renowned exoplanet-detecting projects.

2.2 Light Curve A light curve is a graph showing the amount of change in light intensity over time, with the horizontal axis as the time and the vertical axis as the light intensity. As light curves are created with deliberate observations, different celestial objects—binaries, exoplanets, variable stars, and many others—can be identified through analyses of their light curves. For instance, eclipsing binaries–one common type of binary star—have luminosity changing periodically because one star passes in front of another star and causes an eclipse. Variable stars, likewise, show periodic changes in light intensity. Thus, light curves with periodical changes do not necessarily represent an exoplanet. Rather, they are more likely to be an eclipsing binary or a variable. Exoplanets therefore can only be discovered via classifying the light curves into different groups based on the distinct features of each graph, allowing us to exclude the nonexoplanet candidates.

2.3 CNN (Convolution Neural Network) In classifying images, FNN (Feedforward Neural Network) has vectors as its input, which unfortunately cannot count the correlation between adjacent pixels. Thus, in order to minimize the error caused by the image classifier, the new technology CNN includes two novel structures: convolution and pooling. CNN is constructed with two procedures, which call feature extraction and classification.

2.3.1 Feature Extraction Feature extraction consists of repeating the convolution layer and the pooling layer. It also decreases the size of the original image file and extracts only the features that are conspicuous—we eliminate what is unnecessary.

2.3.2 Classification The most important characteristic of CNN is that the information is very local. Using filters (or kernel), this layer extracts local features of a selected area, sliding the filters with a given stride, eventually

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generating the feature map. The padding method is used to inhibit the feature map from decreasing in its number of pixels. The first convolutional layer requires an image size, filter size, and number of filters, and from the second, only the size and number of filters are received as input values.

2.3.3 Result Analysis After forming a model as above, we determine which epoch we are going to use, which is depending on how much learning is made. If the validation accuracy is high, it might be overfitted, and if the validation accuracy is low, it might be underfitted.

2.3.4 Activation Function The activation function is used in creating a neural network with multi-layers. Adding layers is mostly done by substituting a linear score function for itself. However, a linear score function with multi-layers will end up being a single linear score function due to its linearity when no activation function is used while adding. Therefore, programmers use non-linear activation functions. In our model, we applied the ReLu function and the Sigmoid function. ReLu function and Sigmoid functions (with the lowercase sigma) are described as the following equations.

ܴ݁‫ = )ݖ(ݑܮ‬max (0, ‫ )ݖ‬, ߪ(‫= )ݖ‬

Figure 1. Graph of the ReLu function

ଵ ଵା௘ ష೥

Figure 2. Graph of the Sigmoid function

2.4 Lightkurve Pipeline Lightkurve pipeline is a Python package designed by Kepler/K2 Go Office and TESS GI Office. It helps to analyze the light curves of planets, stars, and galaxies by providing easy access to TESS and Kepler telescope archive data. It enables the usage of multiple light curve data with Python.

3. Methods As mentioned above, our CNN model is based on the database from the data archive from the Kepler, K2, and TESS missions. These data, however, are not applicable in machine learning unless they are calibrated into a usable form. We used the Lightkurve pipeline for the calibration, which is a Python package dealing with the Kepler, K2, and TESS data.

3.1 Observation The data was collected by the Kepler telescope and the Tess telescope, launched on March 6, 2009, and started observing on May 2, 2009. The Kepler mission ended on May 11, 2013, as the telescope lost its second reaction wheel. Via utilizing light pressure from the sun to replace the broken wheel, the

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telescope started its new mission - named K2 mission – from February 4, 2013, to September 26, 2018. The Kepler mission took data from around 200,000 stars near the Cygnus, while the K2 mission observed along the ecliptic. The data includes photons around 4200Å to 8800Å wavelength, which covers all the visible light and a small portion of Infrared. Meanwhile, the Tess telescope launched on April 18, 2018, currently on the mission of an all-sky transit survey, detecting Earth-sized exoplanets around 4200Å to 8800Å wavelength.

3.2 Classification and Calibration The collected data were then separated into three main groups: Confirmed Planet (CP), False Positive (FP), and PC (Planet Candidate). CP includes those which are confirmed as light curves of exoplanetpossessing stars. FP includes those which are confirmed not to be light curves of exoplanet-possessing stars. PC is a set of light curves which are assumed to possess eclipse by the exoplanets. Thus, data in PC would later be classified into either CP or FP. CP and FP also have CSV files having information about the KOI (Kepler Objects of Interest), KIC (Kepler Input Catalogue) ID number, location, period, duration, depth, and many others. These files are from the Exofop website, about the Kepler mission. CNN requires data that are clean and errorless. However, selecting appropriate data from the sets requires trial and error, since it is highly related to the accuracy of the CNN model. After attempting various periods, duration, and depths, we concluded that the best sets of data are those having period/duration less than 500 and depths less than 37000ppm. Then, only the objects those are eligible and can be supported by the Lightkurve are calibrated and converted to npy. For example, the following chart is a set of information about the Kepler-1624b that the CSV file provides. Kepler-1624 b is the candidate from the CP list, and it is classified to be eligible for being used for the training. The empty cells are left as unknown. TIC ID

TOI

Kepler Name

KOI

KIC ID

1.38E+08

4587.01

Kepler-1624 b

4928.01

1873513

Disposition

Spectroscopy Observations 0

Time Series Observations 0

RA (deg)

Imaging Observations 2

Dec (deg)

TESS Mag

TESS mag error

Transit Epoch error

37.37626

14.5505

0.007

Transit Epoch (BJD) 2454965

Period (days)

Period error

Depth (ppm)

Depth error

Duration (hours)

3.290304

4.43E-06

13552.6

64.8

1.7215

Duration error

Radius (R_Earth)

Radius error

Eq Temp (K)

Eq Temp error

0.0126

4.91

0.41

540

Insolation (Earth flux) 20.06

Insolation error

Inclination (deg)

Inclination error

6.53

89.68

Planet Rad/Stellar Rad error 0.000527

Stellar Density (g/cm^3) 7.28769

Stellar Density error 0.05143

292.5799

0.00178

Planet Radius/Stellar Radius 0.105209

Semi-Major Axis (AU) 0.0327

Table 1. Full set of information about the Kepler-1624 b provided by the CSV file We searched the data by their KIC ID numbers. Then, we downloaded the light curves from every

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quarter–because it allows us to gain many data as possible that are mostly clean and errorless. The data are then stitched for each quarter and normalized. The light curves of all quarters are plotted and folded with period and transit epochs. The folded light curves are drawn with black-and-white color inversion.

Figure 3. Uncalibrated light curve of the Kepler-1624 b

Figure 4. Fully calibrated light curve of the Kepler-1624 b

3.3 Extraction of data for the training Typical png images are hard to be used in training for CNN models since the loss of data increases. Thus, we converted png images those are previously calibrated into numpy array form to train our model. Our code includes two np.array: X data and the Y data. X data is the np.array of the 256×256-sized images, while Y data includes CP or FP converted to [0,1], [1,0] form by the One-Hot Encoding. We extracted the data for the two np.array, saved as a two-dimensional npy file. In total, we finally obtained 1169 files of CP and 1117 files of FP, all of them in 256×256 size.

3.4 Construction of CNN Model After saving our data in 3.3, the X data and the Y data in the form of npy were distributed 4:1 in the test: 0.2 size to gather the data required for CNN training and verification. The distribution randomly changed every time the CNN model was trained.

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Our model was founded on the sequential model by Keras; we constructed our own model, most apt in classifying the light curves, by stacking layers with the final size of 6×6. Layers with 6×6 made the distinct characteristics of each graph to be well-represented. We also applied Dropouts in the middle of our code, so that the code can be committed to avoiding overfitting while improving accuracy. During training our model, we first put the Epoch value to be 100. Afterward, graphs for the accuracy and the loss were drawn to determine the range of the Epoch which showed the optimal points while considering the accuracy and the loss. We finally finished our training by using a median value of the range of the Epoch.

Figure 5. Accuracy graph of the CNN model trained in an apposite Epoch

Figure 6. Loss graph of the CNN model trained in an apposite Epoch CNN model was then saved as a h5 file. The model was later used for the verification of the accuracy using CP and FP light curves. Most importantly, we applied our model to the PC data, the candidates yet to be verified.

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4. Result 4.1 Testing Model

Figure 7. The overall result of testing the model The final accuracy of the model, tested with CP and FP light curves, showed 89.9%. We classified 314 PC data into CP and FP using our model, which showed 172 CPs and 142 FPs. The list is in the appendix. We adapted the model to each CP and FP dataset as investigating the accuracy. Among the 1169 CP data, 1124 were classified correctly while 45 were incorrect, resulting in 96.2% of accuracy. Correspondingly, among the 1117 FP data, 1004 were classified correctly while 113 were incorrect, resulting in 89.9% of accuracy.

4.2 Error Investigation Due to the small dataset, the accuracy showed a minor discrepancy up to ±5% every time we tested our model.

5. Conclusion The model we built was particularly effective in determining CP, yet 89.9% accuracy for FP data is not much of a defect. Thus, we believe that our model can be fully used in extracting the hot lists, which are candidates likely to be exoplanets. As our model lacked some consistency, in further investigation, we expect that using Generative Adversarial Networks (GANs), an alternative method for generating

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similar images as CNN, would produce a better result.

6. Appendix 6.1 Book of python codes Calibrating raw data from the archive to black and white images import os, io import numpy as np import matplotlib.pyplot as plt import pandas as pd import lightkurve as lk from PIL import Image, ImageOps from datetime import datetime MAX_NUM = 5000 DEP_CUT = (500, 37000) if not os.path.exists("./CP"): os.mkdir("./CP") if not os.path.exists("./FP"): os.mkdir("./FP") if not os.path.exists("./PC"): os.mkdir("./PC") flog = open(f"lc_info_{datetime.now().strftime('%Y%m%d%H%M%S')}.csv", "w") flog.write("disposition,id,koi,depth,period,duration,n_y,sig_y,avg_yerr\n") disposition_counts = [] for disposition in ['CP', 'FP', 'PC']: df_list = pd.read_csv(f'{disposition}_LIST.csv', skiprows=3, usecols=(3,4,13,15,17,19)) # sorting the list by DEPTH df_list = df_list.sort_values("Depth (ppm)", ascending=False) # counter for collecting number count = 1 for i, row in df_list.iterrows(): # collect only the finite LCs if count > MAX_NUM: break koi = f"{row[0]*100:07.0f}" id = f"{row[1]:09.0f}" # check if the target has been processed # if os.path.exists(f"./{disposition}/{id}_{koi}_lc_fold.png"): # count += 1 # print(f"{count:4d} [SKIP] {id} exists") # continue

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# read t0 and period for folding t0 = row[2] - 2454833 # convert BKJD period = row[3] depth = row[4] duration = row[5] # check if the csv of target exists if not os.path.exists(f"./CSV/{id}_{koi}_lc_all.csv"): print(f"{disposition} [ERR] NO LC") continue if np.isnan(depth): print(f"{disposition} [ERR] depth is nan") continue if (depth < DEP_CUT[0]) or (depth > DEP_CUT[1]): print(f"{disposition} [ERR] depth = {depth}") continue if period/(duration/24) > 500: print(f"{disposition} [ERR] period/duration = {period/(duration/24)}") continue # read the csv of the target print(f"{disposition} {count:4d} [READ] cat of {id}_{koi}") df_lc = pd.read_csv(f"./CSV/{id}_{koi}_lc_all.csv") # make the LC object from csv lc_all = lk.LightCurve(time=df_lc.time, flux=df_lc.flux, flux_err=df_lc.flux_err) print(f"{disposition} {count:4d} [OK] LC download") # plot the LC of all quarters plt.close('all') ax = lc_all.plot() ax.set_title(f"[{disposition}] {id}_{koi}") ax.figure.savefig(f"./{disposition}/{id}_{koi}_lc_all.png") # calc. and draw periodogram # #p = lc_all.to_periodogram(method='LombScargle') # p = lc_all.to_periodogram('bls', duration=0.1) # period = p.period_at_max_power # t0 = p.transit_time_at_max_power # dur = p.duration_at_max_power # dep = p.depth_at_max_power # fold the LC with period and transit epoch #lc_fold = lc_all.fold(period*2, t0) lc_fold = lc_all.fold(period, t0) x, y, yerr = lc_fold.time.value, lc_fold.flux.value, lc_fold.flux_err.value ymed, ymin = np.median(y), np.min(y) # ydel = ymed - ymin ydel = depth/500000 if not np.isnan(depth) else ymed - ymin

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# draw the folded LC plt.close('all') fig = plt.figure(num=1, figsize=(2.56,2.56)) ax = fig.add_axes([0,0,1,1]) x_start, x_end = -period*0.5, +period*0.5 #n_bins = max(3*period/(duration/24), 1024) dx = (x_end - x_start)/2048 lx, ly, ly_err = [], [], [] for x0 in np.arange(x_start, x_end, dx): ybin = y[(x >= x0) & (x <= x0+dx)] if len(ybin) == 0: continue lx.append(x0+dx/2) ly.append(np.median(ybin)) ly_err.append(np.std(ybin)) lx, ly, ly_err = np.array(lx), np.array(ly), np.array(ly_err) ax.fill_between(lx, ly-ly_err, ly+ly_err, color='k', alpha=0.5, edgecolor=None) ax.plot(lx, ly, 'k-', lw=1) # ax.scatter(x, y, 0.2, 'k', alpha=0.2) ax.set_xlim(-period*0.5, +period*0.5) ax.set_ylim(ymed-ydel, ymed+ydel) ax.set_axis_off() # save the plot to file object im_file = io.BytesIO() fig.savefig(im_file, format="png") # invert the plot to black and white neg_im = ImageOps.invert(Image.open(im_file).convert("RGB")) # save the inverted plot neg_im.save(f"./{disposition}/{id}_{koi}_lc_fold.png") # write the log sig_y = np.std(y) avg_yerr = np.mean(yerr) flog.write(f"{disposition},{id},{koi},{depth},{period},{duration},{len(x)} ,{sig_y},{avg_yerr}\n") count += 1 disposition_counts.append(count) flog.close() print("the number of CP, FP, PC: ", disposition_counts)

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Creating npy files by drawing the light curves of the suitable candidates meeting the conditions from sklearn.model_selection import train_test_split import numpy as np from glob import glob import cv2 import pandas as pd import os DEP_CUT = 0 NUM_CUT = 5000 cp_list = pd.read_csv(f'CP_LIST.csv', skiprows=3, usecols=(3,4,13,15,17,19)) #cp_list = cp_list.sort_values("Depth (ppm)", ascending=False) cp_list = cp_list[cp_list["Depth (ppm)"] > DEP_CUT] fp_list = pd.read_csv(f'FP_LIST.csv', skiprows=3, usecols=(3,4,13,15,17,19)) #fp_list = fp_list.sort_values("Depth (ppm)", ascending=False) fp_list = fp_list[fp_list["Depth (ppm)"] > DEP_CUT] dfs = [cp_list, fp_list] categories = ["CP","FP"] nb_classes = len(categories) image_w = 256 image_h = 256 X, Y, DEP = [], [], [] for idx, cat in enumerate(categories): #label = [0 for i in range(nb_classes)] #label[idx] = 1 label = True if (cat=="CP") else False df = dfs[idx] image_dir = f"./{cat}" #files = glob(image_dir+"/*_lc_fold.png") count = 0 for i, row in df.iterrows(): koi = f"{row[0]*100:07.0f}" id = f"{row[1]:09.0f}" depth = row[4] if depth < DEP_CUT: continue if count >= NUM_CUT: continue filename = f"{image_dir}/{id}_{koi}_lc_fold.png"

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if not os.path.exists(filename): print(f"[ERR] no png file of {id}_{koi}") continue gray = cv2.imread(filename,cv2.IMREAD_GRAYSCALE) gray = cv2.resize(gray, dsize=(image_w, image_h)) X.append(gray.copy()) Y.append(label) DEP.append(depth) count += 1 print(f"[OK] read png ({count}) {id}_{koi}") print(cat, label, count) X = np.array(X) Y = to_categorical(Y) Y = np.array(Y) DEP = np.array(DEP) #np.save(f"DDEP{DEP_CUT}_input_set", X) #np.save(f"DDEP{DEP_CUT}_label_set", Y) #np.save(f"BNUM{NUM_CUT}_input_set", X) #np.save(f"BNUM{NUM_CUT}_label_set", Y) #np.save(f"BRND{NUM_CUT}_input_set", X) #np.save(f"BRND{NUM_CUT}_label_set", Y) np.save(f"AEDEP500_37K_256_input_set", X) np.save(f"AEDEP500_37K_256_binary_label_set", Y) print("ok,", len(Y)) X_train, X_test, Y_train, Y_test = \ X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2) xy = (X_train, X_test, Y_train, Y_test) np.save(f"Model_train_test_set", xy) print("ok,", len(Y)) print("[OK] save train sets") print(f"CP={(Y==True).sum()}, FP={(Y==False).sum()}")

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Creating CNN model, adding layers, and training the model import tensorflow as tf from sklearn.model_selection import train_test_split from keras.models import Sequential from keras.layers import Convolution2D, MaxPooling2D from keras.layers import Activation, Dropout, Flatten, Dense import numpy as np from keras.layers import Dense, Flatten, Conv2D, MaxPooling2D from glob import glob import matplotlib.pyplot as plt from keras.utils import to_categorical from keras.preprocessing import image

categories = ["CP","FP"] X = np.load(".\AEDEP500_37K_256_input_set.npy",allow_pickle=True) Y = np.load(".\AEDEP500_37K_256_binary_label_set.npy",allow_pickle=True) nb_classes = len(categories) X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2) xy = (X_train, X_test, Y_train, Y_test) np.save(f"Model1_train_test_data_set", xy)

X_train = X_train.astype("float") / 256 X_test = X_test.astype("float") / 256 print('X_train shape:', X_train.shape)

model = Sequential() model.add(Conv2D(128, kernel_size=(3, 3), activation='relu', input_shape=(256, 256, 1))) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Conv2D( 32, kernel_size=(3, 3), activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Conv2D( 8, kernel_size=(3, 3), activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(rate=0.2)) model.add(Conv2D( 4, kernel_size=(3, 3), activation='relu')) model.add(Dropout(rate=0.2)) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Conv2D( 2, kernel_size=(3, 3), activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2)))

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model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dropout(rate=0.2)) model.add(Dense(2, activation='sigmoid')) model.summary() model.compile(loss='binary_crossentropy', optimizer='Adam', metrics=['accuracy']) hist = model.fit(X_train, Y_train, epochs=20, validation_data=(X_test, Y_test)) model.evaluate(X_test, Y_test) plt.plot(hist.history['loss'],color='b',label='Training Loss') plt.plot(hist.history['val_loss'],color='r',label='Validation Loss') plt.legend() plt.show() plt.plot(hist.history['accuracy'],color='b',label='Training Accuracy') plt.plot(hist.history['val_accuracy'],color='r',label='Validation Accuracy') plt.legend() plt.show() model.save("CP_FP_CNN.h5")

Applying the CNN model to the actual light curve png files and returning the result from keras.models import load_model import cv2 from PIL import Image import numpy as np import os import sys import fnmatch CNN = load_model('/content/CP_FP_CNN_relu_sigmoid_20230816B.h5') CNN.summary() from google.colab import drive drive.mount('/content/drive') path_dir = "/content/drive/MyDrive/HOBY/PC_image/" file_list = os.listdir(path_dir) for png in file_list: image = Image.open(path_dir + png) gray = cv2.imread(path_dir + png,cv2.IMREAD_GRAYSCALE) gray = cv2.resize(gray, dsize=(256, 256)) image = png.replace(".png",'') np.save("/content/drive/MyDrive/HOBY/PC/"+png, gray.copy())

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directory = '/content/drive/MyDrive/HOBY/PC' sys.stdout = open('/content/res1.txt', 'w') for file in os.listdir(directory) : f = os.path.join(directory, file) k = np.load(f) my_test = k.reshape(1,256,256,1)/256 res = CNN.predict(my_test) n = np.argmax(res) exo_class = ["FP","CP"] print(file.strip("_lc_fold.png.npy"), exo_class[n]) sys.stdout.close()

filelist = [] directory = '/content/drive/MyDrive/HOBY/PC' #CP or FP or PC for file in os.listdir(directory) : f = os.path.join(directory, file) k = np.load(f) my_test = k.reshape(1,256,256,1)/256 res = CNN.predict(my_test) n = np.argmax(res) exo_class = ["FP","CP"] file = file.strip("_lc_fold.png.npy"), exo_class[n] filelist.append(file) CP_num = 0 FP_num = 0 for i in filelist: b,c = i[0].split('_') print("KOI", end=' ') for j in range(5): print(c[j], end='') print(".", end='') for k in range(5,7): print(c[k],end='') print(",", i[1]) if i[1]=='CP': CP_num += 1 else: FP_num += 1 print("CP number:", CP_num) print("FP number:", FP_num)

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6.2. Result for PC Verification KOI 04303.01

KOI 01581.01

KOI 01455.01

KOI 04363.01

KOI 03689.01

KOI 00802.01

KOI 05435.01

KOI 08111.01

KOI 04636.01

KOI 05327.01

KOI 02052.01

KOI 08270.01

KOI 03909.01

KOI 05715.01

KOI 05480.01

KOI 01101.02

KOI 07847.01

KOI 06635.01

KOI 04670.01

KOI 00521.01

KOI 02150.01

KOI 00684.01

KOI 00841.04

KOI 07231.02

KOI 02480.01

KOI 03072.01

KOI 01708.01

KOI 05222.01

KOI 00950.01

KOI 05479.01

KOI 00797.01

KOI 01271.01

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7. References Abhishek Malik, Benjamin P Moster, Christian Obermeier. Exoplanet Detection using Machine Learning. 2021. Tinfei Lo, Jiani Fu. Analysis of Eclipsing Binary Stars and Identification of Exoplanets Using Transit Timing Variation Using data from TESS. 2022 Sangeetha Nandakumar, Mauro Barbieri, Jeremy Tregloan-ReedTaranga. Analysis of TESS Short Cadence data for years 1 and 2. 2022 George Clayton Sturrock, Brychan Manry, Sohail Rafiqi. Machine Learning Pipeline for Exoplanet Classification. 2019 Lightkurve Collaboration, José Vinícius de Miranda Cardoso, Christina Hedges, Michael GullySantiago, Nicholas Saunders, Ann Marie Cody, Thomas Barclay, Hall Oliver search by orcid, Sheila Sagear, Emma Turtelboom, Johnny Zhang, Andy Tzanidakis search by orcid, Ken Mighell, Jeff Coughlin, Keaton Bell search by orcid, Zach Berta-Thompson, Peter Williams, Jessie Dotson, Geert Barentsen. Lightkurve: Kepler and TESS time series analysis in Python. 2018 Rachel Akeson, Jessie Christiansen. TESS Follow-up Observing Program Working Group (TFOP WG): The ExoFOP-TESS Website. 2019

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Motion Abnormality Detector Detecting Fall Injuries Prevalent in Vulnerable Populations Author 1

Author 2

Author 3

Youn, Minhyuk

School Name

Seoul Foreign School

Full Name

Lim, Wonjun

School Name

Chadwick International

Full Name

Yu, Choeun

Korea International School, Jeju

Full Name (Last Name, First Name)

(Last Name, First Name)

School Name

ABSTRACT: This study aims to develop a Motion Abnormality Detector (MAD), a system that can detect aberrant movements such as falls, faints, and seizures for children with disabilities and physically challenged seniors to alert their guardians. According to the World Health Organization, “falls are the second leading cause of unintentional injury deaths worldwide” with an estimate that 684,000 people die due to falls globally [1]. Additionally, adults over 60 suffer the greatest number of falls, which is indicative of a need for attention to older, vulnerable populations [1]. MAD utilizes Computer Vision (CV) and Pose-Estimation Techniques (PET) to accurately capture abnormal movement in real-life situations based on heuristic algorithms derived from the analysis of patterns from video data. MAD, programmed on a Raspberry Pi, sets itself apart by expanding the range of movement for detection and can be mounted anywhere within the household. Distinguishing itself from conventional wearable smartdevices, the mounted MAD allows immediate and constant detection, ensuring efficient tracking. MAD can serve as a safety net for guardians caring for vulnerable individuals, and ensuring that in cases of emergencies, medical treatment can be delivered within the golden hour.

KEYWORDS: Abnormality Detection, Injury Alert System, Computer Vision, Pose Estimation, Raspberry Pi

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INTRODUCTION

1.1

BACKGROUND

Globally, falls are the second leading cause of unintentional injury and an estimate of 684,000 people die due to falls [1]. Vulnerable populations (i.e., seniors over the age of 60) are susceptible to such injuries as their range of movement begins to limit and their general health deteriorates. Injuries due to falls can be fatal, but also injuries like seizures and faints are equally as dangerous. Such injuries impact not only elders, but also individuals of all ages. Providing aid and medical services to individuals who are incapacitated is essential care. Especially as there is a golden hour time frame, where injuries are reversible if patients receive care within an allotted amount of time, having guardians alerted of when the individual has sustained the injury and provide care is impertinent.

1.2

DANGER CRITERIA

Danger criteria includes downward abnormal and aberrant movements, such as sudden falls, faints, seizures, etc. These situations can happen anywhere and anytime to anyone, making these situations all the more dangerous. The resulting injuries can vary depending on what movements have occurred, ranging from minimal physical injuries to death. Thus, accurately defining each situation (i.e. falls, faints, and seizures) will be adequately accounted for within the program.

1.3

PURPOSE

This study was devised with the larger aim of raising awareness about injuries due to falls, as well as seizures and faints, and the dire impacts it has on vulnerable populations. In this paper, we present a Motion Abnormality Detector (MAD) that accurately captures abnormal movement in real-life situations based on heuristic algorithms derived from the analysis of patterns from video data. MAD can provide immediate and constant detection, thus if any accidents occur, guardians are notified immediately and medical care can be delivered within the golden hour. The golden hour refers to the period of time immediately after a traumatic injury where if swift medical and surgical treatment is applied, death can be most likely prevented [2].

DEVELOPMENT PROCEDURES

2.1

Hardware Design and Implementation

We used the Raspberry Pi 4 Model B along with the camera module to develop MAD. The Raspberry Pi 4 Model B is a small, low-cost, single-board computer developed by the Raspberry Pi foundation widely used for Do-It-Yourself projects. The Raspberry Pi allowed us to conveniently set up the foundational hardware for MAD. We set up the Raspberry Pi 4 Model B with the recommended operating system Raspbian and connected it to the monitor for ease of use. Then, we attached the camera module to continuously monitor and read live video captures. The Raspberry Pi 4 Model B runs detect.py to run detections and is connected to Wifi to send text messages to the guardian using Naver Cloud Platform’s SMS API. The camera itself was hoisted on a wall so that Raspberry Pi can register and record footage throughout the entire room.

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Table 1. Hardware components

Figure 1. System design overview

2.2

Software Design

First, we utilized the OpenCV library to read and process live video from the Raspberry Pi’s camera module. OpenCV is a commonly used Python library for projects associated with computer vision. Then, we tracked the recorded movements using Google’s machine learning library, Mediapipe. Within the library, we utilized the Pose Landmark Model (BlazePose GHUM 3D) to detect key parts and the movements of the human body recorded in the frame. The pose solution detects 33 pose landmarks of the human body and each landmark has an output data of ‘x’, ’y’, ’z’, ‘visibility’ [3]. Respectively each represent: • ‘x’ and ‘y’: represents the normalized coordinates between 0.0 to 1.0 of a landmark in a frame, with ‘x’ being normalized by the width of the frame and ‘y’ being normalized by the height of the frame.

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• ‘z’: represents the depth of the landmark relative to the midpoint of the hips, with the origin being at the midpoint of the hips. A smaller value for z indicates that the landmark is closer to the camera. • ‘visibility’ is a value between 0.0 and 1.0 indicating the probability that the landmark is visible in the image, without being occluded. The Pose Landmark Model outputs the location of a certain parts of the human body in the form of ‘x’, ‘y’, and ‘z’ relative to the position in the frame, thus we were able to assume the output data as movement in a 3D space, which is identical to a room where MAD should be placed in.

Figure 2. Pose Landmark Model [3]

Table 2. Detecting Human Pose with Mediapipe [4]

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To detect falls, faints, and seizures, we needed to define a set of heuristic rules for the program to understand when such events occurred within detection. MAD only captures dangerous situations, so normal falls with quick recovery were purposefully excluded. Additionally, we accounted for the possibility of obscured facial features from certain angles, so MAD instead tracks the movement of the right shoulder or left shoulder and the right hip or left hip, depending on which shoulder has higher visibility given by the Pose Landmark Model detailed above. The Pose Landmark Model reads each frame individually and detects human movement. When a series of frames can be defined as {f1, f2, f3, f4 … fn} (f for frame) and detection of the shoulder with higher visibility is defined as {dfs1, dsf2, dsf3, dsf4 … dsfn} (dsf for detection of shoulder in frame), then acceleration in a 3D space between each consequent frame using the distance formula defined by (1): (xК - xЙ)² + (yК - yЙ)² + (zК - zЙ)² (1) So in our case, acceleration would be defined as (2): (dsf2.x - fds1.x)² + (dsf2.y - dsf1.y)² + (dsf2.z - dsf1.z)² (2) This computes the acceleration of the shoulder between each frame into a single number. In detecting falls and faints, we utilized University of Rzescow’s UR Fall Dataset to analyze video data and form a set of heuristic rules [4]. We fed the 20 videos in the dataset to the Pose Landmark Model and used the acceleration defined above as a key metric to capture how movement occurs when a fall happens. We used the same metrics and imitated falls and faints ourselves to gather more data. When a fall happens, we recognize that acceleration increases by more than 50% within 0.5 seconds compared to the 0.5 seconds before. We also recognized that the ‘y’ value of the shoulder when a fall happens is less than the ‘y’ value of the hip when standing up; the ‘y’ value represents height in the frame. Since a fall can be categorized with the prior conditions, we additionally set a time constraint to rule out the instances of falls that were immediately recovered. Falls that occur beyond the time constraint are defined as falls without recovery. Before the time constraint, the system recognizes marked falls as possible falls. Subsequently, we categorized faints as falls with a longer time constraint as the individual will be stationary on the ground for a longer period of time, compared to an average fall. Recovery was defined as the ‘y’ value of the shoulder reaching 50% of its height before the fall and the ‘x’ value changing more than 30% from the location of the fall. In detecting seizures, we couldn’t conclusively define one heuristic rule for a seizure because there are many types of seizures. Subsequently, there were no available public video datasets we can analyze accounting the design of MAD. Ultimately, we decided to detect tonic-clonic seizures, which is one of the most commonly experienced seizures [5]. Tonic-clonic seizures, also known as grand mal seizures, involve both stiffness and rhythmic jerking movements [6]. Tonic movements involve stiffness, while clonic movements involve rhythmic jerking [6]. Because we couldn’t record instances of tonic-clonic seizures, we had to focus on the available definition itself to determine a heuristic rule. We focused on the fact that tonic-clonic seizures consist of repetitive motions. We were already tracking ‘x’, ‘y’, ‘z’ points of the shoulder with higher visibility between each frame, so we could compute the difference in ‘y’ of the shoulder, which accounts for the height value, between consecutive frames. If the person in the frame is moving in one direction, the ‘y’ value difference would consistently be a positive or a negative value, and intuitively repetitive motions means that the difference of ‘y’ would be consistently changing from positive to negative value and vice versa. Using the definition of shoulder with higher visibility used in the fall, difference would be defined by (3): dsf2.y - dsf1.y (3) Therefore, we could define seizures as differences in ‘y’ rapidly changing from positive to negative values and vice versa. Also, to rule out regular repetitive motions such as dancing, exercising, or rocking back and forth, we only accounted for rapid changes with a time constraint. Finally, because rapid movements can be considered as a recovery due to our logic of fall detection, we decided to check for seizures regardless of possible fall.

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Definition of possible falls, falls, faints, seizures, and recovery by MAD: • Possible Fall: a 50% increase in acceleration headed downwards in 0.5 seconds compared to the acceleration in 0.5 seconds before. • Fall: minimal movement without recovery for continuing five seconds after possible fall. • Faint: minimal movement without recovery for continuing twenty seconds after possible fall. • Seizure: five sign changes in difference every second for continuing ten seconds. • Recovery: Shoulder height within the frame reaching 50% of its previous height before the fall and shoulder width changing 30% from the fall. Figure 2. Acceleration change when fall occurs

Figure 3. Height/width change when fall occurs

Figure 4. Height/width change when faint occurs

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Figure 5. Width/height change when recovery occurs

Lastly, when such events occur, an alert is sent via Naver Cloud Platform’s SMS API to send a text message to inform the guardian of the situation that has occurred, whether it be a fall, faint, seizure, etc. Within the message, the name of the location and person can be customized by the individual to best reflect the situation. Figure 6. Examples of MAD’s text alert

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2.4 Software Implementation Figure 7. Software Flow Diagram

The detect.py is constantly running on the Raspberry Pi 4 Model B with the camera module hoisted on the wall. Once a human body is detected within the frame, it starts tracking ‘x’, ‘y’, ‘z’ points of the shoulder and the ‘y’ points of the hip with higher visibility and checks for fall, faints, and seizures to send a text alert through an API. The code below imports the required libraries for MAD:

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Then, we set the initial variables for using Mediapipe’s Pose Landmark Model:

We also have to create a function to create a global dictionary that stores and update variables for detection:

Functions below define acceleration and difference as defined above:

Functions below detect fall and faint for each frame according to the definitions set above:

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Function below detect seizures for each frame according to the definitions set above:

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Next are functions to use Naver Cloud SMS API. The code below consists of a function to make signatures to use the API and a function that provides data to send a text alert through the API. We adapted Naver Cloud Platform’s instructions to create this method [7] :

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Finally, the execution of detect.py and function mad combines the functions defined above to 1) turn on the camera, 2) process each frame by performing pose detection, 3) calculate acceleration and height difference, 4) calls check for falls, faints, and seizures, 5) draw landmarks, and 6) display the resulting information on the frame:

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EXPERIMENT PROCEDURES, RESULTS & ANALYSES

3.1

Experiment Procedure of MAD

Three sets of experiments were conducted to verify the performance of MAD in detecting falls. Because faints were defined as minimal movement for 20 seconds following a fall, the experiment for faint was excluded. The experiments conducted were: Experiment on unused videos in the University of Rzescow’s UR Fall Dataset [4]. Experiments at home that we performed imitating falls in eight angles with Raspberry Pi. Videos from the University of Edinburgh’s CAVIAR Test Case Scenarios that contain walking, browsing, and resting [8]. One set of experiments were conducted to verify the performance of MAD in detecting seizures. Because there were no publicly available dataset that fits our needs, we used 3 Youtube videos posted by Epilepsy Foundation and Apollo Hospitals [9][10][11].

3.2

Experimental Results & Analysis of MAD

For the first fall experiment, we fed ten unused videos from the University of Rzescow’s UR Fall Dataset (video number: 21-30) into MAD to inspect if MAD can accurately identify falls [4]. Because these videos are only a few seconds long, it did not fit into our existing definitions of falls. Therefore, we only checked if a possible fall would be detected at the moment of the fall. We found that MAD detected all possible falls within the test dataset. Table 3. Fall Detection with MAD utilizing University of Rzecow’s UR Fall Dataset [4]

Figure 7. Detection of Dataset

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The second fall experiment was conducted by ourselves to inspect if MAD can capture falls at different angles. These were conducted through the Raspberry Pi. Testing eight different angles, MAD was able to capture all angles and identify them as a fall. Table 4. Fall detection with MAD utilizing personally captured footage

The third fall experiment was conducted to check if MAD falsely detects non-falls as falls. We fed 10 videos from the CAVIAR Test Case Scenarios that contain walking, browsing, and resting [8]. It is important to note that these videos were filmed at an angle that is different from how MAD is recommended to be placed. Though there were no false positives, there were three videos that MAD couldn’t detect the human being in the frame. We conclude that this can be attributed to the fact that the subject of the video was too far away from the camera of MAD. Alternatively, it can be attributed to MAD detecting too much noise, so it couldn’t detect the human being in the frame. Table 5. Detection with MAD [7]

In summary for the fall detection experiment, MAD was able to correctly identify 25 videos out of 28 tested, thus an accuracy rate of about 89%. For our seizure experiment, we used three Youtube videos from the Epilepsy Foundation and Apollo Hospitals as mentioned above. We also had to alter our ten seconds seizure rule because the length of seizures in these videos were all less than ten seconds. With these conditions, MAD was able to identify all three seizures with our heuristic rule from the definitions. Table 6. Seizure Detection with MAD [9] [10] [11]

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DISCUSSION

MAD could be used in a variety of locations, ranging from personal homes to hospitals, to alert guardians of danger with a certain level of accuracy and precision. However, there are several limitations to its current implementation that may impact its accuracy and effectiveness. One major limitation is the lack of human action video data that show falls, faints, and seizures from home environments. This can lead to edge cases in fall detection where the system produces false positives or false negatives. Without more data, MAD's ability to develop a more accurate heuristic rule for identifying seizures is hindered. As explained above, there isn’t a single type of seizure that everyone experiences. As such, a diversity of video data footage is impertinent to developing a more holistic and effective MAD. With the data we could find, we chose to focus only on one type of seizure, tonic-clonic seizures. Another limitation is that the current implementation of MAD relies on heuristic rules rather than deep learning models to detect falls, faints, and seizures. While heuristic rules can be effective in certain cases, deep learning models may offer greater accuracy and adaptability when it comes to detecting these scenarios. Therefore, further work on MAD could involve refactoring the current code to incorporate deep learning models, which could potentially improve the system's ability to accurately detect these types of events. Overall, the limitations of the MAD system are largely due to the lack of sufficient video data. In order to address these limitations and improve the accuracy of the system, it is beneficial to collaborate with research institutions or other organizations that have access to larger datasets and more resources for collecting and analyzing video data. By leveraging these resources, more thorough testing and refinement of the MAD system can lead to greater accuracy and effectiveness in detecting dangerous situations of falls, faints, and seizures

CONCLUSION

In summation, MAD has immense potential to positively impact individuals around the globe by detecting a variety of fall and fall-related injuries, then alerting guardians within the golden hour. By alerting guardians of the situation when it occurs, MAD provides preventionary healthcare. MAD’s greatest advantage is in its ability to provide prevention of worsening injuries by detecting the fall, providing alerts, and facilitating subsequent healthcare. While MAD is still in its early development state, there exists limitless potential to help save lives across the globe. As this idea is in its infancy, bred by a group of South Korean high school students, the possibility of MAD can be explored and fully achieved with the proper resources, time, and research. With further development, MAD can reach those who can benefit from this technology, ranging from children to elderly across the world. With proper prevention, unintentional injury deaths from falls can be avoided. In closing, MAD provides a solution to aid one of the most dire medical problems that society collectively faces.

ACKNOWLEDGEMENT The study and tangible developments of MAD would not be possible without the support and guidance of Yeon Sean Park, a Data Scientist at the University of California, Berkeley. He has been an incredible mentor online, fostering our interest in biomedical engineering research. Throughout the development of MAD, he has been a supportive mentor, answering our questions and queries. Undoubtedly, the results and success of MAD would be incomplete without the guidance of his mentorship.

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REFERENCES [1] (26 April 2021). World Health Organization. Retrieved from https://www.who.int/newsroom/fact-sheets/detail /falls [2] American College of Surgeons (2008). Atls, Advanced Trauma Life Support Program for Doctors. Amer College of Surgeons. ISBN 978-1880696316. [3] Github.io. Retrieved from https://google.github.io /mediapipe/solutions/pose.html [4] Bogdan Kwolek, Michal Kepski, Human fall detection on embedded platform using depth maps and wireless accelerometer, Computer Methods and Programs in Biomedicine, Volume 117, Issue 3, December 2014, Pages 489-501, ISSN 0169-2607 [5] Types of Seizures. (n.d.). Epilepsy Foundation. Retrieved December 26, 2022, from https:// www.epilepsy.com/parents-and-caregivers/talking-kids-about-epilepsy/types-seizures [6] Tonic-clonic Seizures. (n.d.). Epilepsy Foundation. Retrieved December 26, 2022, from https://www.epilepsy.com/what-is-epilepsy/seizure-types/tonic-clonic-seizures [7] Naver Cloud Platform. Retrieved from https://api.ncloud-docs.com/docs/aiapplication- service-sens-smsv2 [8] EC Funded CAVIAR project/IST 2001 37540, found at URL: http://homepages.inf.ed.ac.uk/rbf/ CAVIAR/ [9] Apollo Hospitals. (2012, September 28). Apollo Hospitals | First Aid in Seizure | What to do in case of seizure? [Video]. YouTube. https://www.youtube.com /watch?v=owXhSD7XwUk [10] Epilepsy Action. (2014, November 6). Epilepsy in schools: how to deal with a tonic clonic seizure [Video]. YouTube. https://www.youtube.com/ watch?v=olArThAgUd8 [11] Epilepsy Action. (2014, November 6). How to help if someone has a tonic clonic seizure Epilepsy Action Employer Toolkit [Video]. YouTube. https://www.youtube.com/watch? v=7N74EFyEhUA

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RESEARCH P

How much is enough sleep? Current status of sleep duration in South Korea after Covid 19.

Author 1

Full Name

Chang, Won-Jun

Asia Pacific International School

(Last Name, First Name)

School Name

KEYWORDS: sleep, duration, sleep disorder, Covid 19, health

Problem Statement Sleep duration is associated with various health outcomes, such as mortality, chronic diseases, and mental health1. Therefore, it is important to maintain a healthy sleep pattern and quality. Especially, Covid 19 has caused disruption in the sleep pattern and routine.

Objectives and Aims This study aimed to evaluate the current duration of sleep and sleep disorder in students and adults of South Korea. We plan to compare the current sleep duration with those from before Covid 19 to understand whether Covid 19 has caused disruption in the sleep pattern and routine in South Korea.

Background and Significance One study reported that the average sleep duration in South Korea was about 6.5 hours per day based on a survey by Gallup Korea in 20172. However, this figure is lower than the OECD average of 8.3 hours per day3. South Korea ranked in the worst level for sleep duration when compared to other countries3. Some of the reasons for dissatisfaction of sleep in South Korea are stress, noise, and temperature. Sleep duration is associated with various health outcomes, such as mortality, chronic diseases, and mental health. A meta-analysis of 16 studies found that both short (<6 hours) and long (>9 hours) sleep duration were associated with increased risk of all-cause mortality. Another meta-analysis of 22 studies found that short (<7 hours) and long (>8 hours) sleep duration was associated with increased risk of cardiovascular disease, diabetes, and obesity. Moreover, a systematic review of 75 studies found that sleep duration was related to various aspects of mental health, such as mood, cognition, and psychiatric disorders. Therefore, it is important to maintain a healthy sleep pattern and quality. There are many possible reasons for South Korea’s average sleep duration being lower than other countries. South Koreans are known for their strong work ethic and long working hours. Smartphones

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and other devices have made it easier for Koreans to stay connected with their work, even when they’re not in the office. South Korean students are known for their intense study habits and high academic expectations. Many students attend after-school programs or private tutoring sessions that can last until late at night, leaving little time for sleep. South Koreans are some of the highest consumers of coffee in the world. While caffeine can help people stay alert during the day, consuming too much can disrupt sleep patterns and lead to insomnia. South Korea is a densely populated country which can make it difficult for people to relax and get a good night’s sleep.

Research Design and Methods Web-based questionnaire was developed for this study. We will survey current duration of sleep in South Korea through Web-based questionnaire. We will compare the current sleep duration data acquired through Web-based questionnaire with existing statistics for sleep duration before and during Covid 19.

Anticipated Results and Potential Contribution We collected and examined the preliminary data gathered from 17 responses of the survey; results are as shown in graphs as below. We found Koreans sleep 6 to 8 hours per day. About 11% of the subjects reported having sleep problems. Survey also suggested that Koreans consume 1 to 2 cups of coffee per day. We will investigate how much people sleep duration has been affected by Covid 19 by comparing the duration of sleep in South Koreans before and after Covid 19.

Figure 1. Participant characteristics

Figure 2. Sleep duration and sleep disorder: Preliminary data

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Figure 3. Coffee consumption in South Korea

References 1. SH Kim et al., Sleep duration and mortality in Korean adults: a population-based prospective cohort study. BMC Public Health. 2020, 28;20(1):1623; doi: 10.1186/s12889-020-09720-3. 2. HJ Kim et al., The Relationship between Sleep Duration and Perceived Stress: Findings from the 2017 Community Health Survey in Korea. Int J Environ Res Public Health. 2019, 16, 3208; doi:10.3390/ijerph16173208 3. Tk Han et al., Is Sleep Duration Associated with Biological Age (BA)? : Analysis of (2010– 2015) South Korean NHANES Dataset South Korea Int J Environ Res Public Health. 2018, 14;15(9):2009; doi: 10.3390/ijerph15092009

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Exploring the Neural Underpinnings of Aesthetic Preferences in Design: A Multidisciplinary Analysis

Full Name

Choi, Yejune

Libertas Scholars College Prep

(Last Name, First Name)

School Name

KEYWORDS: Cognitive Neuroscience, Perceptual Judgment, Embodied Cognition, Cultural Relativity, Cross-Cultural Psychology, User-Centered Design, Affordances, Emotion Processing

Abstract This research explores the neural underpinnings of aesthetic preferences in design, integrating cognitive neuroscience, psychology, and design theory. Aesthetic experiences are found to be deeply rooted in cognitive processes within the brain. Cultural influences emphasize the need for cultural sensitivity in design, while user-centered design principles stress the integration of aesthetics and functionality. Neuroimaging techniques reveal distinct cognitive pathways during aesthetic judgments, underscoring the complexity of aesthetic perception. This interdisciplinary study contributes to a deeper understanding of design's neural foundations and its impact on user experiences.

Introduction This research explores the neural underpinnings of aesthetic preferences in design, integrating cognitive neuroscience, psychology, and design theory. Aesthetic experiences are found to be deeply rooted in cognitive processes within the brain. Cultural influences emphasize the need for cultural sensitivity in design, while user-centered design principles stress the integration of aesthetics and functionality. Neuroimaging techniques reveal distinct cognitive pathways during aesthetic judgments, underscoring the complexity of aesthetic perception. This interdisciplinary study contributes to a deeper understanding of design's neural foundations and its iIn an increasingly visual and design-centric world, the quest to understand the underlying neural mechanisms of aesthetic preferences holds profound significance. The intricate interplay between human cognition and design elements has been a subject of fascination for both psychologists and designers alike. This research endeavors to delve into the realm where psychology meets design, aiming to uncover the neural substrates that orchestrate the preferences for aesthetically pleasing designs. Through the lens of neuroscience, this investigation seeks to provide insight into how the brains respond to and appreciate the artistry embedded in various design choices. The central question driving this research can be succinctly articulated: What are the underlying neural mechanisms that govern aesthetic preferences in design? In other words, what happens in the brains

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when encountering a well-designed product, visual composition, or architectural space that captivates the senses and triggers a sense of aesthetic satisfaction? The connection between aesthetics and human psychology has been a subject of inquiry for centuries, dating back to the philosophical musings of Plato and Aristotle. Yet, it is only in recent decades that advances in neuroscience have allowed us to peer into the intricacies of the human brain and gain a deeper understanding of how aesthetic preferences are neurologically instantiated. The intersection of psychology and design is fertile ground for exploration, offering opportunities to uncover the cognitive and neural processes that underpin the appreciation of the visual world. The importance of this research lies in its potential to shed light on the enigmatic concept of aesthetics, which has far-reaching implications across diverse domains. In the realm of design, understanding the neural mechanisms of aesthetic preferences can guide designers in crafting products, interfaces, and environments that resonate with users on a profound level (Chen et al. 2019). In education, it can inform pedagogical approaches that leverage aesthetic principles to enhance learning outcomes (Cupchik et al. 2018). Moreover, insights into aesthetics have the potential to inform marketing strategies, cultural preservation efforts, and even therapeutic interventions (Vartanian et al. 2019). This research is not merely an intellectual pursuit but also holds practical significance for industries ranging from art and architecture to advertising and user experience design. By elucidating how the brain responds to design elements, it becomes possible to refine design principles, ultimately leading to the creation of more engaging, effective, and emotionally resonant products and environments. The exploration of the neural underpinnings of aesthetic preferences aligns with the contemporary zeitgeist, where design permeates every facet of human life. Navigating a world saturated with visual stimuli, the ability to decipher what makes a design aesthetically pleasing can empower individuals and industries alike. By unveiling the cognitive and neural mechanisms that govern the aesthetic sensibilities, this research transcends disciplinary boundaries and offers a holistic perspective on the relationship between human perception, cognition, and design.

Literature Review The exploration of the neural mechanisms underlying aesthetic preferences in design is deeply rooted in the philosophical contemplations of aesthetics. Plato and Aristotle, two luminaries of ancient philosophy, engaged in dialogues that laid the foundational ideas connecting beauty and cognition. Their discussions emphasized that aesthetics is intertwined with the fundamental cognitive processes, suggesting that the appreciation of beauty is not merely superficial but rooted in the very nature of the perception (Budd 2019). Contemporary psychology has taken up the mantle of this philosophical inquiry, seeking to unravel the cognitive processes that underlie aesthetic experiences. A pivotal study by Vartanian and colleagues (2019) ventured into the realm of architecture to explore the impact of design on aesthetic judgments and approach-avoidance decisions. Their use of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), unveiled a fascinating interplay between the built environment and neural responses. The findings suggest that variations in architectural elements, such as ceiling height and perceived enclosure, can significantly modulate neural activity, shedding light on the intricate relationship between design and the human brain's response to aesthetics. In the context of design theory, Chen and colleagues (2019) conducted an enlightening study that delved into the cultural dimensions of aesthetic perception. Their research underscores the idea that design choices are not universally appreciated but are deeply influenced by cultural background. By investigating how different cultural groups exhibit distinct preferences in face identification, this study

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highlights the role of cultural context in shaping aesthetic judgments. This finding has substantial implications for design professionals operating in multicultural contexts, emphasizing the importance of cultural sensitivity in design decisions. Furthermore, the nexus between aesthetics and functionality in design is a topic of paramount importance. Don Norman (2013), a renowned design theorist, posits that aesthetics and functionality are intimately intertwined. He argues that designs that successfully merge visual appeal with functional efficiency are more likely to create positive user experiences. Norman's work underscores the need for designers to consider the psychological aspects of design, particularly how it elicits emotional responses in users. This perspective aligns with the central theme of the research, emphasizing the neurocognitive processes that come into play when individuals encounter aesthetically pleasing designs. The burgeoning field of neuroaesthetics seeks to bridge the gap between aesthetics and neuroscience, ffering empirical insights into the neural substrates of aesthetic experiences. Cupchik and colleagues (2018) embarked on a neuroimaging study to investigate how viewing artworks triggers cognitive control and perceptual facilitation processes in the brain. Their findings provide empirical evidence that aesthetic experiences engage specific neural networks, shedding light on the intricate interplay between visual stimuli and cognitive processing. To facilitate this research, neuroimaging techniques such as fMRI and electroencephalography (EEG) have emerged as invaluable tools. Jacobsen and colleagues (2017) employed EEG to investigate the neural correlates of aesthetic image processing. Their study revealed differential responses in the brain to affective and cognitive judgments of aesthetics, offering nuanced insights into how distinct cognitive processes come into play when individuals evaluate the beauty of visual stimuli.ƒ

Research Questions The research questions lay the groundwork for in-depth exploration and investigation into the neural mechanisms that form the basis of aesthetic preferences in design, encompassing both theoretical and practical dimensions of the subject: How do neural mechanisms contribute to the formation of aesthetic preferences in design, and what are the key cognitive processes involved? To what extent does cultural background influence neural responses and aesthetic judgments when exposed to design elements, and how can cultural sensitivity be integrated into design practices? What are the neuroscientific and psychological implications of seamlessly integrating aesthetics and functionality in design, and how do these principles enhance user experiences? How do neuroimaging techniques, such as fMRI and EEG, reveal distinct neural pathways activated during affective and cognitive judgments of aesthetics, and what does this reveal about the multifaceted nature of aesthetic perception? What future directions in neuroaesthetics research can utilize neuroimaging techniques to investigate the neural mechanisms underlying specific design elements, such as color, symmetry, or form, and how can this deepen the understanding of aesthetic preferences in design?

Research Design and Methods The research method is a practical approach to investigating the underlying neural mechanisms of aesthetic preferences in design. By systematically reviewing existing research, analyzing findings, and analyzing patterns in the literature, this study aims to contribute to the understanding of the cognitive and neural processes associated with aesthetic experiences in design. Data Collection As the primary research method for this project, an extensive literature review will be conducted. This review will encompass academic journals, books, and reputable online sources, focusing on studies that investigate the neural mechanisms of aesthetic preferences in design. The following steps will be followed: Utilize online academic databases (e.g., Google Scholar, JSTOR, PubMed) to access peer-

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reviewed articles and publications. Search for relevant keywords such as "neuroaesthetics," "aesthetic preferences," "design and neuroscience," and "cognitive response to design." Analyze the selected literature, with a focus on identifying key findings related to neural responses to design elements and aesthetics. Data Analysis After gathering a substantial body of literature, the findings will be analyzed and organized to identify common themes, patterns, and insights. This step will involve: Creating an annotated bibliography or summary of each relevant source. Identifying key concepts, methodologies, and theories explored in the literature. Analyzing and comparing the neuroscientific evidence and psychological theories related to aesthetic preferences in design. Ethical Considerations Since this research does not involve human subjects, ethical review and approval are not required. However, it is essential to adhere to ethical guidelines when citing and referencing the work of other researchers to avoid plagiarism. Research Limitations It is important to acknowledge certain limitations of this research method, including the potential for bias in the selection of literature and the reliance on existing studies rather than original data collection. Additionally, the quality and availability of internet resources may vary.

Research Schedule The research schedule of 12 weeks will encompass a comprehensive exploration of the neural mechanisms that underlie aesthetic preferences in design. This research schedule outlines key phases and timelines, offering a roadmap for a methodical and insightful investigation. Weeks 1-2: Literature Review In the initial two weeks, the focus is on setting clear research objectives and formulating pertinent research questions. Extensive searches using academic databases are conducted to identify relevant literature from various sources. The process includes reading and analyzing peer-reviewed articles and books to compile an annotated bibliography, laying the groundwork for the research. Weeks 3-4: Literature Review Continuing into the third and fourth weeks, the literature review phase is characterized by an in-depth exploration of existing knowledge. This phase aims to identify common themes, patterns, and theoretical frameworks that emerge from the reviewed literature. Additionally, the goal is to summarize key findings and insights, thereby refining the research objectives based on emerging insights. Weeks 5-6: Synthesis and Analysis Moving into the fifth and sixth weeks, the synthesis and analysis phase begins. Here, the collected findings from the literature review are meticulously synthesized and organized. The focus is on analyzing the integration of scientific theories and concepts that are relevant to the research. Simultaneously, the discussion section is initiated, and initial implications for both theoretical and practical aspects in design are identified. Weeks 7-8: Methodological Approach The subsequent two weeks are dedicated to defining the methodological approach for the research. This

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phase entails selecting the most appropriate research methods and tools to be employed. Clear criteria for selecting literature and data sources are established to maintain rigor and relevance throughout the project. Furthermore, reference management software is integrated to enhance organizational efficiency. Weeks 9-10: Data Collection and Analysis As the research enters the ninth and tenth weeks, the focus remains on data collection and initial analysis. Given that the research predominantly relies on a comprehensive literature review, these weeks primarily involve the ongoing acquisition and extraction of pertinent literature. The methodology for data analysis is fine-tuned, and potential gaps and areas for more in-depth exploration are identified. The discussion section is further developed, aligning with the ongoing analysis. Weeks 11-12: Discussion and Conclusion In the final two weeks, the emphasis is on the discussion and conclusion phases of the research. These weeks mark the critical juncture where the collected findings are analyzed and interpreted, with a focus on their relevance to the research question. Implications of the research for the fields of design, psychology, and neuroscience are emphasized. Possible directions for future research are explored, including the potential integration of neuroimaging techniques. Finally, the research is summarized, highlighting key takeaways and contributions. The research document is meticulously reviewed and prepared for submission.

Research Design and Methods The exploration of the neural mechanisms underlying aesthetic preferences in design has uncovered a trove of scientific theories, empirical data, and profound insights. This section delves deeper into the core theories and empirical findings, offering an extensive understanding of the interplay between aesthetics, psychology, neuroscience, and design. Neuroaesthetics: A Multidisciplinary Frontier Neuroaesthetics represents an interdisciplinary nexus where cognitive neuroscience, psychology, and aesthetics converge. It springs from the premise that beauty and aesthetics are not elusive abstractions but phenomena rooted in the neural substrates of the human brain (Cela-Conde et al., 2011). Neuroaesthetics seeks to reconcile the subjectivity of aesthetic preferences with empirical inquiry by unraveling the neural processes responsible for aesthetic experiences. This burgeoning field draws upon theories of visual processing, such as Marr's computational theory (Marr, 1982), which postulates that the brain processes visual information in multiple stages, from low-level features to high-level abstractions. Unveiling the Neural Correlates of Aesthetic Preferences Cupchik and colleagues' (2018) seminal study, which harnessed advanced neuroimaging techniques including functional magnetic resonance imaging (fMRI), peeled back the layers of the neural landscape governing aesthetic experiences. When participants were exposed to artworks, fMRI revealed heightened activity in specific brain regions: the anterior cingulate cortex, the ventral striatum, and the orbitofrontal cortex. These regions are intricately linked to cognitive control, emotional processing, and reward perception (Vartanian, 2016). The empirical evidence thus furnishes substance to the notion that aesthetic preferences are not confined to the whims of individual taste but are grounded in quantifiable neurocognitive responses. Cultural Dimensions of Aesthetic Perception Chen and colleagues' (2019) incisive exploration into the cultural dimensions of aesthetic perception uncovers a fascinating facet of aesthetics. Their research unearths that individuals from diverse cultural backgrounds exhibit distinct preferences in spatial frequency tuning for face identification. Cultural

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psychology, informed by the works of scholars like Nisbett and Miyamoto (2005), asserts that culture shapes not only cognitive processes but also perceptual frameworks. This theory posits that cultural diversity in aesthetic preferences reflects the amalgamation of neural processes and sociocultural influences, demonstrating the intricate interplay between biology and culture in shaping the aesthetic sensibilities. The Aesthetic-Usability Effect: Merging Beauty and Functionality Don Norman's theory of the "Aesthetic-Usability Effect" (Norman, 2002) offers a pragmatic lens through which to view the aesthetic dimension of design. This theory contends that aesthetically pleasing designs not only captivate the eye but also enhance perceived usability and functionality, even when objective functionality remains unchanged. Empirical studies corroborate this phenomenon. For instance, Tractinsky and colleagues (2000) demonstrated that products perceived as more beautiful were more likely to be forgiven for user errors, leading to heightened user satisfaction and perceived usability. This theory illuminates the potent synergy between aesthetics and functionality in design. The Multifaceted Nature of Aesthetic Perception Jacobsen and colleagues' (2017) intricate inquiry into the multifaceted nature of aesthetic perception uncovers a dichotomy in neural engagement during affective and cognitive judgments of aesthetics. Their findings echo the dual-process theory of cognition (Evans & Stanovich, 2013), postulating that aesthetic appreciation involves the orchestration of intuitive, emotion-driven processes and deliberate, cognition-infused processes, contingent upon the nature of the judgment. This duality underscores that aesthetic perception is not a monolithic construct but a symphony of cognitive and emotional responses in the brain.

Discussion The exploration into the neural mechanisms underpinning aesthetic preferences in design has yielded a rich tapestry of scientific insights. This section delves into the implications of these findings, discusses the limitations of the research, and outlines promising future directions for the field. Implications of the Results The results presented in the preceding sections hold significant implications for several domains, including design theory, cultural sensitivity in design, and the understanding of the human brain. The convergence of neuroaesthetics and design theory reveals that aesthetic preferences are not arbitrary but grounded in quantifiable neurocognitive responses. Design professionals can harness this knowledge to create products, environments, and interfaces that resonate with users on a neurocognitive level. By integrating principles from neuroaesthetics, designers can strive to enhance the visual appeal and functionality of their creations, aligning aesthetics with usability (Norman, 2002). The exploration of cultural dimensions in aesthetic perception emphasizes the pivotal role of cultural context in shaping aesthetic preferences. Designers operating in multicultural contexts can draw upon these insights to tailor their creations, fostering greater inclusivity and resonance with diverse audiences. Recognizing that aesthetic sensibilities are culturally contingent underscores the need for designers to transcend ethnocentrism and consider the cultural backgrounds and expectations of their target users (Chen et al., 2019). The revelation of distinct neural pathways involved in affective and cognitive judgments of aesthetics deepens the understanding of aesthetic perception. This nuanced perspective underscores that aesthetic appreciation is not a monolithic construct but a dynamic interplay of cognitive and emotional responses in the brain. Such insights pave the way for more targeted investigations into the neural processes underlying specific aesthetic elements, such as color, symmetry, or composition.

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Limitations While this research provides valuable insights, it is important to acknowledge its limitations. This study is reliant on existing research and literature reviews, lacking the original empirical data that experimental studies could provide. While synthesizing existing findings enriches the understanding, future research should incorporate original experiments to validate and expand upon these insights. The exploration of cultural dimensions in aesthetic perception hints at the influence of culture but does not offer exhaustive cross-cultural comparisons. Future studies should engage in more extensive crosscultural investigations to validate and refine the understanding of cultural influences on aesthetics. The reliance on neuroimaging techniques has methodological limitations, including the cost and access to neuroimaging equipment. Future research should explore alternative methodologies, such as online surveys and behavioral experiments, to make these studies more accessible and inclusive. Future Directions Building upon the foundations laid by this research, several promising avenues for future exploration emerge. Investigate how specific aesthetic elements (e.g., color, symmetry, complexity) modulate neural responses. By isolating these elements, researchers can provide a more granular understanding of the neural processes underpinning aesthetic preferences. Conduct cross-cultural neuroaesthetic studies that encompass a broader spectrum of cultures and regions. This will deepen the understanding of how cultural variations influence neural responses to aesthetics. Translate neuroaesthetic insights into practical design principles. Develop guidelines that assist designers in leveraging neuroscientific findings to create products and environments that optimize both aesthetics and functionality.

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References Budd, M. (2019). The Aesthetic Appreciation of Nature. Stanford Encyclopedia of Philosophy. Cela-Conde, C. J., Marty, G., Maestú, F., Ortiz, T., Munar, E., Fernández, A., ... & Quesney, F. (2011). Activation of the prefrontal cortex in the human visual aesthetic perception. Proceedings of the National Academy of Sciences, 108(12), 1-6. Chen, Y., Vizioli, L., Zhang, X., & Caldara, R. (2019). Culture shapes spatial frequency tuning for face identification. Journal of Experimental Psychology: Human Perception and Performance, 45(9), 1182-1191. Cupchik, G. C., Vartanian, O., Crawley, A., & Mikulis, D. J. (2018). Viewing artworks: Contributions of cognitive control and perceptual facilitation to aesthetic experience. Brain and Cognition, 123, 128-138. Evans, J. S. B. T., & Stanovich, K. E. (2013). Dual-process theories of higher cognition: Advancing the debate. Perspectives on Psychological Science, 8(3), 223-241. Jacobsen, T., Höfel, L., & Spindler, M. (2017). EEG correlates of aesthetic image processing: Differential responses to affective and cognitive judgments. The Open Neuroimaging Journal, 11(1), 22-30. Kitayama, S., & Uskul, A. K. (2011). Culture, mind, and the brain: Current evidence and future directions. Annual Review of Psychology, 62, 419-449. Marr, D. (1982). Vision: A computational investigation into the human representation and processing of visual information. W. H. Freeman. Nisbett, R. E., & Miyamoto, Y. (2005). The influence of culture: Holistic versus analytic perception. Trends in Cognitive Sciences, 9(10), 467-473. Norman, D. A. (2013). The Design of Everyday Things. Basic Books. Norman, D. A. (2002). Emotion and design: Attractive things work better. Interactions, 9(4), 36-42. Tractinsky, N., Katz, A. S., & Ikar, D. (2000). What is beautiful is usable. Interacting with Computers, 13(2), 127-145. Vartanian, O., Navarrete, G., Chatterjee, A., Fich, L. B., Leder, H., Modrono, C., ... & Skov, M. (2019). Architectural design and the brain: Effects of ceiling height and perceived enclosure on beauty judgments and approach-avoidance decisions. Journal of Environmental Psychology, 65, 101318. Vartanian, O. (2016). Neuroscience of aesthetics. Annals of the New York Academy of Sciences, 1369(1), 172-194.

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Assessing the Environmental Impact of Electric Vehicle Batteries: Towards Sustainable Solutions and Future Outlooks Full Name

Hwang, Yujin

Saint Johnsbury Academy Jeju

(Last Name, First Name)

School Name

KEYWORDS: EV batteries, environmental impact, life cycle assessment, raw material extraction, emissions, health risks, safety, battery recycling, sustainable practices, alternative battery chemistries, recycling technologies, resource conservation, technological innovation, regulatory development

ABSTRACT The research explores the environmental impact of electric vehicle (EV) batteries and urges sustainable solutions to mitigate long-term damage. The study employs a comprehensive literature review methodology, utilizing internet resources and a laptop, while excluding interviews and experiments. The research investigates the entire life cycle of EV batteries, from raw material extraction to recycling, identifying potential health risks and environmental damage during operation and assessing limitations in current recycling methods. It emphasizes the future outlook for sustainable EV batteries and underscores the urgency of implementing eco-friendly practices to minimize the environmental harm caused by batteries in the EV industry. The results reveal historical parallels in resource-intensive mining practices, safety concerns, and recycling efforts, shedding light on the evolution of environmental awareness, technological progress, and regulatory responses. This research contributes to the ongoing discourse on sustainable transportation and informs future research and policy development in the EV sector.

INTRODUCTION The burgeoning electric vehicle (EV) industry has garnered significant attention in recent years, serving as a linchpin in global efforts to mitigate climate change and reduce greenhouse gas emissions (Jones et al. 2020; Smith 2019). Central to this transformative shift towards sustainable transportation are the lithium-ion batteries that power EVs, enabling them to travel long distances while producing zero tailpipe emissions (Smith 2019). However, beneath the veneer of eco-friendliness, an essential and complex question emerges: What is the true environmental impact of electric vehicle batteries? This research paper embarks on an in-depth exploration of the multifaceted environmental implications associated with EV batteries, driven by a profound imperative to advocate for sustainable solutions that can mitigate the long-term ecological damage they may entail. The central research question guiding this study is both comprehensive and pressing: What can be done to comprehensively assess and

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address the environmental impact of electric vehicle batteries, from the extraction of raw materials to their end-of-life recycling, while concurrently identifying potential health risks and environmental harm during their operational lifetime? The rationale behind this research question is rooted in the remarkable ascent of electric vehicles as a potential panacea for environmentally-conscious transportation (Jones et al. 2020). As nations worldwide adopt increasingly ambitious emissions reduction targets, electric vehicles are emerging as a critical tool in the global fight against climate change (Smith 2019). Therefore, it becomes crucial to scrutinize the complete life cycle of EV batteries, evaluating their environmental footprint from the outset of raw material procurement through their operational phase and ultimately to their recycling or disposal. Amidst the optimism surrounding electric vehicles, it is incumbent upon us to critically assess the potential environmental and health ramifications that may accompany their widespread adoption (Jones et al. 2020). In doing so, the study highlights the integral role of EV battery sustainability in the broader context of achieving global emissions reduction goals and promoting environmentally responsible mobility solutions. Furthermore, this research endeavors to uncover the limitations of existing battery recycling methods, shedding light on areas where improvements are urgently needed (Smith 2019). Recycling is a linchpin in the quest for more sustainable batteries, as it plays a pivotal role in reducing the overall environmental impact of these energy storage systems. In tandem, this paper aims to cast a forward-looking gaze on the future prospects of sustainable electric vehicle batteries, underlining the pressing need to implement environmentally friendly practices and technologies (Jones et al. 2020). By delving into these dimensions, this study seeks to contribute to the ongoing discourse on sustainable transportation and emphasize the pivotal role of assessing EV battery environmental impact in achieving a greener and more sustainable future.

LITERATURE REVIEW The environmental impact of electric vehicle (EV) batteries is a topic of growing concern, reflective of the burgeoning global interest in sustainable transportation (Jones et al. 2020; Smith 2019). As EVs become increasingly popular as a means to mitigate climate change and reduce greenhouse gas emissions, it is crucial to critically examine the life cycle of EV batteries, from raw material extraction to recycling, in order to comprehend their overall ecological footprint (Smith 2019; Anair et al. 2012).

Life Cycle Assessment of EV Batteries The concept of life cycle assessment (LCA) in the context of electric vehicle (EV) batteries has gained prominence as a systematic approach to evaluate their environmental impact over the entire life cycle. Historically, LCAs emerged as a response to growing concerns about the environmental consequences of industrialization and the need to quantify and reduce these impacts (Frischknecht et al. 2006). Since then, LCAs have been applied to a range of products and technologies, including EV batteries. LCA studies of EV batteries have revealed that the extraction and processing of raw materials are crucial stages in understanding their environmental impact. Lithium-ion batteries, for instance, rely on minerals like lithium, cobalt, and nickel, which are often obtained through resource-intensive mining operations (Graedel et al. 2015). The historical context of mining and resource extraction underscores the need for sustainable sourcing practices and the mitigation of ecological consequences in these processes (Graedel et al. 2015). Moreover, LCAs have shown that the energy consumption and emissions associated with EVs depend on various factors, including the source of electricity used for charging. This aspect harks back to historical discussions about energy sources and their environmental implications, echoing the debates surrounding the transition from fossil fuels to cleaner energy alternatives (Hawkins et al. 2013).

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Health Risks and Environmental Damage The operational phase of EV batteries, marked by their use in electric vehicles, introduces potential health risks and environmental harm. Historical parallels can be drawn to the early days of the automotive industry when the environmental and health impacts of gasoline-powered vehicles became evident. Air pollution from exhaust emissions and the health effects of leaded gasoline are examples of issues that led to regulatory interventions (Abbott et al. 2011). In the case of lithium-ion batteries, the use of hazardous materials and chemicals in their production and disposal has raised concerns similar to those surrounding the use of leaded gasoline. The historical context of chemical safety regulations and workplace safety standards informs the current discussions on mitigating risks associated with battery manufacturing and disposal (Abbott et al. 2011). Furthermore, the potential for fires and thermal runaway events in EV batteries during their operational life has historical analogs in early technological developments. For instance, the history of early electrical systems and batteries is replete with incidents of fires and accidents, underscoring the importance of safety considerations in the adoption of new technologies (Larsson et al. 2020).

Battery Recycling and Its Limitations The recycling of EV batteries is often seen as a solution to mitigate the environmental impact of their disposal, echoing historical efforts to reduce waste and promote resource conservation. Recycling, as a concept, has evolved over time, driven by growing concerns about resource depletion and environmental pollution (Stephens and Bauer 2017). In the context of battery recycling, historical milestones include the establishment of recycling infrastructure for lead-acid batteries, driven by the recognition of the toxic nature of lead and the need to prevent environmental contamination (Stephens and Bauer 2017). The limitations faced by existing recycling methods for lithium-ion batteries, including issues related to complex battery chemistries and the lack of standardized processes, underscore the ongoing challenges in adapting recycling practices to evolving technologies (Dunn et al. 2015).

Future Outlook for Sustainable EV Batteries The future outlook for sustainable EV batteries represents a continuum of innovation and progress in the field of energy storage. Historically, technological advancements have often been driven by environmental and societal imperatives. For instance, the development of catalytic converters in automobiles was a response to growing concerns about air pollution and the need for cleaner exhaust emissions (Zhang et al. 2020). In the realm of sustainable EV batteries, the pursuit of alternative battery chemistries, such as solid-state and lithium-sulfur batteries, can be seen as part of a broader historical trend of seeking cleaner and more efficient technologies (Liu et al. 2018). The historical context of technological innovation underscores the potential for breakthroughs that can reduce the environmental footprint of batteries. Additionally, efforts to improve recycling technologies and increase recovery rates align with historical initiatives to reduce waste and promote circular economies. The historical context of waste management and resource conservation informs contemporary endeavors to enhance recycling processes and reduce the environmental impact of battery disposal (Stephens and Bauer 2017). Examining these historical parallels provides valuable insights into the current discourse on sustainable transportation and the urgent need to address the environmental challenges associated with EV batteries.

RESEARCH QUESTIONS The research questions provide a comprehensive framework for investigating the environmental impact of EV batteries, incorporating historical context and contemporary sustainability challenges: How does

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the life cycle assessment (LCA) methodology contribute to the understanding of the environmental impact of EV batteries, and what historical parallels can be drawn to resource-intensive mining practices in the battery industry? What are the key factors influencing the environmental impact of EV batteries during their operational phase, and how do they relate to historical discussions on vehicle efficiency and emissions? What are the health risks associated with the production and operation of EV batteries, and how do they align with historical concerns about workplace safety and hazardous materials in industrial settings? What are the challenges and limitations faced by current recycling methods for EV batteries, and how do they resonate with historical efforts to establish efficient recycling processes for emerging technologies? What is the future outlook for sustainable EV batteries, including alternative battery chemistries and recycling technologies, and how does it align with historical trends of technological innovation and regulatory development in response to environmental challenges?

RESEARCH DESIGN AND METHODS The research methodology is centered on a comprehensive literature review, designed to critically examine existing literature and synthesize knowledge on the environmental impact of electric vehicle (EV) batteries, while also addressing the broader context of sustainability in the EV industry.

Data Collection The primary data collection method for this research involves a systematic review of academic papers, reports, articles, and relevant online resources. The literature search will encompass reputable academic databases such as PubMed, IEEE Xplore, Google Scholar, and institutional libraries. The internet will serve as the primary source for accessing and retrieving relevant information, including research papers, reports, government publications, and industry news. This data will be collected through keywordbased searches using search engines.

Data Analysis The collected literature will be reviewed and synthesized to identify key themes, trends, and findings related to the environmental impact of EV batteries. This synthesis will include an analysis of research methodologies, data sources, and the evolution of research in this field. Subsequently, a comparative analysis of different studies will be conducted to highlight variations in findings, methodologies, and the geographical or temporal context in which the research was conducted.

Ethical Considerations Since this research relies exclusively on existing literature and internet resources, ethical considerations primarily pertain to proper citation and attribution. Care will be taken to accurately cite all sources and provide proper attribution to authors and publications.

Limitations The quality and quantity of available information on the internet may vary, and not all sources may be peer-reviewed. Therefore, careful consideration will be given to the credibility and reliability of the sources used. The literature review may be influenced by the availability of data and research bias in the selected studies. Efforts will be made to include a diverse range of sources and perspectives. Also, more recent developments and studies may not be included in the analysis.

RESEARCH SCHEDULE In the context of a 12-week research project focused on exploring the environmental impact of electric vehicle (EV) batteries, the schedule plays a critical role in ensuring that the research objectives are met efficiently and effectively.

Week 1-2: Project Initiation and Planning

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The inception of any research project is marked by the need to lay a strong foundation. In the first week, the researcher embarks on defining the research objectives, which serve as the guiding stars throughout the study. Simultaneously, preliminary literature review commences to identify existing knowledge and gaps in the chosen field. During the second week, meticulous planning takes center stage. With research questions honed, the researcher meticulously crafts a comprehensive research plan. This plan includes milestones, tasks, and deadlines, setting the trajectory for the weeks to come.

Week 3-4: Literature Review The subsequent phase involves an exhaustive dive into the existing body of knowledge. Weeks three and four are dedicated to an in-depth literature review, drawing from an array of sources. The researcher mines relevant academic papers, reports, articles, and online resources. As the research schedule unfolds, the review takes shape, transforming into a valuable repository of insights.

Week 5-6: Data Collection and Compilation Week five ushers in the era of data collection. Armed with the knowledge gathered in the previous phase, the researcher embarks on a journey to gather data from various online sources. Simultaneously, a meticulous organization of the findings begins. A reference database is curated, ensuring that citations and attributions are flawless. The following week maintains the focus on data collection and compilation. This stage is marked by diligence, as the researcher endeavors to ensure that no relevant information is left uncollected.

Week 7-8: Data Analysis and Synthesis With a rich dataset in hand, week seven sees the initiation of data analysis. It's a process of unraveling the intricacies of the information gathered. Key themes begin to emerge, and connections between disparate sources become apparent. Week eight continues the process of analysis while introducing the vital aspect of synthesis. It's here that the research starts taking a coherent form. Findings are woven together into a narrative that will eventually shape the research paper.

Week 9-10: Writing the Research Paper As the project crosses the halfway point, the focus shifts toward writing. Week nine marks the commencement of drafting the research paper. The first sections to receive attention are the introduction and literature review. These sections serve as the backbone of the research, providing context and framing the subsequent discussion. Week ten is dedicated to expanding the paper. The methodology, results, and discussion sections come into focus. It's a period of reflection and analysis, as the researcher endeavors to present the findings clearly and coherently.

Week 11: Finalizing the Paper As the research project nears its conclusion, the eleventh week is designated for finalizing the paper. It's a phase of review and revision, with meticulous attention to detail. The researcher ensures that the paper maintains clarity, is well-organized, and adheres to proper citation practices. Supplementary elements, such as tables, figures, and appendices, are introduced where necessary.

Week 12: Proofreading and Submission The final week of the research schedule is reserved for proofreading and final preparations. The researcher carefully scrutinizes the entire paper, hunting for grammar, spelling, and formatting errors.

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References are reviewed and formatted to perfection. With the research paper now in its most refined state, it's time for submission.

RESULTS The results of this research, which primarily relied on a comprehensive literature review, offer valuable insights into the environmental impact of electric vehicle (EV) batteries and the broader context of sustainability within the EV industry.

Life Cycle Assessment (LCA) of EV Batteries The life cycle assessment (LCA) methodology has played a pivotal role in evaluating the environmental impact of EV batteries. LCA, originally developed in the 1960s as a tool for assessing the environmental impact of products, has evolved significantly over the decades (Frischknecht et al. 2006). It gained prominence in the battery industry as a means to quantify the ecological footprint of batteries (Notter et al. 2010). Research consistently underscores the importance of raw material extraction in the life cycle of EV batteries. Historical parallels can be drawn to resource-intensive mining practices dating back to the industrial revolution. The extraction of minerals like lithium, cobalt, and nickel involves extensive energy consumption and environmental consequences, reminiscent of historical mining operations (Graedel et al. 2015). Variations in environmental impact assessments stem from factors such as geographical location and regional differences in mining practices. For instance, the environmental impact of lithium extraction can differ significantly between lithium-rich regions like the Lithium Triangle in South America and lithium production in Australia (Graedel et al. 2015).

Operational Phase and Emissions Studies on the operational phase of EV batteries have delved into energy efficiency and emissions during vehicle use. This aspect has historical parallels with early debates on the efficiency and emissions of internal combustion engine vehicles (Hawkins et al. 2013). The source of electricity used for charging plays a pivotal role in determining the environmental impact of EVs. Regions with cleaner energy grids historically correlate with lower emissions from electric vehicles. This dynamic reflects broader historical trends in the transition from fossil fuels to cleaner energy sources (Hawkins et al. 2013). Research emphasizes the importance of driving patterns and vehicle efficiency. Historical discussions on fuel efficiency and vehicle maintenance harken back to the early days of the automotive industry when fuel consumption and emissions were central concerns (Hawkins et al. 2013).

Health Risks and Safety The use of hazardous materials and chemicals in EV battery production has historical parallels with industrial safety concerns dating back to the early 20th century. Workplace safety standards and environmental regulations have evolved over time in response to these concerns (Abbott et al. 2011). Incidents of battery fires and thermal runaway events during the operational life of EVs have historical precedents in early electrical systems. Historical records document accidents related to early battery technologies, contributing to safety improvements over time (Larsson et al. 2020).

Battery Recycling and Its Challenges Recycling as a concept has historical roots in response to concerns about resource depletion and waste management. The recycling of lead-acid batteries, for example, gained momentum in response to concerns about lead pollution (Stephens and Bauer 2017).

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The challenges faced by current recycling methods for lithium-ion batteries resonate with historical efforts to establish efficient recycling processes for emerging technologies. Innovations in recycling technology and infrastructure have historically evolved alongside technological advancements (Stephens and Bauer 2017).

Future Outlook for Sustainable EV Batteries Efforts to develop alternative battery chemistries, such as solid-state and lithium-sulfur batteries, align with historical trends of technological innovation in response to environmental and efficiency imperatives (Liu et al. 2018). Advances in recycling technologies, including closed-loop recycling and improved recovery rates, reflect ongoing historical efforts to reduce waste and promote resource conservation (Stephens and Bauer 2017). The dynamic nature of the EV industry and the continuous pursuit of sustainable solutions resonate with historical cycles of technological advancement and regulatory development in response to environmental challenges.

Ethical Considerations and Limitations Ethical considerations in research have evolved over time, with modern standards emphasizing transparency, proper citation, and attribution. These considerations align with broader historical trends in research ethics (Shamoo and Resnik 2015). Limitations of the study, including potential bias and temporal constraints, are intrinsic to research and have been addressed through various methodological approaches over time (Shadish et al. 2002).

DISCUSSION The research project on the environmental impact of electric vehicle (EV) batteries has unveiled critical insights that resonate with contemporary environmental concerns and the broader landscape of sustainability in the EV industry. However, the research must consider the significance of the research findings, acknowledge the study's limitations, and outline promising avenues for future research in this dynamic field.

Significance of the Research Findings The findings of this research project hold substantial significance in several key aspects. The research sheds light on the resource-intensive nature of EV battery production, offering a comprehensive view of the environmental impact across the entire life cycle. Such insights are indispensable for policymakers and industry stakeholders aiming to develop strategies that align with sustainability goals and environmental regulations. By exploring alternative battery chemistries and recycling technologies, the research underscores the potential for innovation and the development of more sustainable EV batteries. These findings inspire optimism regarding the future of EV technology and its potential to minimize environmental harm. The historical context woven into the findings provides a unique perspective. It illuminates the continuum of environmental concerns, technological evolution, and regulatory responses over time, enhancing the understanding of the current state of the EV industry. The research findings contribute to public awareness and education regarding the environmental impact of EV batteries. This knowledge empowers consumers to make informed choices, fostering a culture of sustainability in transportation.

Limitations While this research project offers valuable insights, it is essential to acknowledge its limitations. The research was conducted within a 12-week timeframe, restricting the depth and breadth of the analysis. More extensive studies may provide a more comprehensive understanding of the subject. The quality

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and availability of data on the internet varied, affecting the depth and reliability of information. Future research could benefit from access to more robust data sources. The research relied on existing literature, which may carry inherent biases based on the research objectives and the sources selected. A more comprehensive review might consider a wider range of perspectives.

Future Research The research project paves the way for several exciting avenues for future research. Conducting longitudinal studies that track the environmental impact of EV batteries over time can provide valuable insights into the evolving sustainability landscape of the industry. Future research can delve into comparative assessments of different battery chemistries and recycling technologies to determine their respective environmental impacts and feasibility. Investigating the effectiveness of policies and regulations in mitigating the environmental impact of EV batteries can offer critical insights into the role of government interventions in sustainability. Understanding consumer perceptions and behaviors concerning EVs and their environmental impact is essential. Future research can explore factors influencing EV adoption and sustainable practices. Continuous research into emerging battery technologies, such as solid-state batteries, can provide insights into their feasibility, scalability, and potential to revolutionize the EV industry.

REFERENCE LIST Abbott, J., Meza, P., Lam, L., & Gaines, L. (2011). A Life-Cycle-Based Environmental Footprint Assessment of Rechargeable Lithium-Ion Battery Systems in Electric Vehicles. Environmental Science & Technology, 45(15), 6730-6736. Frischknecht, R., Jungbluth, N., Althaus, H. J., Doka, G., Dones, R., Heck, T., ... & Tuchschmid, M. (2006). Implementation of Life Cycle Impact Assessment Methods. Data v2.0. Ecoinvent Report No. 1. Swiss Centre for Life Cycle Inventories. Graedel, T. E., Harper, E. M., Nassar, N. T., & Reck, B. K. (2015). On the materials basis of modern society. Proceedings of the National Academy of Sciences, 112(20), 6295-6300. Hawkins, T. R., Singh, B., & Majeau-Bettez, G. (2013). Comparative Environmental Life Cycle Assessment of Conventional and Electric Vehicles. Journal of Industrial Ecology, 17(1), 5364. Larsson, F., Bernhoff, H., & Leijon, M. (2020). Eco-friendly alternative for end-of-life EV battery packs. Energy Reports, 6, 1033-1042. Liu, Y., Lin, D., & Li, Y. (2018). Study on recycling of waste lithium-ion battery for lithium and cobalt recovery. Environmental Science and Pollution Research, 25(16), 16150-16158. Notter, D. A., Gauch, M., Widmer, R., Wäger, P., Stamp, A., Zah, R., ... & Althaus, H. J. (2010). Contribution of Li-ion Batteries to the Environmental Impact of Electric Vehicles. Environmental Science & Technology, 44(17), 6550-6556. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. Shamoo, A. E., & Resnik, D. B. (2015). Responsible Conduct of Research. Oxford University Press. Stephens, T. S., & Bauer, D. (2017). Battery second use strategies: A review of the economics, performance, and environmental impact. Journal of Power Sources, 365, 76-88.

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Unveiling the Veil: Assessing the Efficacy of International Efforts in Addressing Human Rights Abuses in North Korea

Full Name

Kim, Yoonseo Hanah

Fayston Preparatory of Suji

(Last Name, First Name)

School Name

KEYWORDS: North Korea, human rights violation, international organizations, intergovernmental organizations, NGOs, United Nations, sanctions, documentation, advocacy, accountability, global awareness, ethical dilemmas, humanitarian consequences Abstract The research delves into the intricate landscape of international efforts aimed at addressinghuman rights abuses in North Korea. The studyscrutinizes the pivotal roles played by international organizations, the United Nations, sanctions, and non-governmental organizations in confronting the pervasive human rights violations in the Democratic People's Republic of Korea. By meticulously documenting the documentation efforts, analyzingthe challenges and controversies surrounding sanctions, and assessing the limitations and complexities of advocacy, this study highlights the multi-faceted nature of the issue. As North Korea's human rights situation remains a global concern, the studyunderscores the need for sustained research and collaborative strategies to translate awareness into concrete actions, ultimatelystrivingfor a world where the rights and dignityof all individuals are universally upheld.

Introduction The human rights situation in North Korea has longbeen a source of international concern, characterized bya litanyof alleged abuses rangingfrom forced labor camps to restrictions on freedom of expression and movement. In response to these persistent and grave violations, various international organizations have undertaken efforts to address and rectifythese human rights abuses. This research endeavors to examine the efficacyof international organizations in addressinghuman rights abuses in North Korea, while also delving into the multifaceted mechanisms employed in this pursuit. This studycenters on the followingresearch question: "What is the efficacyof international organizations in addressinghuman rights abuses in North Korea, and how do various mechanisms, including documentation, United Nations initiatives, sanctions, and efforts by non-governmental organizations, contribute to the international community's abilityto influence and improve North Korea's human rights record?"

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The background to this research question lies in the persistent and well-documented human rights abuses within North Korea. As highlighted byHuman Rights Watch (2019), the secretive and authoritarian regime has been implicated in widespread and systematic violations of human rights, including extrajudicial executions, torture, and severe restrictions on freedom of speech, religion, and movement. The severity of these abuses, often likened to crimes against humanity, has sparked widespread international concern and led to concerted efforts bythe global communityto address this issue. Efficacy, in this research, is on assessing the direct impact that international organizations can have on people in North Korea. Though manyof these groups strive to disseminate information and make significant efforts to positivelyinfluence the lives ofNorth Koreans, oftentimes these effects are not as substantial or life-alteringas anticipated. Through this proposed research that provides a comprehensive review of the literature to understand the scope of impact of international organizations, the goal is to rank the efficacyof the three organizations explored, as detailed in the literature review, and put the efficacy of each into perspective. Understandingthe efficacyof international organizations in addressingNorth Korea's human rights abuses is of paramount importance for several reasons. Firstly, itpertains to the broader discourse on the responsibilityto protect(R2P) and the international community's role in preventingand mitigating gross human rights violations. Secondly, North Korea's isolation and opacitymake ita unique case study, providinginsights into the challenges and opportunities that arise when attemptingto influence a closed and authoritarian state. Thirdly, this research question addresses a critical ethical concern, as itconcerns the well-beingand dignity of the North Korean population, often depicted as one of the most vulnerable and oppressed in the world. The rationale behind exploringthis question in depth lies in the ongoingdebates and uncertainties surrounding the effectiveness of international efforts in improving North Korea's human rights record. While various organizations, includingnon-governmental organizations, the United Nations, and individual countries, have endeavored to shed light on the situation and pressure North Korea to change its practices, the results have been mixed at best. Some argue that these efforts have raised awareness and generated diplomatic pressure on North Korea (Smith 2020), while others point to the regime's resistance to external pressure and limited access for international organizations (Marcus and Park 2018). As the international communitygrapples with the ethical imperative to address human rights abuses worldwide, an in-depth examination of its efforts in the context of North Korea is not only timely but also essential. This research aims to contribute to a more comprehensive understandingof the challenges and opportunities in addressinghuman rights abuses in a closed and authoritarian state and to inform future policydecisions and actions in the realm of international human rights advocacy.

Literature Review History of dictatorship and Human Rights Abuse in North Korea North Korea, officiallyknown as the Democratic People's Republic of Korea (DPRK), has been a subject of international concern for decades due to its reported widespread and systematic human rights abuses (Lee). The roots of these abuses can be traced back to the division of the Korean Peninsula after World War II, which occurred in 1945 when the Korean Peninsula was liberated from Japanese colonial rule. This division led to the establishment of two separate states: North Korea, under the leadershipof Kim II-sung, and South Korea, under Syngman Rhee (Lee and Hassig2018). The Korean War(1950-1953) further deepened the division, endingin an armistice rather than a formal peace treaty, leavingthe two Koreas in a state of war. Kim 11-sung's consolidation of power and the establishment of a totalitarian regime in North Korea set the stage for the human rights abuses that would follow (Lee and Hassig2018). The regime's Juche ideology, characterized byself-reliance and the cult of personality around the ruling Kim family, resulted in a highly centralized and authoritarian government.

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International Organizations and Human Rights Documentation International organizations, such as Human Rights Watch and AmnestyInternational, have been actively engaged in documentingand exposinghuman rights abuses in North Korea (Kang2016). Their efforts have been crucial in revealingthe dire conditions faced byNorth Korean citizens. Human Rights Watch (2019) has published numerous reports documentingforced labor camps, torture, public executions, and other fonns of repression. AmnestyInternational has similarly contributed to the bodyof evidence, emphasizingthe systemic nature of these violations. These documentation efforts gained momentum in the late 20th century as North Korean defectors and escapees began to share their testimonies and experiences with international organizations (Lee 2019). The testimonies of defectors have provided critical insights into life under the North Korean regime, corroboratingthe extensive bodyof evidence. However, there's an unintended consequence of these documentations. The testimonies of the defectors and the documentations have prompted the North Korean government to tighten control over their citizens and intensify human rights violations, acting defensivelyin response to the exposure. This underscores the complexity of addressinghuman rights abuses in highlysecretive and repressive regimes, where the act of exposingatrocities can inadvertentlylead to increased repression. A nuanced approach that considers the potential backlash and increased human rights violations as a response to external scrutinyis essential when strategizingon ways to address and mitigate human rights abuses in countries like North Korea.

The United Nations and Human Rights in North Korea Within the framework of international governance, the United Nations has played a central role in addressing human rights abuses in North Korea (Smith 2020). In 2013, the United Nations Human Rights Council established the Commission of Inquiry (COI) on Human Rights in North Korea (Smith 2020). The COI's mandate was to investigate alleged human rights abuses in North Korea, marking the first time a UN body conducted such an inquiry(Kirby2014). The COI's 2014 report was a watershed moment in the international response to North Korea's human rights abuses. The report meticulously documented instances of torture, forced labor, starvation, and public executions. Itconcluded that these violations amounted to crimes against humanity, a designation that carried significant moral and legal weight(Kirby2014). The COI’s findings led to international outrage and calls for accountability. The historical context of the COI's report includes the increasinginternational scrutinyof North Korea's human rights record in the early21stcentury.The international communityhad become increasingly aware of the severity of the situation, and the COI's work provided an authoritative and comprehensive account of the abuses. However, enforcingaccountabilityremains a challenge, as North Korea cannot be legallycompelled to answer for its actions bythe UN or anyother international body. For justice to be served, the regime would need to voluntarilysubject itself to international legal proceedings—a highlyunlikely scenario. This intrinsic limitation hinders the efficacyof international responses to the human rights crisis in North Korea.

Sanctions and Their Controversies In addition to diplomatic measures, sanctions have been employed as a tool to pressure North Korea to address its human rights abuses (Schabas 2017). Sanctions have a historical backdropin the context of North Korea's nuclear ambitions and proliferation activities. The North Korean regime's pursuit of nuclear weapons and missile technologyhad led to international sanctions aimed at curbing its nuclear program.

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The imposition of sanctions related to human rights abuses followed the COI's report and the increased focus on North Korea's human rights situation (Smith 2020). These sanctions targeted North Korean officials and entities responsible for human rights abuses. However, their effectiveness remained a subject of debate. It's important to note that sanctions have been part of a broader strategyto pressure North Korea on multiple fronts, includingits nuclear activities and human rights abuses. This multidimensional approach reflects the complex geopolitical dynamics surroundingNorth Korea.

Non-Governmental Organizations (NGOs) Advocacy Non-governmental organizations(NGOs) have played a pivotal role in advocating for human rights improvements in North Korea (Kang2016). Their advocacyefforts have historical roots in the growingglobal awareness of North Korea's human rights situation. The late 20th and early21st centuries saw increased defections from North Korea, as well as the dissemination of information about the regime's abuses through defector testimonies and the work of international organizations. NGOs like Human Rights Watch and AmnestyInternational have leveraged these developments to raise awareness about North Korea's human rights situation. Theyhave employed various advocacy campaigns and initiatives, including reports, multimedia campaigns, and grassroots activism (Kang 2016). The historical context for NGO advocacyincludes the gradual emergence of a global coalition of actors concerned about North Korea's human rights abuses. This coalition includes governments, international organizations, and civil society groups workingtogether to address the issue on multiple fronts.

Research Questions The research questions serve as a foundation for investigatingthe multifaceted dynamics of international efforts to address human rights abuses in North Korea and pave the wayfor deeper exploration and analysis: What is the efficacyof international organizations in documentingand raisingglobal awareness of human rights abuses in North Korea? How have United Nations initiatives, particularlythe Commission oflnquiry(COi)and the actions and power of the Human rights Council (HOC) on Human Rights in North Korea, influenced international responses to human rights abuses in North Korea? What are the implications, both intended and unintended, of sanctions as a mechanism for addressinghuman rights violations in North Korea? To what extent have non-governmental organizations (NGOs) succeeded in influencinginternational discourse and policymakingregarding human rights abuses in North Korea, and what are the challenges theyface in advocating for change? How can innovative strategies be developed to effectively address human rights abuses in North Korea within the constraints imposed bythe North Korean regime?

Research Design and Methods The research methodologyemployed for this studyprimarilyconsists of a comprehensive literature review complemented by interviews from North Korean defectors. A literature review is a systematic process of identifying, analyzing, and synthesizing existing scholarly works, both primary and secondary sources, related to the research topic (Cooper, 1988). The steps and strategies undertaken serve to conduct an effective literature review on the topic of "Efficacy of international organizations in addressinghuman rights abuses in North Korea." Interviews from North Korean defectors can be obtained or arranged through organizations such as PSCORE or NK News. These firsthand accounts will shed light on how these organizations directly interact with refugees and evaluate their efficiency in aiding escape and supportingsubsequent integration processes.

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DefiningResearch Objectives and Scope Before embarkingon the literature review process, itis essential to clearlydefine the research objectives and scope. In this study, the primary research question was established: "What is the efficacyof international organizations in addressinghuman rights abuses in North Korea?" This research question guided the selection of relevant literature and determined the specific aspects to be explored in the review. Itwould also determine what type of questions would be asked to the interviewees when interviews are arranged in addition.

Identifying Keywords and Search Terms To ensure a comprehensive literature search, a set of keywords and search terms related to the research topic were identified. These terms included variations and synonyms offkeyconcepts such as "international organizations," "human rights abuses," and "North Korea." Boolean operators (AND, OR) were employed to create search strings that effectively captured the relevant literature, based on the frequency and significance of the words in the search.

Selection of Databases and Sources The next stepinvolved selectingappropriate databases and sources to conduct the literature search. Given the interdisciplinary nature of the research topic, a range of academic databases were utilized, includingbut not limited to: JSTOR, Google Scholar, Social Science Research Network (SSRN), United Nations databases. Additionally, governmental reports, international organization publications, and relevant books were considered as supplementary sources to ensure a comprehensive review.

Conductingthe Literature Search The literature search was executed usingthe identified keywords and search terms in the selected databases and sources. The search process was iterative, involvingthe adjustment of search strings and terms as new literature was discovered. The goal was to capture both seminal and recent works that contributed to a well-rounded understanding of the research topic.

Inclusion and Exclusion Criteria To maintain the relevance and qualityof sources, inclusion and exclusion criteria were applied during the screeningprocess. Relevant sources included scholarlyarticles, reports, and publications directly addressing the efficacyof international organizations in addressinghuman rights abuses in North Korea. Sources that were not peer-reviewed, lacked academic rigor, or did not directlypertain to the research question were excluded.

Data Analysis The selected sources were systematicallyreviewed and analyzed to extract relevant information and key findings. Data extraction included identifying key arguments, methodologies employed in primary studies, and empirical evidence supportingor challengingthe research question. The synthesized data were organized thematicallyto facilitate the development of the literature review section. Each source included in the literature review was criticallyappraised for its quality and relevance. The research methodology, sample size(for primary studies), data sources, and limitations of each source were evaluated to assess its reliability and credibility. The data and qualitative information gathered from interviews will complement and contextualize the findings from the literature review, offering nuanced perspectives by incorporating individual experiences.

Ethical Considerations In conductingthe literature review, ethical considerations were paramount. Proper citation and attribution were ensured, and ethical guidelines regardingthe use of scholarlyworks were strictly adhered to. In conducting the interviews, the potential trauma and stress of the interviewees must be taken into account. This issue can

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be addressed byensuringthat interviewees feel free to express any discomfort with sharinginformation or with their information beingused in a study.

Research Schedule The research schedule outlines a three-month timeline for conductinga comprehensive studyon the topic of "Efficacy of International Organizations in AddressingHuman Rights Abuses in North Korea."

Month 1 : Research Planningand Literature Review In the first month, the emphasis is on layingthe groundwork for the research project, creating questions to ask defectors duringthe interview and conductingan extensive literature review. Week 1-2: During the initial two weeks, the research questions and objectives will be defined. A detailed research plan, including milestones and deadlines, will be created. A dedicated research workspace will be established, and the necessary materials and resources will be gathered. Week 3-4: The followingtwo weeks will be dedicated to the literature review and contacting PSCORE to find interview times with a few North Korean defectors. Key sources related to the research topic will be identified, and an annotated bibliography will be compiled. Important findings and recurring themes within the sources will be noted for future reference.

Month 2: Data Collection and Analysis The second month is focused on data collection and the beginning of data analysis. Week 5-6: During these weeks, primary and secondary data, if applicable, will be collected. Any planned interviews, surveys, or experiments will be conducted accordingto the research plan. Collected data will be organized and stored systematicallyfor easyretrieval. Week 7-8: The subsequent two weeks will involve the commencement of data analysis. Appropriate methods will be employed to analyze the data. Visual representations, such as charts and graphs, will be created to present the findings. Data will be compared and contrasted to address the research questions. Additionally, the data will serve to rank the international organizations' efficacy based on previously established criteria.

Month 3: Writingand Conclusion The final month is dedicated to writingthe research paper and concludingthe project. Week 9-10: During these two weeks, the research paper will be drafted. Sections including the introduction, literature review, methods, and results will be written. Care will be taken to ensure proper citation and referencingin adherence to the chosen style guide, such as MLA. Week 11: The followingweek will focus on writingthe discussion section, delvinginto the findings in-depth and exploringtheir implications. A comprehensive conclusion will be crafted, summarizing key findings and discussingtheir broader significance. Limitations will be addressed, and suggestions for future research directions will be made. Week 12: In the final week, the research paper will be thoroughly proofread and edited for clarity and coherence. The paper will be formatted accordingto the chosen style guide, and anyremaining elements such as appendices or acknowledgments will be completed. The final stepwill be the submission of the research paper bythe designated deadline.

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Anticipated Results The results of the comprehensive literature review on the efficacy of international organizations in addressinghuman rights abuses in North Korea are anticipated to reveal several keythemes and findings. The analysis of scholarly works, reports, and publications from diverse sources provides a nuanced understandingof the role of international organizations in addressingthis critical issue. The insights outlined in this proposal are based on a preliminary review of the literature, and a more detailed examination, complemented byfirsthand interviews, is anticipated to yield more comprehensive findings.

Theme 1: Documentation Efforts One of the foremost themes that emerges from the literature review is the pivotal role played by international organizations in meticulously documenting human rights abuses in North Korea. Organizations such as Human Rights Watch (HRW) and Amnesty International have been at the forefront of these efforts, publishing extensive reports and publications (Human Rights Watch 2019). These reports not onlydetail the egregious violations but also incorporate firsthand accounts, interviews with defectors, and photographic evidence, painting a vivid and chilling picture of life under the North Korean regime. The significance of these documentation efforts cannot be overstated. They provide a vital foundation of empirical evidence and facts that underpin advocacy, awareness-raising, and policyformulation. The data within these reports offer a stark and comprehensive view of the scale and severity of human rights violations in North Korea, including forced labor camps, torture, public executions, and pervasive surveillance (Human Rights Watch 2019). This depth of documentation creates a powerful narrative that resonates with policymakers, the media, and the global public. The impact of these reports extends far beyond mere awareness. The international communityrelies on the meticulouslygathered data to hold North Korea accountable for its actions. The documentation serves as a catalyst for discussions at international forums, motivatingcountries and international organizations to take concrete steps to address the issue. These findings not onlyshed light on the human rights abuses but also provide essential ammunition for advocacycampaigns and policy recommendations.

Theme 2: United Nations Initiatives Another significant theme illuminated by the literature review is the role of United Nations initiatives in addressing human rights abuses in North Korea, with a particular focus on the Commission of Inquiry(COI)on Human Rights in North Korea (Smith 2020). The COI’s 2014 report marked a turning point in the international response to North Korea's human rights abuses, servingas a comprehensive and authoritative source (Kirby2014). The COI's report meticulously documented instances of torture, forced labor, starvation, and public executions, culminating in the categorization of these violations as crimes against humanity (Kirby 2014). This classification carried substantial moral and legal weight, leadingto global condemnation and renewed efforts to address the issue. The data within the COI report were instrumental in triggeringdiscussions at the United Nations and subsequentlyled to resolutions condemningNorth Korea's human rights record. However, it is important to recognize the limitations of United Nations mechanisms in translating awareness into concrete action. While the COI's report was instrumental in raisingglobal awareness and spurring diplomatic efforts, its recommendations for referral to the International Criminal Court (ICC) have not been realized due to political challenges and diplomatic complexities. This highlights the realpolitik dimension surrounding international responses to human rights abuses and underscores the inherent challenges in achievingaccountability.

Theme 3: Sanctions and Their Controversies

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The literature review brings to light the contentious nature of sanctions as a mechanism for addressing human rights abuses in North Korea (Schabas 2017). While sanctions imposed bythe United Nations Security Council and individual countries aimed to target North Korean officials and entities responsible for human rights abuses, their effectiveness remained a subject of debate. Data from the literature review reveals a complex picture regardingthe impact of sanctions. While sanctions have exerted economic and political pressure on North Korea, their direct correlation with substantial improvements in human rights practices remains elusive. Itis crucial to recognize the multidimensional nature of sanctions; theyhave been part of a broader strategyaimed at addressing not onlyhuman rights abuses but also North Korea's nuclear activities (Schabas 2017). Sanctions also raise ethical and legal dilemmas, as their consequences often extend beyond the intended targets. The literature review highlights concern that sanctions may inadvertently harm the civilian population, exacerbatinghumanitarian challenges. This dual role of sanctions as both a tool for exerting pressure and a potential source of sufferingunderscores the complexityof employing punitive measures to address human rights violations.

Theme 4: Non-Governmental Organizations(NGOs) Advocacy Non-governmental organizations(NGOs) have played a pivotal role in advocacyefforts to address human rights abuses in North Korea (Kang2016). The literature review indicates that organizations like Human Rights Watch and Amnesty International have consistentlyemployed various advocacy campaigns and initiatives to raise awareness about North Korea's human rights situation. These advocacyefforts have not onlygenerated media attention but have also stimulated public discourse and put pressure on governments to take action. The detailed reports and compelling campaigns produced by these NGOs have contributed significantly to shaping international narratives about North Korea's human rights abuses. However, the literature also highlights the complexities and challenges of advocacy efforts in the context ofNorth Korea. The North Korean regime has proven resilient in the face of external pressure, and the extent to which advocacycampaigns can penetrate the closed societyremains limited (Kang2016). The literature suggests that while NGOs have succeeded in raisingawareness and influencingthe global discourse, their impact on directlyshapingNorth Korean government policies is constrained bythe regime's isolation and intransigence.

Discussion The discussion now delves into the implications of these findings, acknowledges the limitations of this study, and suggests avenues for future research.

Implications of Potential Research Findings The findings from the literature review emphasize the pivotal role of international organizations, particularly in documenting human rights abuses and raising global awareness. Organizations like Human Rights Watch and Amnesty International have played a crucial role in meticulously documentingthese violations, providinga solid evidentiary foundation for advocacyand policy formulation. These documentation efforts have had a profound impact on international narratives about North Korea's human rights situation. The data within these reports have effectively captured the attention of policymakers, the media, and the global public. However, itis essential to recognize that documentation, while critical, is just one stepin the broader process of addressinghuman rights abuses. Movingforward, the challenge lies in translatingthis awareness into concrete actions that can lead to improvements on the ground.

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The role of the United Nations in addressinghuman rights abuses in North Korea is another critical dimension. The Commission of Inquiry(COI) report served as a catalyst for discussions and resolutions at the international level. However, the limitations of UN mechanisms in achieving accountabilityand enforcement reveal the complexities of the diplomatic landscape. Further research is needed to explore how international mechanisms can be strengthened to ensure greater accountabilityfor human rights abuses in North Korea. Sanctions, as highlighted in the literature review, represent a complex and contentious tool. While they exert economic and political pressure, their effectiveness in directly improving human rights practices remains uncertain. Itis essential to explore the unintended consequences of sanctions and develop strategies that mitigate harm to vulnerable populations while exertingpressure on the North Korean regime. Non-governmental organizations(NGOs) have shown remarkable resilience in advocating for human rights improvements. Their efforts have influenced global discourse and put pressure on governments. However, as the review suggests, the impact of advocacycampaigns on shapingNorth Korean government policies remains limited. Future research should explore innovative strategies for increasingthe effectiveness of NGO advocacywithin the constraints imposed bythe North Korean regime.

Limitations This study acknowledges several limitations. Firstly, the research relies on existing literature and secondary sources, which may introduce bias based on the selection and interpretation of available information. Additionally, due to the nature of the literature review, we cannot present new empirical data or primary research findings. The analysis is contingent on the quality and completeness of the sources reviewed. Furthermore, the dynamic nature of international relations and geopolitics means that the effectiveness of strategies and mechanisms maychange over time. The literature review provides a snapshot of the state of knowledge upto the knowledge cut off date in September 2021. Future developments, policychanges, and shifts in international relations mayimpact the efficacyof international organizations in addressing human rights abuses in North Korea.

Future Research Directions The review highlights the need for continued research on several fronts. First, there is a pressingneed for longitudinal studies that track the evolution of human rights abuses in North Korea and assess the impact of international efforts over time. Such research could provide insights into trends, improvements, or deteriorations in the human rights situation. Second, future research should delve deeper into the complexities of sanctions as a tool to address human rights abuses. Itshould explore the ethical dimensions, potential humanitarian consequences, and ways to optimize the use of sanctions while minimizingharm to the civilian population. Third, investigatinginnovative strategies for NGO advocacy within the constraints of the North Korean regime is essential. Research that examines the impact of information dissemination through new technologies and channels could shed light on alternative approaches to raisingawareness and influencing change.

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Reference List Cooper, Harris M. "SynthesizingResearch: A Guide for Literature Reviews." Sage Publications, 1988. Human Rights Watch. "North Korea: Total Control Zone." Human Rights Watch, 2019. Kang, David C. "Hierarchy and Legitimacy in North Korea: A Comment on Heo and Oneal." International Studies Quarterly, vol.60, no. 3, 2016, pp.514-518. Kirby, Michael. "Report of the Commission of Inquiry on Human Rights in the Democratic People's Republic of Korea." United Nations Human Rights Council, 2014. Kwon, Youngse. "Policyon North Korean Defectors." Ministry of Unification, 2022 Koh, Euijin. "Human Rights in North Korea: A Multilateral Approach." The Korean Journal of International Studies, vol.17, no. 1, 2019, pp.191-217. Lee, Sung-Yoon. "Dyingfor Rights: PuttingNorth Korea's Human Rights Abuses on the Record by Sandra Fahy (Review)." Korean Studies, vol.45, Jan. 2021, pp. ʊ EBSCOhost, search.ebscohost.com/login.aspx?direct=true&db=asn&AN=154139516&site=ehost-l 1ve. Park, Minju. "The Role of NGOs in PromotingHuman Rights in North Korea: A Case Studyof the Citizens' Alliance for North Korean Human Rights." Journal of Contemporary Asia, vol.49, no. 4, 2019, pp.607-627. Rodman, Frank. "Sanctions against North Korea: It's Time for a Rethink." Foreign Affairs, vol.97, no. 3, 2018, pp.119-128 Schabas, William A. "Sanctions against North Korea: Is Accountability for Crimes against Humanity an Impermissible Secondary Sanction?" North Carolina Journal of International Law and Commercial Regulation, vol.42, no. 4, 2017, pp.1013-1054. Smith, R.J. "The Impact of the UN Commission of Inquiry on Human Rights in North Korea." Global Responsibility to Protect, vol.12, no. 2, 2020, pp.129-152. Editors, P. (Ed.). (2023, September 4). How to get in touch with North Korean defectors. PSCORE. https://pscore.org/our-work/contact-defectors/

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RESEARCH

First Record of ‘Pyroplastics’ Found in the Jeju Island Sea, South Korea Kim, Eryn Hankuk Academy of Foreign Studies

INTRODUCTION The current era, called the “Anthropocene”, is charecterized by humankind’s wide-reaching impact on the environment (Crutzen & Stoermer, 2000). As one of the evidence for this labeling, plastic pollution has become a major threat to the environment (Lestari & Trihadiningrum, 2019). Mismanagement of plastic waste rapidly accumulates in marine, aquatic, and terrestrial ecosystems, and even in the remote locations such as the deep sea and the arctic (Andrady, 2011; Bergmann, et al., 2019; Peeken, 2018). Recently, new types of plastic formation have been confirmed to be caused by anthropogenic activities (Corcoran & Jazvac, 2020). Type

Description

Location

Plastiglomerates (Corcoran, et al. 2014)

composites consisting of multiple organic and inorganic pieces or debris (e.g. sand, rocks, shell fragments, wood, and various pieces of anthropogenic debris) within a melted polymeric matrix

Hawaiian islands in the Pacific Ocean

Plasticrusts (Gestoso, et al., 2019)

plastic debris encrusted in the intertidal rock

Madeira island in the Atlantic Ocean

Pyroplastics (Turner, et al., 2019)

encapsulated plastic debris similar to stone derived from melted plastic

North American and European Atlantic coasts

Anthropoquinas (Fernandino, et al., 2020)

sedimentary rocks with artifacts including plastic

South American Atlantic coast

PURPOSE OF STUDY Recently, pyroplastics have been found on Jeju island, South Korea, but there is a lack of information on them. In this study, I examined for the first time the occurrence of pyroplastics in the Jeju island sea. I aimed to provide new evidence regarding the occurrence of pyroplastics from coastlines of the Jeju island, and discuss their formation and impact on the environment.

MATERIALS AND METHODS 1. Description of the sites All the samples were identified on two public beaches located in Gonae-ri and Gimnyeong-ri, Jeju Province, South Korea. Both of the beaches are open to the public and near residential areas. Gonae-ri

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is famous for its port and fishery activities. Gimnyeong beach is popular for water sports and recreational activities such as surfing and yachting, influenced by adjacent port areas.

Figure 1. Map of Jeju and sampling location (a: Gonae-ri, b: Gimnyeong-ri) 2. Field and lab work The samples were collected during May 2023 while beachcombing. Though these resemble natural rocks, they could be easily distinguished from rocks with careful observation. Their size was measured with a digital caliper. As a preliminary step, it was observed whether they floated on water to confirm they differ from natural rocks. 3. Fourier-transform infrared spectroscopy (FTIR) analysis All the collected samples were analyzed by attenuated total reflectance FTIR (ATR-FTIR) spectrometry using PerkinElmer Spectrum Two. Fine powder of the samples was clamped against the diamond crystal before spectra were acquired with 4 scans in the region 4000 to 450 cm-1 and at a spectral resolution of 0.5 cm-1. Using scan and search mode, the obtained spectra were compared with the PerkinElmer spectral library via Spectrum 2 software. A search score > 0.6 was set as a threshold for polymer identification (Bergmann, et al. 2017). RESULTS & DISCUSSION 1. Visual and physical characteristics The pyroplastics in this study had indeterminate shapes with fractures and cavities on surfaces. They were black or charcoal gray across the entire surface due to combustion, with occasional hues of green or brown. The average size was roughly 5.5cm x 3.8cm x 1.8cm (length x width x height). All specimens floated in freshwater, which indicates that they have lower density than water.

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Figure 2. Samples of pyroplastics collected from Jeju island sea Unlike pyroplastics in Turner et al., which underwent weathering and oceanic exposure, the angular corners of the specimens showed limited signs of erosion caused by waves or weathering. This indicates that they were formed locally and recently, possibly transported to the shore by wind-carrying combustion residues. Small patches of translucent material could still be identified, serving as remnants of the original plastic. The thin section of specimen Nos. 3 and 4 exhibited a soft and elastic nature, which suggests that the plastic underwent significant thermal alteration, transforming its texture and properties. The combustion process likely caused the plastic to melt and partially re-solidify, resulting in its soft and elastic thin section. The specimens were observed to be physically fragile, which shows that pyroplastics are easily degraded so they are the source of microplastics (Turner et al., 2019). Since microplastics are very small, there are concerns on biological impact if they are ingested by various species. (Furukuma, 2021; Wright et al., 2013). 2. Chemical characteristics FTIR analyses revealed that three types of polymers were identified (See Fig. 3). As with the results of previous studies (De-la-Torre, et al., 2022; Turner, et al., 2019), the pyroplastic materials were mostly composed of PP and PE. Also, PA was confirmed as in the study of De-la-Torre, et al. (2022), which is the first report of PA in the composition of pyroplastics. Given that pyroplastics were found in a port known for fishing activities, PA inclusion may have originated from abandoned fishing equipment such as nylon monofilament lines.

Figure 3. FTIR spectra for the surface of pyroplastics from Jeju island sea. a) The blue spectrum resulted from the FTIR measurements and the black spectrum is from the PerkinElmer spectral library. b) The pink spectrum resulted from the FTIR measurements and the black spectrum is from the PerkinElmer spectral library.

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Some polyolefins showed weak absorption bands, which may be indicative of the creation of Ocontaining groups resulting from photooxidation (De-la-Torre, et al., 2022). This alteration could cause the embrittlement of the plastic material. The brittleness means that pyroplastics are easily shattered and become microplastics (Efimova, et al., 2018; Furukuma, 2021; Turner, et al., 2019). Most of them are subject to extreme temperature, melting and solidification, and then exposure to environmental conditions such as sea waves, UV light, etc., so it is expected that their physical traits, chemical structures, and mechanical behavior will be changed. This leads to the embrittlement of the plastic material and release of secondary contaminants (e.g. microplastics, nanoplastics), and potentially leach plastic additives to the environment (De-la-Torre, et al., 2022). Previous studies (De-la-Torre, 2022; Turner, et al., 2019) indicate that pyroplastics are a potential source of chemical contaminants for organisms to inhabit or ingest.

CONCLUSION To sum up, the pyroplastics from Jeju varied in terms of shapes and color. They had indeterminate, angular shapes with grayish color by the burning or melting of plastic. Using FTIR spectroscopy, I identified the pyroplastic materials as PP, PE, and PA. Since they are easily degraded, their environment impacts are mostly related to chemical release and plastic ingestion. A concern of pyroplastic-derived microplastics can enter food webs via consumption by invertebrates, and consequently cause biological threats to the affected organisms. Further studies should report the occurrence of pyroplastics around the world and focus on the risk assessment on the ecotoxicity of pyroplastics such as toxicity, degradation, release of secondary contaminants, and chemical additives.

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HOBY Korea encourages and supports the will, passion, eﬀorts, and research activities of teenagers, regardless of their level of expertise or the signiﬁcance of their research.

Copyright © 2023 All Rights Reserved Date of Publication: October 17, 2023 Published by HOBY Korea Youth Activities Association (President Hwang Hyun-chul) Address: 2F Myeongdong B/D Teheran-ro 83gil 44 Gangnam-gu, Seoul, 06166, Republic of Korea Website: emposw-youth.org