FYR 2024 Graduate RISE Impact Report- Research & Innovation- Prairie View A&M University by PVAMU Research&Innovation

GRADUATE RISE 2024

Research & Innovation for Scholarly Excellence Grant Program

RESEARCH & INNO VA TIO N TION

Magesh T. Rajan, Ph.D., P.E., M.B.A. Vice President, Research & Innovation

Message from the Vice President

The Division of Research & Innovation (R&I) is dedicated to nurturing and advancing the research and innovation landscape at Prairie View A&M University (PVAMU). Through the Faculty RISE-Graduate Research Grant program, R&I provides essential support for faculty-mentored graduate students engaged in research and innovative activities. This initiative empowers faculty researchers to sustain and expand their projects while simultaneously mentoring graduate students, helping to cultivate the next generation of experts in their respective fields.

With the assistantships they receive, RISE graduate students can dedicate more time and energy to their research endeavors, leading to deeper inquiry and more impactful results.

In this compendium, R&I proudly presents the research reports of the Faculty-RISE graduate students. The reports collected in this booklet represent contributions from all seven colleges and two schools within the university, showcasing the diverse research landscape at PVAMU.

R&I is honored to support graduate research through the Faculty RISE Graduate Research Grant program, which serves as a vital pathway for producing future scholars, educators, engineers, scientists, nurses, and architects. This program not only fosters individual growth but also celebrates and promotes the spirit of interdisciplinary collaboration across the university, creating a vibrant academic community dedicated to innovation and excellence. By encouraging partnerships between various disciplines, R&I aims to enhance the research experience for students and faculty alike, ultimately contributing to the broader mission of PVAMU.

Agriculture, Food, and Natural Resources

Praedial Larceny: Exploring its Psychological and Socio-Cultural Influence on Jamaican Farmers Salvation Atalor and Donald G Stoddart Ph.D.*

Department of Agriculture, College of Agriculture, Food, and Natural Resources

Introduction:

Over the years, Jamaican farmers and the Caribbean at large have been faced with the problem of praedial-larceny (Little, 2011). Simply put, praedial-larceny is the theft of agricultural produce or the means of production including materials and other fixed capital resources such as machinery that are involved in agricultural production. Praedial-larceny has resulted in several negative outcomes. These negative outcomes are not only related to the agricultural sector, but they also have social and psychological implications for those who are immediately affected by the practice. For example, “In Jamaica, official figures report annual loss to farmers and fishers more than US$55.0M or 6% of gross output, while Trinidad and Tobago reports US$11.3M over a 6-month period. Belize estimates annual loss to be over US$300,000 and St. Vincent and the Grenadines an estimated US$2.3M. The Commonwealth of The Bahamas estimates annual loss to its marine fish industry in the amount of US$16 .0M. Saint Lucia is spending more than US$400,000 annually on district pilot activities to prevent and reduce Praedial-larceny, and Grenada, Antigua and Barbuda and St Vincent and the Grenadines smaller but relatively important amounts” (Little, 2011, p.12). Therefore, Praedial-larceny has become a major disincentive to agricultural production and food security not only in Jamaica but the entire region. This disincentive where individuals refrain from investing in agriculture due to the risk of losses, contribute to the loss of employment, and increase in poverty especially in rural communities that rely heavily on small scale farming as a means of survival. Praedial larceny is not a new phenomenon and may have its genealogy engrafted to the colonial era (Thorton, 1902). According to Thorton, (1902), “from its widespread and persistent occurrence, it has long been a serious factor militating against the prosperity of the Colony” (Thorton, 1902 p.135). Although efforts were being made from this time and in contemporary periods, for example the anti praedial-larceny legislations created in Jamaica in the 1980s to combat the practice, the practice continue to increase (Little, 2011). Therefore, there is great need to expend resources in the study of praedial-larceny. However, not much is being done within the academy to bring light to the causes and effects of predial larceny.

Objectives:

The purpose of this study is to explore the psychological and socio-cultural impact of praediallarceny on farmers in south central communities of Jamaica. This will offer insights into how this crime has altered agricultural practices. The specific goals of this project are to

1. investigate the legacy of praedial larceny in Jamaica.

2. determine the perceived causes of praedial larceny.

3. to make meaning of participants’ perception of the recent anti praedial larceny proposals

4. To attain different perspectives pertaining to the solution of praedial-larceny within Jamaica

Methodology:

This study employs a mixed method approach where data from a descriptive qualitative paradigm is compared with data collected from a survey instrument. Researchers will interview participants using open-ended questions to get rich description of their experiences with praedial larceny within their community. The questionnaires will be distributed through various channels (e.g., in-person, online, via agricultural cooperatives). The results will be assessed, compared and discussed.

Preliminary Results and Discussions:

Literature review reveals that the problem of praedial larceny is ongoing and needs attention. Numerous small and medium size farmers are being affected by this crime. It is also revealed that some farmers are unimpressed by law enforcement’s drive to curve the crime and as such they try to implement measures to reduce the crime. The proposal for this research is submitted to PVAMU IRB and is awaiting approval to begin data collection in fall 2024.

Impacts/Benefits:

This study addresses a gap in the literature on praedial larceny in the Jamaican rural society and contributes to the body of knowledge. The literature review with proposal was presented at the Conference for Interdisciplinary Student Research (CISR) (April 2024) - College of Juvenile Justice, Prairie View A&M University, Prairie View, TX 77446. A proposal was also accepted to present at the American Association for Adult and Continuing Education (AAACE) 2024 Annual Conference in Las Vegas. It is the intention that this research will be published in a reputable journal and made accessible to all, particularly, those affected by praedial larceny. The University will benefit from this research since the result will be shared with the stakeholders to address similar issues in the U.S.A. Also, additional research will facilitate informed policy implementation.

References:

1. Little, V. (2011). Praedial Larceny: Its Consequences for Caribbean Agriculture. CARICOM View, 6–11.

2. Thornton, S. L. (1902). Prædial Larceny in Jamaica. Journal of the Society of Comparative Legislation, 135-148.

Arts and Sciences

Design and Synthesis of New Quinoxaline-Based Derivatives as PARP-1 Inhibitors

Taylor Viles and Sameh Abdelwahed, Ph.D.*

Introduction:

Department of Chemistry, College of Arts & Sciences

Taylor Viles and Sameh Abdelwahed, Ph.D.* Department of Chemistry, College of Arts & Sciences

PARP-1 acts as a “molecular nick sensor” to DNA single-strand (ssDNA) breaks and catalyzes the transference of ADP-ribose units (utilizing nicotinamide adenine dinucleotide (NAD+) as a substrate) to acceptor proteins, facilitating the recruitment of the damaged DNA and promoting cell survival

This process is crucial in the base excision repair (BER) of single-strand DNA breaks, which is linked to the resistance that typically develops following traditional cancer treatments. PARP-1 suppression enhances the damage of injured DNA resulting in s ynthetic lethality in DNA-repairing-deficient cancer cells, such as BRCA1/2-deficient cells. Thus, PARP-1 suppression synergizes the impact of various antiproliferative drugs such as topoisomerase-I inhibitors, DNA alkylating drugs, and ionizing radiation. Moreover, some PARP suppressors are effective as single agents against cancers bearing BRCA1- or BRCA2-mutations.

Poly (ADP-ribose) polymerases (PARPs) constitute a group of at least 17 enzymes that are correlated with the DNA damage repair process. PARP-1 is the most abundant member of this group and has emerged as one of the most auspicious molecular targets for cancer management in the past decade. PARP-1 acts as a “molecular nick sensor” to DNA single-strand (ssDNA) breaks and catalyzes the transference of ADP-ribose units (utilizing nicotinamide adenine dinucleotide (NAD+) as a substrate) to acceptor proteins, facilitating the recruitment of the damaged DNA and promoting cell survival . This process is crucial in the base excision repair (BER) of single-strand DNA breaks, which is linked to the resistance that typically develops following traditional cancer treatments. PARP-1 suppression enhances the damage of injured DNA resulting in s ynthetic lethality in DNA-repairing-deficient cancer cells, such as BRCA1/2-deficient cells. Thus, PARP-1 suppression synergizes the impact of various antiproliferative drugs such as topoisomerase-I inhibitors, DNA alkylating drugs, and ionizing radiation. Moreover, some PARP suppressors are effective as single agents against cancers bearing BRCA1- or BRCA2-mutations.

The US FDA recently approved four PARP suppressors, Olaparib, Rucaparib, Niraparib, and Talazoparib, for curing BRCA-mutated, HER2-negative advanced, metastatic ovarian, or breast cancer. In addition, there are several PARP suppressors under study in various clinical phases, such as Veliparib, Pamiparib, Simmiparib, and Fluzoparib. Furthermore, recent studies investigated the therapeutic potential of various PARP-1 suppressors for other refractory diseases such as Alzheimer’s disease (AD). Accordingly, the development of effective PARP-1 inhibitors plays an important role in medicinal chemistry communities.

Objectives:

Quinoxaline stands as a prized framework and a fundamental component in numerous anticancer agents due to its established role as a selective adenosine triphosphate (ATP) competitor and its bioisosteric resemblance to benzimidazole, quinazolinones, isoquinolinones, phenanthridone, and phthalazinones – the foundational structures of a multitude of PARP-1 inhibitors. Moreover, the incorporation of sulfonyl and sulfonamide groups into various heterocyclic ring systems has been widely acknowledged as an esteemed strategy for hindering the proliferation of diverse human cancer cell lines, employing varied modes of action.

Materials and Methods:

This study was directed toward the design and construction of new quinoxaline compounds using various synthetic pathways illustrated in the accompanying Schemes. The synthesis was initiated by reacting the starting material o-phenylenediamine with oxalic acid in the presence of HCl to provide quinoxaline-2,3(1H,4H)-dione. This compound was treated with chlorosulfonic acid to produce the corresponding key intermediate 6-sulfonyl chloride derivative. This derivative served as an intermediate for the nucleophilic substitution reaction with hydrazine hydrate to afford the 6sulfonohydrazide derivative, which was utilized as a precursor for the ring closure reaction with different active methylene reagents, namely, ethyl-acetoacetate, acetylacetone, and diethyl malonate, to accomplish the corresponding pyrazole derivatives.

Results and Discussion:

The outcomes offer insights into the potential of these compounds as PARP-1 inhibitors, unveiling their inhibitory activity and structure-activity relationships. This research advances our comprehension of molecular interactions and lays the groundwork for innovative therapeutic agents, especially in cancer treatment. The key intermediate 6-sulfonohydrazide analog was used to design and synthesize new derivatives of potential PARP-1 inhibitory activity. Although the new compounds demonstrated reasonable PARP-1 suppression, some compounds emerged as the most promising suppressors, showing greater efficacy compared to Olaparib. Other derivatives exhibited a mild decrease in potency. Furthermore, several compounds were evaluated as in vitro antiproliferative agents against the mutant BRCA1 (MDA-MB-436, breast cancer) cell line compared to Olaparib as a positive control. One compound exhibited the most significant potency, whereas the IC50 value of Olaparib was less effective. Additionally, the examined derivatives displayed a promising safety profile against the normal WI-38 cell line. Cell cycle, apoptosis, and autophagy analyses were conducted in the MDA -

MB-436 cell line for the most potent compound, which exhibited cell growth arrest at the G2/M phase, induction of programmed apoptosis, and an increase in the autophagic process.

Throughout this research, NMR spectroscopy played a crucial role in the material identification process. The student learned to utilize NMR to confirm the structures of synthesized compounds, gaining proficiency in interpreting spectra and identifying key signals corresponding to different functional groups. This hands-on experience with NMR analysis provided a deeper understanding of the structural characteristics and purity of the compounds, which was essential for determining their potential as PARP-1 inhibitors. The student also developed skills in preparing NMR samples, calibrating instruments, and troubleshooting common issues, enhancing their overall analytical capabilities in the laboratory.

Impact:

This study highlights the potential of newly synthesized quinoxaline-based derivatives as effective PARP-1 inhibitors. The promising results, suggest these derivatives could serve as potent anticancer agents, especially against BRCA-mutated cancers. The findings also provide a foundation for further research into the therapeutic applications of these compounds, potentially extending to other diseases such as Alzheimer’s. The successful design and synthesis of these derivatives contribute to the broader field of medicinal chemistry, emphasizing the importance of innovative approaches in drug discovery and development.

References:

1. Guo, C.; Wang, L.; Li, X.; Wang, S.; Yu, X.; Xu, K.; Zhao, Y.; Luo, J.; Li, X.; Jiang, B. ; et al. Discovery of novel bromophenol-thiosemicarbazone hybrids as potent selective inhibitors of poly (ADP-ribose) polymerase-1 (PARP-1) for use in cancer. J. Med. Chem. 2019, 62, 3051–3067. https://doi.org/10.1021/acs.jmedchem.8b01946.

2. Elmasry, G.F.; Aly, E.E.; Awadallah, F.M.; El-Moghazy, S.M. Design and synthesis of novel PARP-1 inhibitors based on pyridopyridazinone scaffold. Bioorg. Chem. 2019, 87, 655–666. https://doi.org/10.1016/j.bioorg.2019.03.068.

3. Li, S.; Li, X.Y.; Zhang, T.J.; Zhu, J.; Xue, W.H.; Qian, X.H.; Meng, F.H. Design, synthesis and biological evaluation of erythrina derivatives bearing a 1,2,3-triazole moiety as PARP-1 inhibitors. Bioorg. Chem. 2020, 96, 103575. https://doi.org/10.1016/j.bioorg.2020.103575.

4. Malyuchenko, N.V.; Kotova, E.Y.; Kulaeva, O.I.; Kirpichnikov, M.P.; Studitskiy, V.M. PARP1 Inhibitors: Antitumor drug design. Acta Nat. (Англоязычная Версия) 2015, 7, 27–37.

Exploiting B1 Vitamin as A Delivery Vehicle for Cargo Inside the Living Cell

Jennifer Nnaemeka and Sameh Abdelwahed, Ph.D.*

Department of Chemistry, College of Arts and Sciences

Introduction:

Cancer remains a significant global health challenge, necessitating continuous exploration of effective treatment options. Recent research has highlighted the potential of various vitamins and nutrients in cancer therapy, with thiamine (Vitamin B1) emerging as a promising candidate due to its role in cellular metabolism and minimal adverse effects. This report outlines the systematic approach undertaken to modify thiamine for enhanced anti-cancer properties, leveraging its biochemical compatibility and potential to inhibit carcinogens.

Objective:

The primary objective of this research is to synthesize a thiamin derivative with improved anti-cancer properties by modifying the thiazole part of the molecule. This involves converting the existing alcohol group into a stronger alcohol, specifically a phenolic compound, known for its efficacy in anti-cancer therapies.

Material and Method:

The procedure entails a biphasic reaction. Initially, the synthesis of the starting material, 2-(4-methylthiazol-5yl) ethyl 4-methylbenzenesulfonate, commenced. TsCl was introduced into a reaction mixture comprising 4methyl-5-thiazoleethanol, triethylamine, and dichloromethane as the solvent. The mixture was then heated at 100°C for 6 hours. Upon the reaction's completion, the resulting solution was washed with water and extracted with dichloromethane, achieving a quantitative yield. In the subsequent phase, the SN2 mechanism reaction was initiated by reacting 2-(4-methylthiazol-5-yl) ethyl 4-methylbenzenesulfonate with various phenolic compounds. The conjugation of phenolic compounds to the synthesized starting material followed standardized research methodologies. Post-reaction, column purification was conducted, resulting in product yields ranging from 50-70%.

Results and Discussion:

Synthesis Outcome: The thiazole derivative was successfully synthesized and reacted with phenolic compounds, creating the desired thiamine derivative. TLC analysis confirmed the reaction completion, with the presence of the desired product.

Purification and Verification: Column chromatography effectively purified the product, as confirmed by consistent TLC results showing a single product spot. Carbon and Proton NMR analysis verified the structural integrity and purity of the final product.

Figure: Scheme to Synthesize and an NMR Example of the Phenolic Derivatives of Thiamin.

The product was weighed, and the percentage yield was calculated based on the molar ratio, confirming an efficient synthesis process.

Discussion:

The modification of thiamine to include a phenolic compound demonstrated potential for enhanced anti-cancer properties. The process showcased the feasibility of using common nutrients in developing effective cancer therapies with potentially fewer side effects.

NMR Spectroscopy Training and Analysis: Training: Students are trained on the principles of NMR spectroscopy, including the theoretical background, instrumentation, sample preparation, data acquisition, and spectrum interpretation. Analysis: The synthesized compound is analyzed using both Carbon-13 (¹³C) and Proton (¹H) NMR spectroscopy to confirm its structure.

Impact:

This research highlights the innovative approach of utilizing a commonly consumed nutrient, thiamine, in cancer therapy. By modifying its structure to include phenolic compounds, this st udy opens avenues for developing more effective and less harmful anti -cancer treatments. The

methodology and findings contribute valuable knowledge to the field of oncology and pharmacology, emphasizing the potential of dietary components in medical applications. This work sets a foundation for future research aimed at optimizing thiamine derivatives and exploring their full therapeutic potential in cancer treatment.

References:

1. Zhang, X.; Basuli, F.; Abdelwahed, S.; Begley, T.; Swenson, R. Radiosynthesis of 5-[18F]Fluoro1,2,3-triazoles through Aqueous Iodine–[18F]Fluorine Exchange Reaction. Molecules 2021, 26, 5522. https://doi.org/10.3390/molecules26185522

2. Vishav Sharma, Dmytro Fedoseyenko, Sumedh Joshi, Sameh Abdelwahed, and Tadhg P. Begley. Phosphomethylpyrimidine Synthase (ThiC): Trapping of Five Intermediates Provides Mechanistic Insights on a Complex Radical Cascade Reaction in Thiamin Biosynthesis ACS Central Science 2024 10 (5), 988-1000. DOI: 10.1021/acscentsci.4c00125

Disparities in Emerging Adults’ Depression and Roles of Greenspace and Social Networks

Ijeoma Ugochinyere Eze and Iyanda Ayodeji, Ph.D.*

Division of Social Sciences, College of Arts and Sciences

Introduction:

Depression significantly contributes to mortality, morbidity, disability, and economic burdens in the United States 1 There has been a steady increase in the occurrence of major depressive episodes among emerging adults, specifically those in their late teens to mid-to-late twenties. The rates have risen from 10.3% in 2015 to 17.2% in 2020 for individuals aged 18-25 and from 7.5% to 9.9% for those aged 26-34.2 This concerning trend underscores the fact that a substantial portion of emerging adults are contending with mental health challenges while transitioning into adulthood. This study draws from social identity theory and therapeutic landscape concepts.

Social identity theory provides insights into the psychological mechanisms through which individuals derive a sense of self and belongingness within the complex tapestry of social interactions. 3 Therapeutic landscapes exemplify the interplay between direct and digital social networks and their combined impact on physical and mental health 4 This concept highlights how specific environments fostered through these networks can have healing or restorative effects on an individual’s well-being. The presence of natural environments, parks, and green spaces within one’s social networks has been incontrovertibly linked to ameliorating mental health, heralding reductions in symptoms of anxiety and depression.

Methodology:

Aim: The project aimed to investigate the impact of Spatial Social Networks and Environmental Exposure (SSNE) on emerging adult’s mental health.

Data: This quantitative cross-sectional study analyzed data (N= 1705) from the SSNE project data. Data were collected between February and October 2023.

Variables: The primary outcome variables are mental health measures using the 9-item Physical Health Questionnaire (PHQ-9) and the 21-item Depression, Anxiety, and Stress Scale (DASS-21).

Explanatory variables are Social class identity (SCI) and two mediating variables green space utilization (GSU) and social network (SSN).

Analytical plan: This study employed descriptive, bivariate, and Structural Equation Model (SEM) statistics to describe and assess the complex relationship between the two outcome variables, one independent and two mediating variables.

Results:

Disparity: We identified a higher prevalence of depression among participants categorized as ‘racial and sexual minorities’ in our study (Table 1)

Table 1: Severity of depression among minority youth in the United States

Note: Non-minority is heterosexual/ White; racial/sexual minorities are members of LGBTQ+ and non-white groups.

SEM result: As shown in Figure 1 below, SCI serves as a protective factor for youth mental health (PHQ9 Coef. = -0.362, 95% CI= -0.582, -0.142, p =0.001; DASS-21 Coef. =-0.491, 95% CI=0.726, -0.257). No significant mediating effect of GSU and SSN was observed. Model diagnostic indices indicate a strong fit as indicated by the Comparative Fit Index (CFI=0.996), Tucker Lewis index (TLI=0.982), and the Standardized Root Mean Square Residual of 0.013, respectively. The Likelihood Ratio Chi-square (χ) assesses the overall fit and the discrepancy between the sample and fitted covariance matrices (χ(3) = 7.733 (p > 0.052).

Figure 1: Structural Equation of youth mental health in the United States

Impacts/Benefits:

The PI attended the 2024 Association of American Geographers Annual Meeting in Honolulu, HI, and the Race Ethnicity and Place Conference in Washington DC, the Health Equity conference by the Centers for Medicare & Medicaid Services in Bethesda, Maryland, where he presented the results of the project. Alongside the presentation, the PI organized and chaired two paper sessions based on the major themes of the project: Impacts of the Natural, Built, and Social Environment on Health 1 &2. The sessions led to insightful discussions, with several attendees showing interest in the published results and the opportunity to collaborate on similar projects. One manuscript is underway to be submitted to a peer-reviewed journal.

Reference:

1. Friedrich MJ. Depression is the leading cause of disability around the world. Jama. 2017;317(15):1517-1517.

2. Lee B. National, State-Level, and County-Level Prevalence Estimates of Adults Aged ≥18 Years Self-Reporting a Lifetime Diagnosis of Depression United States, 2020. MMWR Morb Mortal Wkly Rep. 2023;72. doi:10.15585/mmwr.mm7224a1

3. Postmes T, Wichmann LJ, van Valkengoed AM, van der Hoef H. Social identification and depression: A meta-analysis. European Journal of Social Psychology. 2019;49(1):110-126. doi:10.1002/ejsp.2508

4. Markevych I, Schoierer J, Hartig T, et al. Exploring pathways linking greenspace to health: Theoretical and methodological guidance. Environmental Research. 2017;158:301-317. doi:10.1016/j.envres.2017.06.028

Efficient Removal and Detection of Small Ring Polycyclic Aromatic Hydrocarbons from Water

Viviana Salazar and Harshica Fernando, Ph.D.*

Department of Chemistry, College of Arts and Sciences

Introduction:

Polycyclic Aromatic Hydrocarbons (PAHs) are byproducts of combustion processes and can be found in air, food, water and soil (Figure 1). They even occur naturally in coal, crude oil and gasoline. PAHs are molecules with two or more fused carbon rings. The Environmental Protection Agency (EPA) has identified 16 PAH molecules that should be monitored due to potential health risks from exposure. There have been reports of PAH molecules being linked to oxidative stress, cancer, and cardiovascular diseases. Due to these reports it is imperative to for efficient identification and removal methods of these compounds. Using Green Iron Oxide Nanoparticles (GIONPs), small ring PAHs can be removed and monitored using fluorescence spectroscopy. Through many efforts in removing PAHs, are attempted using different metal ions and green nanoparticles, iron is found to be low cost, low toxicity and abundant making this nanoparticle system a cost-effective method of PAH removal. This study shows show that GIONPs, have the potential to be used to remove PAHs from water.

Figure 1. PAH contamination of water and soil

Objective:

The aim of the project is to identify and analyze the removal process of PAHs using GIONPs synthesized from a green source and iron salts. Some structures of PAH’s are shown in Figure 2.

Figure 2: Structures of polycyclic aromatic hydrocarbons used.

Methods:

Synthesis of Fe nanoparticles:

GIONPs were prepared at room temperature using FeSO4 in a 500 ml beaker. Distilled water was added and stirred. 10.0 ml of the green source was then added and the mixture stirred. The solution was then mixed with 2M NaOH and stirred until a dark brown precipitate was formed. The precipitate was then centrifuged at 6000 rpm for 15 minutes. The nanoparticles were then separated and washed with distilled water. After decanting the supernatant, the precipitate was dried at 70 C overnight and used in characterization and PAH removal experiments.

Scanning Electron Microscope (SEM) and Electron-Dispersive X-ray Spectroscopy (EDS)

measurements:

Analyses from SEM and EDS were performed using a scanning electron microscope and In TouchScope software. The samples were prepared on carbon-coated adhesive tape with backscattered electron images that were collected using an accelerating voltage of 10 kV and a load current of approximately 90uA with a working distance of 9 mm. EDS spectra were gathered at a magnification of 2000x and the analyzed area was 0.15 mm2.

PAH Removal:

Naphthalene, Anthracene, Fluorene and Pyrene were prepared in Acetonitrile. To each PAH solution prepared, 10.0 mg of GIONPs were added and the mixture allowed to mix for 2 to 3 hours. The mixture was then centrifuged at 1000 rpm and scanning at 30 minutes followed by scanning in 15 minute intervals using the Jasco FP-8300 fluorescence spectrometer.

Identification of PAH’s:

Preliminary experiments were carried out to establish the method of identification using a fluorescence energy transfer method. Small ring PAH’s were tested with the fluorophore rhodamine molecule to identify the efficient energy transfer process. All experiments were carried out using a fluorescence spectrometer.

Results and Discussion:

Results from Scanning Electron Microscope (SEM) picture on the left, and Electron-Dispersive Xray Spectroscopy (EDS) picture on the right (Figure 3) are shown below.

Figure 3. SEM and EDS scans of the synthesized nanopartic

The results of the fluorescence intensity scans for four small ring PAH’s are shown in Figure 4.

Figure 4: Fluorescence Intensity Scans of Naphthalene, Anthracene, Fluorene and Pyrene, respectively from left to right. These show the removal of the PAH after the addition of the GIONPs over time.

The graphs below represent the Fluorescence Intensity vs Time plots for the removal of PAHs, this shows a clearer progression over time of the NPs PAH removal over the amount of time indicated in the graphs (Figure 5).

Figure 5: Fluorescence intensity vs time plots. In the results, focusing on the PAH removal and intensity scans, it can be seen that GIONPs are consistent in removing PAHs from compounds. Although the PAH molecule removal using GIONPs takes place at varying minute ranges, it is still seen that PAH molecules intensity is decreasing over time.

Significance:

PAH molecules can be found in air, food, water and soil. They also occur naturally in coal, crude

oil and gasoline. There have been reports of PAH molecules being linked to oxidative stress, cancer, and cardiovascular diseases, 16 PAH molecules have been identified to be potential high risk from exposure. Because they are so widespread, it is important to develop an efficient and effective method of detecting and removing PAH molecules. The results presented here support GIONPs as an efficient and effective method of PAH molecule removal.

Future and ongoing work:

Preliminary work on identification of PAH’s using a fluorescence-based method is established. More work needs to be performed in identifying a suitable dye that allows detection of all sixteen priority PAH’s

References

1. Zang, Y., Zhang L., Huang, Z., Li, Y., Wu, N., He, J., Zang, Z., Liu, Y., Niu, Z. Pollution of Polycyclic Aromatic Hydrocarbons (PAHs) in drinking water of China: Composition, distribution and influencing factors. Ecotoxicology and Environmental Safety. 2019, 177, 108116.

2. Sun, K., Song, Y., Zong, W., Tang, J., Liu, R. Anthracene-induced DNA damage and oxidative stress: a combined study at molecular and cellular levels. Environmental Science and Pollution Research. 2020, 27, 41458-41474.

3. Adeniji, A.O., Okoh, O.O. & Okoh, A.I. Levels of Polycyclic Aromatic Hydrocarbons in the Water and Sediment of Buffalo River Estuary, South Africa and Their Health Risk Assessment. Arch Environ Contam Toxicol 2019, 76, 657–669.

4. Ambade, B., Sethi, S. S., Kurwadkar, S., Kumar, A., Sankar, T. K. Toxicity and health risk assessment of polycyclic aromatic hydrocarbons in surface water, sediments and groundwater vulnerability in Damodar River Basin, Groundwater for Sustainable Development. 2021, 13, 100553.

5. Al-Dossary, M. A., Abood, S. A., Al-Saad, H. T. Effects of physicochemical factors on PAH degradation by Planomicrobium alkanoclasticum. Remediation 2021, 31, 29037.

6. Racicot, J. M., Mako, T. L., Healey, A., Hos, B., & Levine, M. Efficient Detection and Removal of Polycyclic Aromatic Hydrocarbons Using Cyclodextrin-Modified Cellulose. ChemPlusChem, 2020, 85(8), 1730–1736.

7. Serio, N., Miller, K., Levine, M. Efficient Detection of Polycyclic Aromatic Hydrocarbons and Polychlorinated Biphenyls via Three-Component Energy Transfer. Chem. Commun. 2013, 49, 4821-4823.

8. Serio N, Prignano L, Peters S, Levine M. Detection of Medium-Sized Polycyclic Aromatic Hydrocarbons via Fluorescence Energy Transfer. Polycycl Aromat Compd. 2014, 4(5):561- 572.

9. Fernando, H., Ju, H., Kakumanu, R., Bhopale, K. K., Croisant, S., Elferink, C. Distribution of petrogenic polycyclic aromatic hydrocarbons (PAHs) in seafood following Deepwater Horizon oil spill. Marine Pollution Bulletin. 2019, 45, 200-207.

10. Agency for Toxic Substances and Disease Registry (ATSDR) Toxicologial profile for polycyclic aromatic hydrocarbons 1995. (http://www.atsdr.cdc.gov/toxprofiles/tp69.pdf).

11. Pampanin DM in Petrogenic Polycyclic Aromatic Hydrocarbons in the aquatic environment. Chapter 1.2017. Edited by Pampanin DM, and Sydnes MO pp3–13.

12. Poster D. L., Schantz M. M., Sander L. C., Wise S. A. Analysis of polycyclic aromatic hydrocarbons (PAHs) in environmental samples: a critical review of gas chromatographic (GC) methods. Anal. Bioanal. Chem. 2006, 386, 859–881.Ramalhosa M. J., Paiga P., Morais S., Delerue-Matos C., Oliveira M. B. Analysis of polycyclic aromatic hydrocarbons in fish: evaluation of a quick, easy, cheap, effective, rugged, and safe extraction method. J. Sep. Sci. 2009, 32, 3529–3538.

13. Rotkin-Ellman M, Wong K. K., Solomon G. M. Seafood Contamination after the BP Gulf Oil Spill and Risks to Vulnerable Populations: A Critique of the FDA Risk Assessment. Environ. Health. Perspec. 2012, 120, 157–16.

Digital PV Panther Project

Evelyn

Todd and Dr. Tyler Moore, Ph.D.*

Division of Social Science, College of Arts and Sciences

Introduction:

Digital PV Panther Project has set a new standard for archival excellence and digital storytelling on the campus of PVAMU. From June 2022 to August 2023, we have processed over 40 manuscript collections in the PVAMU archives and digitized them. We have also created digital finding aids and published them on our website for visitors to easily find digitized materials. Moreover, we have published numerous academic blog posts detailing our research into the history of PVAMU, and we have published detailed accounts of our research methods. The PVAMU archives remain in dire need of financial and human resources. The improperly stored collections are also in dire need of rehousing and preservation. In the fall/spring of 2023-24, I will work with Dr. Moore to track down other descendants of the enslaved at Alta Vista as well as create digital exhibitions that not only reveal the names of many more people enslaved at Alta Vista, but also tell the unvarnished truth about the harsh realities of the Black experience prior to the Civil War.

Objectives/Goals:

Dr. Moore, the DPPP undergraduate students, and I will publish more of our research on the Digital PV Panther Project blog and academic journals. We will also make more primary sources from the long-unprocessed archival collections at PVAMU accessible to the student body on the Digital PV Panther Project’s social media accounts and website. Moreover, we will secure external funding on the state and federal level to hire more students to work on the project in 2024.

Methodology:

Dr. Moore and I plan to employ the methods of digital humanists, public historians, historical archaeologists, and genealogists to reveal the names of slaves owned by Jared E. Kirby and their descendants, but the primary method we will use to promote research in the archives will be digital storytelling.

Results and Discussion:

For the Fall/Spring Semester of 2023-24, I worked alongside Dr. Moore and the DPPP undergrad students completing the task of processing the Negro Cooperative Extension & Home Demonstration Collection. In the fall, I continued my tasks from the summer and processed and

digitized pictures from the counties. In the spring, the team focused on processing all of the county boxes for the collection and reorganizing the documents. I also participated in the Wyatt Chapel Community Cemetery study, marking and scanning for possible graves.

In the fall, I completed digitizing all of the pictures and maps in the county boxes using the Epson Scanner. Using Microsoft Excel, I documented each item using metadata based off of the box, folder, and any information shared with the photo. I inserted the metadata in the Epson Scanner system and then scan the images. The Epson allows me to preview my scans and then create individual boxes around each item. I have been able to scan up to 8 photos at one time. I appreciate that feature as it allows me to prep the next documents metadata in the excel spreadsheet as it scans the other images. Once I uploaded the scanned images into the appropriate folder in our DPPP system, I convert each .tiff file into a .jpg file for a separate folder. This was necessary for us to be able to use the documents later in our blog posts on our website.

In the spring semester, Dr. Moore instructed us to put all of our focus on completing the task of processing all of the boxes for the collection. We reorganized, renamed, created new boxes and folders, and corrected the filing system for every box in the collection. I also began to correct the metadata in the excel sheet for the pictures that were reorganized.

Significance/Impact:

This project is significant because it urges Prairie View forward in protecting our history and creating our historical digital footprint. It also allows us the opportunity to know and learn from the hardships of the university’s past as well as, honor and water the beautiful seeds our ancestors planted for us. By continuing to preserve through digitization and promote the history of Prairie View A&M University, we protect and solidify the importance and beauty of our legacy.

Characterization of Titanium Nanoparticles prepared using a Traditionally Medicinal Plant and Evaluation of it’s Antioxidant and Cytotoxic Activity

Naiyah McDaniel and Harshica Fernando, Ph.D.* Department of Chemistry, College of Arts and Sciences

Introduction:

Titanium dioxide (TiO2) is a naturally occurring mineral used in domestic and cosmetic products as well as many other applications owing to its characteristics such as surface adsorption, photo catalysts properties and ultra violet absorption. Nano particles (NPs) of TiO2 have a wide range of applications and is used in pharmaceuticals. The biological method of preparation of NPs is increasingly being used and plants and in these cases plant extracts have been used as sources. Plant extracts have higher reduction potentials thereby reducing the time and the chemicals needed for NP preparation. In selecting plants, selecting plants that have a traditional medicine practice will increase the benefits of the synthesized NPs. Traditional medicine consists of health practices, approaches, knowledge, and beliefs incorporating plant-based medicines to treat or prevent illnesses. Research has found the acceptance of traditional medicine increasing as a reliable source of treatment because of its ease in accessibility and affordability. The medicinal plants possess secondary metabolites that form the backbone of this traditional medicine due to their capabilities in treating ailments such as cancer, bacterial, fungal, viral infections, and anti-inflammatory diseases. Plants of the Erythrina genus are native to the tropics of India and Malaysia. Erythrina Variegata belongs to this family of plants, and researchers have studied its phytochemical profile by examining its alkaloid and flavonoid compound presence. These compounds have traditionally aided in treating fever, inflammation, bacterial infection, insomnia, helminthiasis, cough, cuts, and wounds. Current research has examined the bioactive compounds of E. Variegata’s leaves, flowers, and roots. However, no studies have researched medicinal compounds in the plant’s bark and use it in the synthesis of NPs and investigating the applications of these NPs.

Objectives/Goals:

The objectives of the work were to carry out characterizations of the NPs using XRD, XPS and dynamic light scattering experiments, evaluate the redox properties using cyclic voltammetry experiments and to evaluate the antioxidant and cytotoxicity of the prepared NPs.

Methodology:

E. Variegata bark was finely ground into a powder using a food processor to obtain the plant’s extract. 100 mL of distilled water was added to the powder and boiled for 25 minutes. Titanium NP synthesis occurred using green methods by dissolving tetrabutile titanate. E. Variegata extract was added to the mixture under stirring until total precipitation and kept for drying in the incubator at 80 degrees Celsius. TEM images will be obtained using a JEOL 1200 EX microscope at an accelerating voltage of 100 kV. NPs will be sonicated in distilled water and filtered through a 0.2micron filter, and the sample solution pipetted onto a size 300 carbon-coated Cu grid. The particle size distribution of the NPs was obtained from XRD experiments and carried out using a wavelength of 1.540598 Å, with a 40 kV, 25 mA source, and scan type 2Ɵ Cytotoxicity assay was performed at University of Houston in collaboration with a professor at the Pharmacology department. Antioxidant potentials of the TiO2 alone and E. Variegata titanium NPs was be tested using 2,2, diphenyl-1-picrylhydrazyl solution. Butylated hydroxytoluene was be used as positive control and absorption measured at 517 nm.

Results and Discussion:

Titanium NPs using Erythrina Variegata was synthesized and characterized. Some characterized results are shown in Figure 1.

Figure 1. UV-Vis, FTIR, SEM and EDS data of the synthesized NPs. The data in Figure 1 shows the formation of titanium NPs of Erythrina Variegata bark. The presence of titanium is confirmed using the EDS data. The oxidative/reduction potentials of the extract and the NP’s prepared were compared using cyclic voltammetry and the profiles re shown in Figure 2.

Figure 2. Cyclic Voltammogram of E. variegata and Ti NP’s in PBS

The results clearly demonstrate the NP formation changes the redox properties of the plant extract.

Significance:

The results of this study indicate there is potential to use nanoparticles synthesized with E. variegate in many biomedical applications. Future studies should examine the extent these natural products can have in anticancer treatment, drug delivery, and addressing issues caused by reactive oxygen and nitrogen species in the environment and the human body.

References:

1. okunang C, Ndikum V, Tabi O, et al. Traditional medicine: past, present and future research and development prospects and integration in the National Health System of Cameroon. Afr J Tradit Complement Altern Med. 2011;8(3):284-295.

2. Khan T, Ali M, Khan A, Nisar P, Jan SA, Afridi S, Shinwari ZK. Anticancer Plants: A Review of the Active Phytochemicals, Applications in Animal Models, and Regulatory Aspects. Biomolecules. 2019 Dec 27;10(1):47. doi: 10.3390/biom10010047. PMID: 31892257; PMCID: PMC7022400.

3. doi:10.4314/ajtcam.v8i3.65276Buyel J. Plants as sources of natural and recombinant anticancer agents. Biotechnology Advances. 2018;36(2):506-520. doi:10.1016/j.biotechadv.2018.02.002

4. Odongo EA, Mutai PC, Amugune BK, Mungai NN. A Systematic Review of Medicinal Plants of Kenya used in the Management of Bacterial Infections. Evidence-based Complementary & Alternative Medicine (eCAM). March 2022:1-43. doi:10.1155/2022/9089360Oyenihi O, Oyenihi A, Erhabor J, Matsabisa M, Oguntibeju O. Unravelling the Anticancer Mechanisms of Traditional Herbal Medicines with Metabolomics. Molecules. 2021;26(21):6541. doi:10.3390/molecules26216541

5. Ouerghi et al., “Limon-Citrus Extract as a Capping/Reducing Agent for the Synthesis of Titanium Dioxide Nanoparticles: Characterization and Antibacterial Activity.”

6. Williams, B., Gautam, I., Grady, T., Fernando, H. Redox Properties and Temperature

Dependence of Silver Nanoparticles Synthesized using Pasteurized Cow and Goat Milk. Green chemistry letters and reviews. 2022, 15, 69-80.

7. Seydi, N., Mahdavi, B., Paydarfard, S., Zangeneh, A., Zangeneh, M. M., Najafi, F., Jalalvand, A. R., Pirabbasi, E. Preparation, characterization, and assessment of cytotoxicity, antioxidant, antibacterial, antifungal, and cutaneous wound healing properties of titanium nanoparticles using aqueous extract of Ziziphora clinopodioides Lam leaves Appl Organometal Chem 2019; 33:e5009.

Graphitic Carbon Nitride Catalyze Reduction of Azo Bond under Visible LED Light

Glory Goka Ollordaa, Emily Nneka Irikannu and Yingchun Li, Ph.D.* Department of Chemistry, College of Arts and Science

Introduction:

Graphitic carbon nitride (g-C3N4) has attracted great attentions of material scientists due to its interesting graphite-like layered structure and expected unique electronic properties for applications in various fields, such as hard material(Liu and Cohen 1989)，semiconductors (Lin and Wang 2013), catalysts and even as disinfectants. It has been well documented that g-C3N4 could be made from different precursors with different methods into different morphologies. Since the discovery of its photocatalytic capability of splitting water under visible light, most of research in the fields have been focused on the photocatalytic property of g-C3N4 and material based on it. It has been reported that g-C3N4 based material catalyze degradation of organic pollutants in water under visible light. One kind of such pollutants are azo dyes which have been released into environment as residues from fabric-dying industry in developing countries. The degradation of these compounds which is indicated by color disappearance has been attributed to oxidation by oxygen gas in the air catalyzed by g-C3N4 under visible light. Because hydrogen gas is a product in a water splitting process catalyzed by g-C3N4 under visible light, the color disappearance in degradation of azo dyes could also possibly be caused by reduction of azo bond to to hydrazine or amine. Here we report that g-C3N4 catalyze the reduction of azo dyes to amines under visible LED light using methyl orange (MO), methyl Red (MR) and alizarin yellow (AY) as examples.

Materials and Equipment:

1. Photocatalysts (g-C3N4) are prepared following a slightly reported method.

2. Azo dyes: methyl orange (sodium p-dimethylaminoazobenzenesulfonate, MO) is purchased from J.T. Baker Chemical Co.; methyl red (4-Dimethylaminoazobenzene-2′-carboxylic acid sodium salt, MR) from Mallinckrodt Baker; alizarin yellow R (sodium 2-hydroxy-5-[(E)-(4nitrophenyl)diazoenyl]benzoate, AY) from National Aniline Division, Allied Chemical corporation.

3. Furnace-Barnstead Thermolyne 1300. Centrifuge-minispin Eppendorf 5452, UV-spectrometer

4. LED light source

Methods:

Methods for preparation of photocatalysts

Photocatalysts used in our experiments are prepared using a previously reported method with slight modification. In general, melamine around 5 grams was ground and transferred into a porcelain crucible. The crucible was then covered with a porcelain cap, put into a muffle furnace, heated to the preset temperature and maintained at that temperature for a total time of 1 to 2 hours from starting of heating. After heating is stopped, the furnace cools down to room temperature and the product in the crucible is collected. The product was grounded ，characterized and used as photocatalysts.

Method for assessment of activity of photocatalyst

The assessment of photocatalytic effect of g-C3N4 on the reduction of azo dyes by hydrazine in aqueous solution was carried out with a method as described following. Into a glass Pyrex petri dish (100 mm in diameter and 20 mm in height) was added sequentially 50.0 mL of deionized water, 0.50 mL of hydrazine (99% in purity) and 25 mg of photocatalyst. The mixture is stirred magnetically at room temperature for 10 minutes. Then 1.50 mL of stock solution of methyl orange (1.00 mg/mL) is added into the mixture which is stirred for 5 minutes. The LED lights are turned on focused on the solution in the petri dish and timing started. For every 5-minute interval since light shedding on the sample, 1 mL of the reaction mixture was taken out and put into a 1.5 mL plastic snap-lock microcentrifuge tube. The suspension was centrifuged at 13,000 rpm for 10 minutes. The clear solution in the tube was then transferred into a 1 mL cuvette and its absorbance at 464 nm was measured with a uv-spectrometer. The plot of absorbance of the reaction mixture versus the reaction time under light showed the rate of the reaction in the presence of photocatalyst under LED light

The procedure has also been carried out for reduction of methyl red and alizarin yellow at the same reaction conditions except for the absorbance that are measured at 464 nm and 368 nm respectively. The reaction rate of reduction of each azo dye has been studied with the procedure described above at three different conditions: 1) presence of hydrazine but catalyst and light; 2) presence of hydrazine and catalyst but LED light. 3) presence of hydrazine and LED light but catalyst.

Results and Discussion:

Methyl Orange

To demonstrate the photocatalytic effect of g-C3N4 on the reduction of azo compounds by hydrazine, methyl orange was the first to be chosen as a model in this project because it has been wildly used in study of photocatalytic degradation of organic dyes. The visible LED light (15 W) is chosen as a light source in this study for three reasons: first, LED light is more energy efficient than 300 W Xenon lamp which has been widely used in previous studies; second, LED light does not raise the reaction temperature significantly due to it heating effect; and third, the LED light is safer than ultra violet light in biologically related applications.

METHYL RED DEGRADATION REACTIONS

hydarzine + no light + no catalyst

y = -0.0033x + 1.5768 R² = 0.9859

y = -0.0083x + 1.6493 R² = 0.9885 y = -0.005x + 1.6361 R² = 0.679

hydrazine + light + no catalyst

hydrazine + no light + catalyst

hydrazine + light + catalyst

Linear (hydarzine + no light + no catalyst)

Linear (hydrazine + light + no catalyst)

Linear (hydrazine + no light + catalyst)

Expon. (hydrazine + light + catalyst)

METHYL RED DEGRADATION REACTIONS

hydarzine + no light + no catalyst

y = -0.0033x + 1.5768 R² = 0.9859

y = -0.005x + 1.6361 R² = 0.679

y = -0.0083x + 1.6493 R² = 0.9885

y = 2.7455e-0.026x R² = 0.9428

hydrazine + light + no catalyst

hydrazine + no light + catalyst

hydrazine + light + catalyst

Linear (hydarzine + no light + no catalyst)

Linear (hydrazine + light + no catalyst)

Linear (hydrazine + no light + catalyst)

Expon. (hydrazine + light + catalyst)

ALIZARIN YELLOW DEGRADATION

REACTIONS

y = -0.0017x + 1.3772 R² = 0.5375

y = -0.0005x + 1.2299 R² = 0.453

y = -0.0025x + 1.3287 R² = 0.7483

y = 2.047e-0.026x R² = 0.9151

hydarzine + no light + no catalyst

hydrazine + light + no catalyst

hydrazine + light + no catlyst

hydrazine + light + catalyst

Linear (hydarzine + no light + no catalyst)

Linear (hydrazine + light + no catalyst)

Linear (hydrazine + light + no catlyst)

Expon. (hydrazine + light + catalyst)

Alizarin

Major products identified in the discoloration process.

Conclusion:

Our results demonstrated that azo compounds are reduced to amines in the initial stage of degradation catalyzed by g-C3N4 under visible LED light. The reduction leads to discoloration of the solution. Degradation of the amines to the ultimate product as carbon dioxide or carbonate needs to be studied further in the future. The experiments revealed that g-C3N4 made under temperature higher than 600 OC is of high photocatalytic activity. In addition to the reduction of azo bond to amine, a nitro group in organic compounds is also reduced to an amino group in this process. Therefore, this photocatalytic process may provide practical methods for reduction of other functional groups in organic synthesis.

Reference:

1. Lin, Z. and X. Wang (2013). "Nanostructure engineering and doping of conjugated carbon nitride semiconductors for hydrogen photosynthesis." Angewandte Chemie - International Edition 52(6): 1735-1738.

2. Liu, A. Y. and M. L. Cohen (1989). "Prediction of New Low Compressibility Solids." Science 245(4920): 841.

3. Lei Li, Huanhuan Liu, Chao Cheng, Xinyan Dai, Fang Chen, Jiqiang Ning, Wentao Wang, and Yong Hu 'Photochemical Tuning of Tricoordinated Nitrogen Deficiency in Carbon Nitride to Create Delocalized π Electron Clouds for Efficient CO2 Photoreduction'ACS Catalysis 0, 14, DOI: 10.1021/acscatal.4c01636

Disparities in Emerging Adults’ Depression and Roles of Greenspace and Social Networks

Ijeoma Ugochinyere Eze and Iyanda Ayodeji, Ph.D.*

Division of Social Sciences, College of Arts and Sciences

Introduction:

Depression significantly contributes to mortality, morbidity, disability, and economic burdens in the United States.1 There has been a steady increase in the occurrence of major depressive episodes among emerging adults, specifically those in their late teens to mid-to-late twenties. The rates have risen from 10.3% in 2015 to 17.2% in 2020 for individuals aged 18-25 and from 7.5% to 9.9% for those aged 26-34.2 This concerning trend underscores the fact that a substantial portion of emerging adults are contending with mental health challenges while transitioning into adulthood. This study draws from social identity theory and therapeutic landscape concepts.

Social identity theory provides insights into the psychological mechanisms through which individuals derive a sense of self and belongingness within the complex tapestry of social interactions. 3 Therapeutic landscapes exemplify the interplay between direct and digital social networks and their combined impact on physical and mental health. 4 This concept highlights how specific environments fostered through these networks can have healing or restorative effects on an individual’s well-being. The presence of natural environments, parks, and green spaces within one’s social networks has been incontrovertibly linked to ameliorating mental health, heralding reductions in symptoms of anxiety and depression.

Methodology:

Aim: The project aimed to investigate the impact of Spatial Social Networks and Environmental Exposure (SSNE) on emerging adult’s mental health.

Data: This quantitative cross-sectional study analyzed data (N= 1705) from the SSNE project data. Data were collected between February and October 2023.

Variables: The primary outcome variables are mental health measures using the 9-item Physical Health Questionnaire (PHQ-9) and the 21-item Depression, Anxiety, and Stress Scale (DASS-21).

Explanatory variables are Social class identity (SCI) and two mediating variables green space utilization (GSU) and social network (SSN).

Results:

Disparity: We identified a higher prevalence of depression among participants categorized as ‘racial and sexual minorities’ in our study (Table 1).

Table 1: Severity of depression among minority youth in the United States

Note: Non-minority is heterosexual/ White; racial/sexual minorities are members of LGBTQ+ and non-white groups.

Figure 1: Structural Equation of youth mental health in the United States

Impacts/Benefits:

References:

1. Friedrich MJ. Depression is the leading cause of disability around the world. Jama. 2017;317(15):1517-1517.

3. Postmes T, Wichmann LJ, van Valkengoed AM, van der Hoef H. Social identification and depression: A meta-analysis. European Journal of Social Psychology. 2019;49(1):110-126. doi:10.1002/ejsp.2508

EDUCATION

Education

And the Winner Is: Exploring Mental Health in Pageantry: A Qualitative Study

Mikayla Oberlton

and Selena D. Tate, Ph.D.*

Department

of Educational Leadership & Counseling, College of Education

Introduction:

Pageantry has been a taboo topic since its inception. Initially viewed as a beauty contest, these competitions scored women in various areas such as interviews, evening gowns, talent, fitness/swimsuits, and onstage questions. These contests allowed winners to earn scholarships, modeling and television contracts, salaries, crowns and sash, and many other opportunities. However, they are often scrutinized for requiring participants to reach an unobtainable level of perfection through any means necessary (Mejia, 2022.) Due to the recent loss of two prominent figures in the pageant community, Cheslie Kryst, Miss USA 2019, and Kaila Posey, a Toddlers and Tiaras child star, both to suicide, many of the mental health issues in this arena have become amplified (Pearson, 2023.)

Several researchers discussed the pressures from sponsors, family, other competitors, and societal standards of beauty that impact the mental well-being of those who participate in the sport (Sy et al., 2021.) Furthermore, in a study on childhood pageant contestants, the idea that many of them suffered both physical and psychological repercussions following their time in pageantry illuminated the need to understand the unique mental health outcomes for this group (Wonderlich et al., 2005.) However, there is a lack of research done on pageantry. Due to this limitation, this study will aim to research the psychological and behavioral implications of competing in pageantry. It is crucial to understand the mental health needs within this niche community.

Objectives:

This study will expand the research literature beyond pageantry and eating disorders (Wonderlich et al., 2005) by shifting attention to the psychological and behavioral implications of competing in beauty pageants. Thus, this qualitative study aims to:

• Examine the lived experiences of pageant participants.

• Examine and increase the awareness of how pageantry may impede competitors' mental wellbeing.

• Examine the familial history in pageantry.

The researchers seek to answer the following questions: What are the experiences of beauty pageant titleholders and competitors? and is there a relationship between pageantry and mental distress?

Methods:

This study will utilize qualitative methods to explore the lived experiences of pageant participants. Specifically, a phenomenological approach was used to investigate mental health in pageantry, as this method was useful when exploring an uncommon phenomenon with limited or no literature. Convenient sampling was used to recruit individuals identified as current titleholders, past titleholders, current competitors, or past competitors were recruited to participate in this study. Recruitment occurred through three social media channels: Facebook, Twitter, and Instagram. Participants completed an informed consent form, a demographic questionnaire, and two semi-structured virtual interviews. Data was analyzed using the interviews and family genograms.

Results and Discussion:

Five core themes were extracted from the data.

• Pressure to perform: Some participants reported feeling pressure from family, pageant sponsors, and directors. One participant commented about her experience with her director: "Because there's someone that I looked up to at the time and I still do but they're feedback was and I remember this was, get your wardrobe together. And it was blunt and presented to me in kind of a harsh manner. And at the time I was already feeling a little disappointed in myself for not doing as well as I had thought that I was going to do so. To get that feedback in that manner really set me back."

• Sisterhood: All participants stated that pageantry exposed them to a sisterhood that allowed them to build relationships and lifelong friendships with "like-minded individuals. Another participant stated:

"And, every (um) girl is, you know, not the typical ditzy pageant girl that you would think of. They're all very intelligent women and that you can learn from and it's just completely opposite of what, (um) maybe television or the cliches portray it to be. It is very…the girls are a lot deeper and (um) kinder than what I had expected them to be."

• Physical experience: Participants identified positive elements of engaging in pageantry, but some felt there was a lack of awareness concerning the needs of non-White contestants. For example, sponsors failed to provide adequate hairstyle choices for ethnic hair texture or make-up for ethnic skin tones. In addition, some observed preferential treatment of some contestants.

"Actually, being in that environment, being in that competition, and then seeing how girls of a certain demographic and class were just set up to win. And then seeing how all of your differences and the things that you felt were unique about yourself didn't really matter. And in some ways just kind of set you back.

• Mental distress: Reportedly, some of the participants experienced mental distress due to the lack of familial support, differing expectations of the contestant and their director or sponsor, and issues with their self-identity when not meeting performance expectations during competitions.

"I had to be put on medication because when it's pageant season and things are approaching I feel like there's so much to do. And I have to research this and think about that. And I gotta raise this money too."

Implications and Benefits:

When working with the pageantry community, mental health professionals must be aware of their own biases to prevent issues related to building a safe therapeutic relationship and experience. Moreover, the pageantry organizations must be aware of and provide mental health resources within the pageantry community, as such efforts may remove the adverse stigma of mental health issues.

The researchers are working to complete an article to be published in a peer-reviewed journal. The study's publication will expand the existing literature beyond the impact of pageantr y and eating disorders

References:

1. Sy, M. P., Martinez, P. G., & Twinley, R. (2021). The dark side of occupation within the context of modern-day beauty pageants. Work, 69(2), 367–377. https://doi.org/10.3233/wor-205055

2. Thompson, S. H., & Hammond, K. (2003). Beauty is as beauty does: Body image and self-esteem of pageant contestants. Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity, 8(3), 231–237. https://doi.org/10.1007/bf03325019

3. Wonderlich, A. L., Ackard, D. M., & Henderson, J. B. (2005). Childhood beauty pageant contestants: Associations with adult disordered eating and mental health. Eating Disorders, 13(3), 291–301. https://doi.org/10.1080/10640260590932896

Untold Stories of URM Middle School STEM Teachers

Jenaye Love-Perkins and Camille S. Burnett, Ph.D.*

Curriculum and Instruction, College of Education

Introduction:

There is a critical need for recruiting, preparing, and retaining science, technology, engineering, and mathematics (STEM) teachers. It is well known that there is a shortage of K-12 STEM teachers nationwide (Cross, 2017; Feder, 2022). Moreover, fewer than 20 percent of mathematics and computer science teachers and fewer than 20 percent of natural science teachers identify as underrepresented and racially minoritized (URM) persons (National Center for Education Statistics, 2011-2012). This shortage of STEM teachers is caused by supply and demand factors (Cowan et al., 2016). The supply of STEM teachers is low; that is, an insufficient number of STEM teachers are being prepared (Fuller & Pendola, 2019). In contrast, the demand for STEM teachers is high; that is, attrition and turnover rates of STEM teachers are problematic in many high-need local educational agencies (Fuller & Pendola, 2019). Little is known about how URM middle school STEM teachers choose their profession and remain in their profession despite the factors that lead to high attrition and turnover rates. Thus, there is a critical need to understand how URM middle school STEM teachers select the K-12 setting for their career and persist in the K-12 setting despite the challenges. Without this knowledge, educators and policymakers will be unable to create effective teacher recruitment, preparation, and retention strategies, and the shortage of URM STEM teachers will continue.

Objectives/Goals:

The goal of this proposed project was to understand the journey taken by URM middle school STEM teachers to enter their profession to better inform recruitment, preparation, and retention strategies. For the proposed project, the journey into the teaching profession will include before, during, and after the teacher preparation phase. The initial interpretation of the phenomenon of this journey is that the pathways to and through teaching for URM middle school STEM teachers are unique and meaningful for each person yet may have intersecting commonalities and can be used to inform teacher recruitment, preparation, and retention practices. Thus, the objective of

the proposed project was to report the stories of URM middle school STEM teachers’ journey to and through the teaching profession

Methods:

The first phase of the project began with a scoping review to assess the potential size and scope of theoretical frameworks used to explain career choice, STEM career choice, teaching career choice, and more specifically, STEM teaching career choice. Several article searches were conducted. The one that proved most fruitful used keywords such as “STEM teachers,” “Preservice teachers or student teachers or pre-service teachers or prospective teachers or teacher candidates,” and “career choice or career decision or career selection or career motivation.” The number of articles was reduced by focusing on articles written in English within the last 20 years, peer-reviewed, and the full text was available through our library. Articles that focused on special education or pre-school and elementary school teachers were excluded from the collection. Eligible theories were tabulated and described.

The second phase of the project focused on instrument development. Three instruments were drafted – the Participant Profile Questionnaire, the Interview Protocol, and the Artifact Protocol (see Results and Discussions for more details). Additionally, the IRB Application for the project was drafted.

The third phase of the project was to include data collection through the following steps:

1. Identify participants.

2. Obtain participants’ consent.

3. Collect participants’ profile information.

4. Interview participants (must be video-taped).

5. Examine relevant artifacts.

6. Transcribe interviews.

The fourth phase of the project was to entail data analysis. This phase was to commence after the first participant’s three-part interview sequence was transcribed. The plan was to use the

following sequential analysis steps adapted from Mills & Gay (2019) and Fisher’s Narrative Paradigm (Communication Theory, 2014) as a framework.

1. Identify key elements of the story.

2. Review artifact data.

3. Rewrite the stories.

Data analysis would then be followed by member checks, i.e., participants would have the opportunity to review their stories before dissemination to ensure the credibility, and therefore the trustworthiness (Mills & Gay, 2019) of the stories reported.

Results and Discussion:

Before the first phase of the project could begin, the research assistant was required to complete several trainings including CITI, Qualtrics, and Library Use. Upon completion of these trainings, then the first phase of the project began. The third and final search for articles yielded 382,203 articles available through our library, but after applying several limitations, the number of articles was reduced to 108. The articles were all carefully reviewed. Social Cognitive Career Theory, FIT-Choice model, and Tripartite Framework emerged from the literature reviewed. These were used to answer the research question, “What theoretical and/or conceptual frameworks have been used to explain why STEM teachers choose their profession?” and to complete the scoping review.

Three instruments were drafted during the second phase of the project – the Participant Profile Questionnaire, the Interview Protocol, and the Artifact Protocol. The Participant Profile Questionnaire includes questions about demographics, educational background, teacher preparation, professional experience, and other information that may be useful in developing a profile of each participant. It also requests additional location and contact information for each participant as a means of planning for later interview data collection. The Participant Profile Questionnaire was drafted in Qualtrics to ensure that the data is systematically collected, safely stored, and easily accessible for later analysis. The Interview Protocol is divided into three sections (see Table 1), adapted from the in-depth interview structure developed by Seidman (2006). The interview questions ask the participants to describe the who, what, where, when, why, and how of their journey to and through the teaching profession to better understand the

participants’ experiences. The Artifact Protocol is an intake sheet that will be used to log relevant information about the artifact. It allows for a description of the type of artifact and the connection of the artifact to the participant’s journey to and through the STEM teaching profession. Depending on the nature of the artifact, a photograph, hyperlink, or other documentation is also included in the Artifact Protocol to aid in later analyses and triangulation of data. Like the Participant Profile Form, the Artifact Protocol is housed in Qualtrics to ensure that the data is systematically logged, safely stored, and easily accessible for later analysis.

Table 1. Sample Interview Questions

Interview

Sample Interview Questions

1. Life History How did the participant come to be a secondary STEM teacher?

2. Contemporary Experience What is it like for the participant to be a secondary STEM teacher? What are the details of the participant’s work as a secondary STEM teacher?

3. Reflection on Meaning What does it mean to the participant to be a secondary STEM teacher? How does the participant make sense of their work as a secondary STEM teacher?

Impact/Benefit:

The findings from the scoping review were presented at the annual Research Association of Minority Professors Conference in Washington, DC. in February 2024 (see Love-Perkins et al., 2024). Phase 3 of the project will begin in Summer 2024 after IRB approval is received. The findings obtained from this project will be used to support the development of a proposal for the NSF Faculty Early Career Development Program.

References:

1. Communication Theory (2014, July 7). The narrative paradigm. https://www.communicationtheory.org/the-narrative-paradigm/

2. Cowan, J., Goldhaber, D., Hayes, K., & Theobald, R. (2016). Missing elements in the discussion of teacher shortages. Educational Researcher, 45(8), 460-462.

3. Creswell, J. W., & Poth, C. N. (2017) Qualitative Inquiry and Research Design: Choosing Among Five Approaches. Sage.

4. Cross, F. (2017, May). Teacher shortage areas: Nationwide listing 1990-1991 through 2017-2018. U.S. Department of Education, Office of Postsecondary Education. https://www2.ed.gov/about/offices/list/ope/pol/bteachershortageareasreport201718.pdf

5. Feder, T. (2022). The US is in dire need of STEM teachers. Physics Today, 75(3), 25-27. https://doi.org/10.1063/PT.3.4959

6. Fuller, E. J., & Pendola, A. (2019). Teacher preparation and teacher retention: Examining the relationship for beginning STEM teachers. American Association for the Advancement of Science.

7. Love-Perkins, J., Barnett-Price, S., Lemons-White, K., & Burnett, C. (2024). Why a STEM teacher? A review of the frameworks. 41st Annual Research Association of Minority Professors Conference, Washington, DC.

8. Mills, G., & Gay, L. (2019). Educational research: Competencies for analysis and applications (12th ed.). New York, NY: Pearson.

9. National Center for Education Statistics. (2011-2012). Percentage distribution of teachers, by school type, race/ethnicity and selected main teaching assignment: 2011–12 [Data table]. https://nces.ed.gov/surveys/sass/tables/sass1112_21022407_t12n.asp

10. Riessman, C. K. (1993). Narrative analysis. Sage.

11. Seidman, I. (2006). Interviewing as qualitative research: A guide for researchers in education and the social sciences (3rd ed.). Teachers College Press.

One and Done: Moving Teacher Candidates through the Teacher Preparation and Certification Program at an HBCU Institution in Texas

Myltazaire K. Crayton and Beverly King Miller, Ph.D.*

Department of Curriculum and Instruction, College of Education

Introduction:

There is a severe teacher shortage within the United States (U.S. Department of Education Office of Postsecondary Education, 2017). Teacher education institutions in Texas are tasked with producing teacher education candidates who are content certified demonstrating content knowledge and education pedagogy. As a result, institutions have established testing certification offices within their institutions to support educational candidates who must not only pass their course content requirements, but also meet the testing requirements to graduate certified for the workforce demands.

Historically Black Colleges and Universities (HBCU) are vital in addressing the need for a diverse workforce. HBCUs make up only three percent of the country’s colleges and universities yet they enroll 10% of all African American students and produce almost 20% of all African American graduates (uncf.org, 2023). HBCU’s in the Texas are tasked with developing Teacher Preparation Programs (TPP) that can produce qualified teachers who can also pass the Texas Education Agency (TEA) content and examinations that result in certification. This will contribute to a diverse teacher workforce.

The PhD student’s research agenda is concerned with the marginalization of pre-service teachers due to a national curriculum that excludes underrepresented and historically minoritized groups ( URM). As a result, this year the focus also included her own research work to ensure her research skills in general are sharpened.

Objectives/Goals:

This research that we worked on together seeks to address the following questions: what is the effectiveness of the testing strategies and software support for the successful completion of teacher candidates in a Teacher Preparation and Certification program at an HBCU in Texas? What do students perceive are challenges and supports that affect the accomplishment of the testing protocols and requirements associated with the TPP Certification office?  This research tracks the progress of students on the software practice exams and their responses to a pre and

mid semester check survey. She was part of the faculty team who presented on this work at the Research Association for Minority Professors( RAMP) in Feb. 2024.

A second goal for this year was the development of a researcher who could produce a strong literature review and defend an argument. She was challenged to hone and sharpen her own research agenda towards the completion of her PhD. As a result, she was supported in two additional presentation opportunities to garner feedback about her work.

Materials and Methods:

This mixed methods study (Creswell and Plano Clark, 2017), presents data collected through two primary sources: anonymous surveys to garner qualitative data, and quantitative data from the results of the software practice exams required of students in the HBCU TPP. Participants included 31 students from the Teacher Education program seeking certification.

A separate E-Course shell was created for students to add the testing information from three software programs. No grades were given for submissions or survey completion so students could be transparent on the survey questions. Data came from three separate software testing sites: Certified Teacher practice exams, 240 Testing modules, and T-Cert quizzes. For the initial manuscript to be submitted this summer, we only used the Certified Teacher data which included 5 examinations taken from January to June.

Significance and Impact:

This pilot study done in the Spring of 2023 attempted to explore the throughput data of Teacher Candidates who completed the requirements and were successful on the TEA content exam of at an HBCU EPP in Texas. It showed that of the 20 students who were pre-education majors, 14 graduated through the program, resulting in a 70% pass rate. Future study is needed to assess the throughput to better understand the support received by this group of students. The PI and GA are working on a manuscript to reflect the data information. This project however, will not be the focus for the PI for 2024-2025.

Summary of Synergistic Activities 2023-2024

Synergistic Activities RAMP Feb. 2024 RISE PhD Student accomplishments

Conference

Presentations

1.Crayton, M ( Feb. 2024) Examination of Cultural Confluence within the K-12 Curriculum: Combating the issue of Cultural Competency in Higher Education. 41st Research Association of Minority Professors Conference. Washington, D.C.

2.King Miller, B.A., Crayton, M. Burnett, C., Sande, B. (Feb. 1-4 2024). One and Done: Moving Teacher Candidates through the Teacher Preparation and Certification Program at an HBCU Institution in Texas. 41st Research

Crayton, M.(April 2024) Examination of Cultural Confluence within the K-12 Curriculum: Combating the issue of Cultural Competency in Higher Education. Conference for Interdisciplinary Student Research (CISR)

PhD Candidate Goals

Association of Minority Professors Conference. Washington, D.C.

References:

Completed and passed Comprehensive Examination for Educational Leadership

1. Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.

2. UNCF. (2023, June, 14) The Numbers Don’t Lie: HBCUs Are Changing the College Landscape. uncf.org. https://uncf.org/the-latest/the-numbers-dont-lie-hbcus-are-changingthe-collegelandscape#:~:text=Some%20of%20the%20most%20heartening,of%20all%20African%20A merican%20graduates

3. NCES. (2022, Dec. 6) Forty-Five Percent of Public Schools Operating Without a Full Teaching Staff in October, New NCES Data Show. Nces.ed.gov. https://nces.ed.gov/whatsnew/press_releases/12_6_2022.asp?utm_content=&utm_medium=e mail&utm_name=&utm_source=govdelivery&utm_term=

The Importance of Minority Teacher Preparation: Tapping the Community College Pipeline to continue the legacy of HBCU’s

Britine Perkins, Ph.D.*

Department of Curriculum and Instruction, College of Education

Introduction:

Texas school districts are becoming increasingly diverse, yet the teachers, principals, and other staff remain predominantly Anglo. As the state’s minority public school enrollment grows, increased districts, especially those in urban areas, recognize that all students deserve to see their ethnicities represented in their education community (Texas Education Agency [TEA], 2020). In addition, ethnically and culturally diverse teachers can smooth minority students ’ transitions to school by serving as cultural translators who build upon the communication and behavioral styles of minority students (Darling-Hammond, 2006; Milner, & Hoy, 2003, NCES, 2021). However, it is increasingly difficult to attract and maintain quality minority candidates in many teacher education programs despite employment opportunities in struggling PK-12 public schools. About 15% of students in teacher preparation programs represent individuals of color, and if past retention trends hold, only two-thirds of these students will become teachers (Darling-Hammond & Berry, 1999). To become a teacher, a college degree is a necessary first step. However, Colleges of Education are not known for their diversity, as evidenced by the previously mentioned statistics regarding the teaching population nationwide. The ingrained racism of teacher education documented in the literature is no surprise to us. Teacher education continues to center on the needs, preparation, and humanity of White teachers (Milner et al., 2013). The two areas of higher education that are diverse and becoming even more so is the community college and HBCUs. In the last 20 years, community colleges’ role in teacher education has become more prominent (Townsend, 2007). Yet, few of these programs have been studied for success levels in adding to the number of employed certified teachers who are minorities. To understand the impact these programs, have, an in-depth case study is needed.

Objectives/Goals:

The overall objective is to examine the effectiveness of one community college’s pre-service program in transferring minority students to a HBCU (Historically Black College or University)

teacher education program and the likelihood of the students graduating with bachelor's and teacher certification by considering the following research questions:

• What kinds of support exist at LSC (Lone Star College) for preparing minority students to successfully complete a teacher certification degree?

• Are there differences in the PVAMU (Prairie View A&M University) and TSU graduation rates for the LSC transfer cohort graduates and the traditional (non-transfer) graduates in the teacher education programs at PVAMU and TSU?

Materials and Methods:

The research study aims to examine the effectiveness of one community college ’s pre-service program in transferring minority students to a HBCU teacher education program and the likelihood of the students graduating with certification. A systematic literature review was done to focus on four sections: 1.Teacher Education as the Foundation for HBCU’s 2. The Community College and Preservice Teacher Education (US/TX) 3. The Teacher Shortage (US/TX) 4. Addressing the Minority Teacher Shortage. This study is a mixed methods case study and involve tracking a minority cohort of students over a set period (considering 5 or 6 years for graduation Timeline).

Archival data for students entering LSC in the fall semester of 2014 have been collected to answer the graduation rate and transfer rate research questions. The researchers are now comparing minority students’ graduation and transfer rates to traditional students’ graduation and transfer rates.

Results and Discussion:

Participants will be selected from archival data obtained from Lone Star College Pre-Service Teacher Education cohort members who have successfully transferred to or graduated from PVAMU or TSU obtained through their respective Offices of Institutional Research. Along with the artifacts and documents will include applicable community college and university catalogs and webpages, LSC pre-service teacher education program information, PVAMU’s and TSU’s College of Education admissions and degree requirements, and LSC marketing materials. The researcher will use all available data to code and organize the categories and themes for the data analysis.

Limiting the study to a specific transfer cohort from LSC during a specified period will help provide a finite number of students cases for el aborating on the case studied. The research

questions will be analyzed qualitatively using artifacts collected from LSC, survey instrument, and utilizing unstructured interviews with the appropriate personnel at LSC. The research questions will also be analyzed by using categorical data provided by LSC, PVAMU, and TSU, and χ2 to compare the transfer and graduation rates for LSC cohort students and traditional (non transfer) PVAMU and TSU teacher education students.

Impact and Benefit:

This research study allows identifies what strategies are needed in teaching for equity and the need for culturally proficient educators. This will continue to be a critical issue in education and our nation’s development. This research study will add to the knowledge related to minority teacher preparation. I intend to continue this research trajectory by applying for grants. I also intend to present this research at several conferences this upcoming academic year. The researcher is a RISE cohort member and will utilize the Office of Research and Innovation to help identify and apply for grants with agencies that would benefit by the results of this research. There are also implications for doing more research to expand the current study.

References:

1. Darling-Hammond, L. (2006). Powerful teacher education: Lessons from exemplary programs. San Francisco, CA: Jossey-Bass.

2. Darling-Hammond, L., & Berry, B. (1999). Teacher supply and demand. Washington, DC: American Council of Education.

3. Milner, H. R., & Hoy, A. W. (2003). A case study of an African American teacher’s selfefficacy, stereotype threat, and persistence. Teaching and Teacher Education, 19, 263-276.

4. National Center for Education Statistics (2021). Characteristics of public school teachers. The Condition of Education. 1-7.

5. Texas Education Agency. (2020). Enrollment in Texas Public Schools, 2019-20. Austin, TX: TEA Division of Accountability Research, Department of Assessment, Accountability, and Data Quality. Retrieved from http: https://tea.texas.gov/sites/default/files/enroll_2019-20.pdf

6. Townsend, B. (2007). Pre-service Teacher Education in the Community College. Community College Review, 35(1), 4-9.

ENGINEERING

Engineering

Development of a Remote Patient Healthcare Cloud Architecture and Evaluation Using Queuing Modeling

Ifeakandu Moses Nzekwe and Justin Foreman, Ph.D.*

Department of Electrical and Computer Engineering, College of Engineering

Introduction:

Remote patient care using internet of things is becoming an increasingly important aspect of actively managing a patient’s health with the expected outcome of mitigating decline or death by being able to monitor health state consistently, detect abnormalities and respond in a timely fashion to emergencies. [3][12]. The increase in health care data management and services necessitates moving such operations to the cloud for improved performance and making for a smart health care system [1]. The architecture for such services in the cloud, or cloud computing(architecture), according to National Institute of Standards and Technology is: “…. a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction” [4]. Due to the increase in patients relying upon remote health services, especially during and after COVID, design of these services for optimal performance is necessary for improving qua lity of care, reducing operational cost and increasing customer satisfaction.

Objectives/Goals:

The goal of study was to investigate the application of queuing theory for improved health cloud architecture services. We evaluated simulation tools, to identify the most reliable ones for the selected architecture; We also gained additional knowledge of cloud architecture platforms, simulation tools The simulation tools were used to simulate a cloud architecture, allowing for evaluation of performance between Python and JavaScript.

system flow chart

This queue flow chart for remote patient management in healthcare facilities is meticulously designed to ensure efficient, fair and timely treatment for all patients.

The prioritization method development and evaluation

1. Patient queue sorting

• Input: List of patients with timestamps.

• Criteria for sorting: Patients can be sorted based on urgency, severity, or arrival time (FIFOfirst in, first out, LIFO-last in first out) .

2. Maximum patient limit per doctor

 Rule: Each doctor can handle a maximum of five patient at a time.

 Action: If s doctor already has five patients, the system should call a second doctor.

3. Patient Authentication

 Step: Authentication each patient before assigning them to a doctor . This ensures that only legitimate patients receive care.

4. Patient Assignment

 Rule; Assign patients to available doctors in the order determined by the sorting criteria.

 Load balancing: If doctor 1 has reached the patient limit, new patients are assigned to doctor 2

Materials and Methods:

In this study, we performed a literature review of current healthcare cloud architectures for remote patient care monitoring, after which we employed simulation tools and performance metrics on AWS, which was chosen as our cloud platform.The simulation tools were used to simulate a cloud architecture, allowing for evaluation of performance between Python and JavaScript. The results obtained from both tools were compared to mathematical models. RESTful APIs were utilized to leverage the interoperability, scalability, and flexibility they offer in remote healthcare services.

Results and Discussions:

Based on the simulation results, this study demonstrates that Python outperforms JavaScript in real-time data processing value insights for the development of more efficient remote healthcare systems.

Moreso, in scenarios characterized by high customer demand and high service capacity, our study indicates that the system is exceptionally well-prepared to manage increased demand efficiently. This is a crucial objective for healthcare providers aiming to deliver superior patient care, particularly during peak periods or times of heightened activity. A well-balanced and optimized system ensures that patients receive prompt attention and care without enduring long wait times or experiencing frustration.

Impacts/Benefits:

This study has the potential to revolutionize healthcare delivery, making it more patient-centric, efficient, and adaptable to evolving healthcare needs. This study contributes to the existing body of knowledge by providing insights into the design, implementation, and evaluation of such systems, with a focus on queuing modeling for performance optimization.As the demand for remote healthcare continue to rise, particularly in the post-pandemic era, this optimization will be essential in delivering timely and effective healthcare services.

References:

1. Aceto, G., Persico, V., Pescapé, “A. Industry 4.0 and health: Internet of things, big data, and cloud computing for healthcare 4.0.” J. Ind. Inf. Integr. 2020, 18, 100129.

2. Albalawi, U., Joshi, S., “Secure and trusted telemedicine in Internet of Things I oT.” In Proceedings of the 2018 IEEE 4th World Forum on Internet of Things (WF -IoT), Singapore, 5–8 February 2018; pp. 30–34.

3. Iranpak, S., Bahrami, A., Shakeri, H., “Remote Patient Monitoring and classifying using the internet of things platform combined with cloud computing” Journal of Big Data vol 8 no 120, 2021 pp 1-22.

4. Botta, A., De Donato, W., Persico, V., et al. “Integration of cloud computing and internet of things: a survey,” Future Gener. Computer. Syst., 2016, 56, pp. 684–700.

Machine Learning-Based Prediction of Free Ige Concentration in Allergic Rhinitis Patients Treated with Allergen Immunotherapy and Omalizumab

Laura Marthe Emilie, Ngansop Djampou and Kazeem Olanrewaju, Ph.D.*

Department of Chemical Engineering, College of Engineering

Introduction:

Immunoglobulin E (IgE) is an antibody integral to the development of allergic diseases. When an allergic individual is exposed to an allergen, their body produces IgE antibodies that bind to the allergen[1], [2]. This binding induces the release of histamine and other inflammatory mediators, leading to the symptoms of an allergic reaction[2]. The concentration of free IgE in the blood represents the quantity of IgE antibodies not bound to allergens and serves as a crucial biomarker for allergic diseases, aiding in diagnosis and monitoring[3], [4]

Allergen immunotherapy (AIT) involves gradually exposing a person to increasing doses of an allergen to desensitize them. Omalizumab is a monoclonal antibody targeting IgE, utilized in treating severe allergic asthma and other allergic diseases. Predicting free IgE concentration can enhance the diagnosis and monitoring of allergic diseases. For instance, a high free IgE concentration correlates with a higher likelihood of an allergy, and tracking free IgE over time can help gauge the efficacy of AIT and omalizumab treatment[5]-[8].

Machine learning (ML), a subset of artificial intelligence, excels in learning from data and making predictions. ML algorithms are emerging as powerful tools for predicting free IgE concentration and other immunological biomarkers in allergic patients [9]-[12]. This study aims to employ a machine learning algorithm to predict free IgE levels in patients with allergic rhinitis undergoing allergen immunotherapy and treatment with omalizumab. Developing ML -based prediction models for free IgE concentration in these patients would signify a major ad vancement in allergy management. These models could assist clinicians in more effectively diagnosing and monitoring allergic rhinitis and evaluating the success of AIT and omalizumab treatment.[13]-[15]

Objectives/Goals:

The objective of this research is to develop and validate predictive models using machine learning techniques to estimate free Immunoglobulin E (IgE) concentration in patients with allergic rhinitis who are undergoing treatment with allergen immunotherapy (AIT) and omalizumab.

Methodology:

The study utilized the Immune Tolerance Network (ITN) TrialShare[16], [17] repository to extract comprehensive immunotherapy datasets for developing a predictive model for free IgE concentration. Initial steps included accessing and filtering relevant studies, exporting data as Excel files, and uploading them to the Orange Data Mining Platform for preprocessing. Preprocessing involved data cleaning, integration, reduction, transformation, and discretization to prepare the datasets for machine learning. The machine learning phase within the Orange Data Mining Platform identified predictors and target variables, with free IgE concentration as the target. Several supervised machine learning algorithms, including k-nearest neighbors, decision trees, linear regression, random forests, ANN, gradient boosting, and SVM, were considered. The dataset was split into training (70-80%) and testing (20-30%) subsets, and missing values were handled through various strategies. Model performance was evaluated based on metrics like R2, MSE, RMSE, and MAE, with R2 being the primary determinant. The process concluded with selecting the best-performing algorithm to predict free IgE concentration accurately.

Results and Discussion:

Different scenarios for addressing missing values and the performance metric results

Scenario 1: imputing missing values with the average/most frequent value

The missing values in the datasets were addressed by imputing the missing free IgE values with the average or most frequent values, using a 10-fold cross-validation approach on an 80% training and 20% testing dataset split for the machine learning algorithm (MLA) model for predicting free IgE concentration. Additionally, the parameters for each MLA were tuned to achieve optimum performance. The performance metrics for this approach are displayed in the Test and Score widget window. Figure 1 illustrates the metric performance of the trained and tested MLAs. The decision tree emerged as the best performing MLA, with optimal parameters set at 29 for the minimum number of instances in leaves and split subsets not smaller than 80. In contrast, the worstperforming model, linear regression, reached its optimum with an alpha parameter of 30 for ridge regression, as shown in Figure 2.

Figure 1: Test and Score showing the model evaluation metric for the MLAs under scenario 1

Figure 2: Linear regression and Decision Tree parameter windows under scenario 1

Scenario 2: Replacing missing values with random value

Missing values in the dataset were replaced with random values. The dataset was then divided into 10 folds, with 80% of the data used for training the machine learning algorithms and the remaining 20% for testing and parameter tuning. The decision tree algorithm emerged as the best performer,

exhibiting the lowest errors compared to other algorithms, with an optimum parameter setting of 29 for the minimum number of instances in leaves and split subsets not smaller than 120. The Support Vector Machine (SVM) was the worst-performing algorithm, with optimum parameters at a cost (C) of 24.00 and a regression loss epsilon (ε) of 4.10, using the RBF kernel.

Figure 3. Decision Tree and Support Vector Machine parameter windows under scenario 2

Figure 4: Test and Score showing the model evaluation metric for the MLAs under scenario 2

Scenario 3: Removing rows with missing values option

Missing values in the dataset were managed using 10-fold cross-validation. We allocated 80% of the data for training the machine learning algorithms (MLAs) and reserved 20% for testing the MLA models used to predict free IgE concentration, resulting in a reduction in the dataset size from 717 to 418 instances. The parameters of each MLA were fine-tuned for optimal performance. The outcomes of this approach, including performance metrics, are displayed in the Test and Score widget window. Figure 5 presents the performance metrics for the trained and tested MLAs. Among the considered algorithms, the neural network emerged as the best-performing model, as depicted in Figure 8, with an optimal configuration of three hidden layers containing 50, 100, and 50 neurons, ReLU activation, and a regularization parameter (α) set to 0.05. The model was trained and tested for up to 500 iterations. In contrast, the least effective model was linear regression, specifically the ridge regression variant, which achieved its best performance with an alpha value of 30, as shown in Figure 6

. Figure 5: Test and Score showing the model evaluation metric for the MLAs under scenario 3

Figure 6. Neural Network and Linear Regression parameter windows under scenario 3

Significant and Impact:

This study aims to develop a machine learning model to predict free IgE concentration in patients with allergic rhinitis treated with AIT and omalizumab. The dataset, sourced from Immune Tolerance/TrialShare, contains data from clinical trials of immunotherapy. Preprocessing steps were undertaken to address inconsistencies, duplications, noise, and missing data. Several machine learning algorithms were trained and tested on the preprocessed dataset, with the best-performing algorithm selected for the final prediction model. Potential applications for this model include diagnosis, monitoring, and personalized treatment of allergic rhinitis. To handle missing free IgE concentration data, four strategies were employed: replacing missing values with the average/most frequent values, using random values, removing instances with miss ing values, and replacing missing values with predictions from the machine learning model. The fourth scenario yielded the best performance, achieving a coefficient of determination (R2) of 0.582, a notable result for human-involved datasets. Among the predictor variables, the treatment group had a significant impact on free IgE concentration predictions, while weekly visits with or without treatment had negligible impact. The decision tree algorithm emerged as the best performer, exhibiting the lowest errors compared to other models.

References:

1. J. Eckl-Dorna et al, "Tracing IgE-Producing Cells in Allergic Patients," Cells, vol. 8, (9), pp. 994. doi: 10.3390/cells8090994, 2019. . DOI: 10.3390/cells8090994.

2. P. Stoffersen et al, "The Allergen-Specific IgE Concentration Is Important for Optimal Histamine Release From Passively Sensitized Basophils," Frontiers in Allergy, vol. 3, pp. 875119, 2022.

3. M. Carlsson et al, "Variability of total and free IgE levels and IgE receptor expression in allergic subjects in and out of pollen season," Scand. J. Immunol., vol. 81, (4), pp. 240-248, 2015.

4. J. Corren et al, "Allergen skin tests and free IgE levels during reduction and cessation of omalizumab therapy," J. Allergy Clin. Immunol., vol. 121, (2), pp. 506-511, 2008.

5. P. P. Belliveau, "Omalizumab: a monoclonal anti-IgE antibody," Medscape General Medicine, vol. 7, (1), pp. 27, 2005.

6. R. G. Hamilton et al, "Advances in IgE testing for diagnosis of allergic disease," The Journal of Allergy and Clinical Immunology: In Practice, vol. 8, (8), pp. 2495-2504, 2020.

7. R. G. Hamilton, "Assessment of human allergic diseases," in Clinical ImmunologyAnonymous 2019, .

8. T. B. Casale et al, "Omalizumab pretreatment decreases acute reactions after rush immunotherapy for ragweed-induced seasonal allergic rhinitis," J. Allergy Clin. Immunol., vol. 117, (1), pp. 134-140, 2006.

9. G. Hoffmann et al, "Using machine learning techniques to generate laboratory diagnostic pathways a case study," J Lab Precis Med, vol. 3, (6), 2018.

10. A. L. Beam and I. S. Kohane, "Big data and machine learning in health care," Jama, vol. 319, (13), pp. 1317-1318, 2018.

11. D. Goodman-Meza et al, "A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity," Plos One, vol. 15, (9), pp. e0239474, 2020.

12. S. J. Kim, K. J. Cho and S. Oh, "Development of machine learning models for diagnosis of glaucoma," PloS One, vol. 12, (5), pp. e0177726, 2017.

13. R. Kavya et al, "Machine learning and XAI approaches for allergy diagnosis," Biomedical Signal Processing and Control, vol. 69, pp. 102681, 2021.

14. M. Sebastiani et al, "Personalized medicine and machine learning: A roadmap for the future," Journal of Clinical Medicine, vol. 11, (14), pp. 4110, 2022.

15. G. Hurault et al, "Personalized prediction of daily eczema severity scores using a mechanistic machine learning model," Clinical & Experimental Allergy, vol. 50, (11), pp. 1258-1266, 2020.

16. Immune Tolerance Network. (September 16,). ITN TrialShare: /home. Available: https://www.itntrialshare.org/project/home/begin.view?_hideWelcome.

17. NIH-Supported Data Sharing Resources. (April 20,). Open Domain-Specific Data Sharing Repositories. Available: https://www.nlm.nih.gov/NIHbmic/domain_specific_repositories.html.

Effects of Printing Parameters on Tensile Properties of FDM 3D printed Silk-PLA

Razaul Islam and Jaejong Park, Ph.D.*

Department

of Mechanical Engineering, College of Engineering

Introduction:

The rapid advancement of technology in the 21st century has significantly revolutionized various sectors, particularly in the realm of manufacturing. One groundbreaking technology that has brought about a paradigm shift in manufacturing processes is Additi ve Manufacturing (AM), commonly known as 3D printing. Unlike traditional manufacturing, additive manufacturing produces parts layer by layer, minimizing material waste and allowing for the creation of intricate shapes. Consequently, 3D printing conserves a significant amount of raw materials throughout the process and has become widely used in industries such as biomedicine, aerospace, automotive engineering, civil engineering, and the food industry. Fused deposition modeling (FDM) is one of the most accessible rapid prototyping technologies in additive manufacturing. This project prioritizes Polylactic Acid (PLA) for its cost-effectiveness and environmental friendliness, in contrast to Polycarbonate (PC), Acrylonitrile Butadiene Styrene (ABS), and others. This research establishes a clear correlation between different process parameters and the mechanical strength of PLA materials. The image-based strain analysis method known as Digital Image Correlation (DIC) was analyzed for full-field displacement and strain measurements. Moreover, DIC enhances defect inspection and analysis by providing detailed quantitative data on displacement and strain, helping detect geometric deformations, cracks, wear, and changes in material properties. This capability ensures thorough assessment and effective maintenance strategies for industrial components. Understanding these aspects will lead to enhanced product quality, reduced costs, improved mechanical performance, and ultimately establish the foundation for repair engineeri ng technology capable of corrective maintenance for both geometric and material-level defects.

Objective/Goals:

The objective of this project is to optimize the fused deposition modeling (FDM) process parameters for Polylactic Acid (PLA) materials to enhance mechanical performance, reduce costs, and improve the quality of 3D printed parts. By doing so, this research aims to establish a clear correlation between process parameters and the mechanical strength of PLA materials. It also aims

to utilize the Digital Image Correlation (DIC) method for full-field displacement and strain measurements, providing insights that will further promote the widespread adoption of FDM technology.

Materials and Method:

The project explored two key areas: (1) an experimental investigation of 3D printed materials, and (2) a study utilizing Digital Image Correlation (DIC). Experimental testing was conducted using a universal testing machine following ASTM D638 standard Three different printing parameters (e.g., layer thickness, printing speed, nozzle temperature) were varied resulting in 27 printing parameter combinations, totaling 135 specimens. Ultimate tensile strength and Young ’s modulus of each printing parameter combination was computed using CSV data from testing frame an d DIC. The tensile properties were then analyzed to determine the statistical significance of the process optimization in FDM printing for PLA materials.

Figure 1: Research overview of the DIC with experimental testing.

Results and Discussion:

During the fall 2023 and spring 2023 semesters, preliminary studies examined the impact of various 3D printing parameters on the mechanical characteristics of PLA material. Parameters such as layer height, nozzle temperature, and printing speed were considered, and the mechanical characteristics were recorded. For better understanding, an Analysis of Variance (ANOVA) was performed to evaluate the most significant process parameters of the 3D-printed silk PLA specimens. Digital Image Correlation (DIC) was performed on the sample specimens to measure full-field displacement and strain during tensile testing, and to analyze the initiation of necking, a

Figure 2: DIC stain analysis results in different directions. task nearly impossible with traditional methods. This project highlights that nozzle temperature significantly impacts the mechanical characteristics of 3D-printed parts and various printing parameters influence where necking begins.

Impact/Benefit:

This research was presented at the International Mechanical Engineering Congress & Exposition (IMECE) conference in New Orleans in 2023. Additionally, a technical paper has been submitted for review for the ASME (IMECE) conference in Oregon, scheduled for November 17 -21, 2024. It was also presented at Prairie View during the Research Week in spring 2023. Furthermore, a journal article will be submitted for peer review in summer 2024. The outcomes of this project will facilitate process optimization in additive manufacturing, ensuring control over desi gn and fabrication processes. This approach aims to improve quality, achieve cost savings, ensure consistency and reliability, enhance environmental sustainability, and ultimately establish the foundation for repair engineering technology encompassing metr ology, inspection, characterization, design analysis, and fabrication capable of correcting both geometric and material-level defects.

Reference:

1. Cori Yancy, Saquib Shahriar, Razaul Islam, Rambod Rayegan, Alok Sutradhar, Jaejong Park, “Identifying Correlation between Thermal Gradient and Major FDM Printing Parameters for Enhanced Mechanical Properties” Progress in Additive Manufacturing Journal, under review.

2. Razaul Islam, Saquib Shahriar, Xiaobo Peng, Jaejong Park, "Effect of Process Parameters on Mechanical Properties of the 3d Printed Silk-Pla Specimens Fabricated via Fused Deposition Modeling" ASME (IMECE) 2024, under review.

3. Saquib Shahriar, Razaul Islam, Jaejong Park, "Enhancing the Structural Performance of 3d Printed Objects Through G Code Optimization via FEA in the FDM Process" ASME(IMECE) 2024, under review.

4. Razaul Islam, Jaejong Park, "An Experimental Investigation of Printing Speed, Layer Thickness, and Nozzle Temperature on the Mechanical Properties of Silk PLA-Printed Specimens" ASME (IMECE2023), New Orleans, Louisiana, October 29-November 2, 2023 (Conference Presentation)

5. Razaul Islam, Daniel Bujato, Saquib Shahriar, Xiaobo Peng, Jaejong Park "Experimental Investigation of Printing Parameters on the mechanical properties of Silk-PLA Printed Specimens" Conference for Interdisciplinary Student Research (CISR), PVAMU, 2024

6. Saquib Shahriar, Jaejong Park, Cha Bum Lee, "Additive Repair Engineering Framework via Metrology and Optimization-Guided Reverse Design" Conference for Interdisciplinary Student Research (CISR), PVAMU, 2024

Preliminary Study: Additive Manufacturing of Chicken Feather Fiber Filled Polybutylene Succinate (PBS) Biopolymer

Md Shariful Islam and Lai Jiang Ph.D.* Department of Mechanical Engineering, College of Engineering

Introduction:

One of the emerging biopolymers in today’s market is Polybutylene Succinate (PBS) due to its biodegradability and biocompatibility. PBS is an aliphatic polyester with excellent ductility at room temperature, whose elongation at break may exceed 300% [1, 2], which enables PBS to be an appealing polymer for biomedical applications as a shape -memory material [3]. PBS has been used in tissue engineering and controlled drug release, and also many other applications such as automobile, packaging, agriculture, and constructions where recovery and recycling of materials after use is problematic [4]. However, there are some disadvantages associated with PBS such as low mechanical strengths, low melt viscosity, and high cost. To solve this issue, protein -based natural fibers can be used as a filler in the PBS matrix to form biocomposites [5].

As the world’s largest broiler chicken producer, the United States produced about 21 million tons of chicken meat in 2022 [6]. Annually, there are more than 1.36 million tons of waste chicken feathers in the U.S. alone [7]. The annual worldwide consumption of poultry is about 127.06 million tons, of which feathers form about 10% of the chicken weight [8]. These feathers are sometimes processed into low-grade animal feeds, which adds little value to the feathers and may also cause diseases in the animals. All too often, they become a waste disposal or environmental pollution headache, incinerated or stored in landfills [7]. Despite their high availability, low cost, and good mechanical properties (average tensile strength = 203 ± 74 MPa, and tensile modulus = 3.59 ± 1.09 GPa [9]), chicken feather fibers (CFFs) are rarely used as a filler for biopolymers. Therefore, the combination of PBS and CFF as a filler is highly desirable for making biocomposites used in 3D printing by balancing the PBS biopolymer’s strength and ductility.

Objectives:

This research validates the hypothesis that CFF-filled PBS biopolymer filaments can be used in the FDM 3D printing process.

Methods:

Raw chicken was collected from the Poultry Center at Prairie View A&M University (PVAMU). The feathers containing quills and barbs were soaked in water with a cleaner for 24 hours to remove debris. Subsequently, the feathers were dried in an oven at 85°C for 6-7 hours to eliminate moisture, and then grounded for 8 minutes using an IKA A10 Basic lab grinder at up to 25,000 rpm speeds. Two types of contents were identified after grinding: fine powder and fibrous particles. They were sieved through a 30 mesh sieve (0.6 mm hole size) to ensure particle consistency for passage through the 0.6 mm 3D printer extruder nozzle. During this process, most of the fibrous particles were removed from the CFF powder. Furthermore, the sieved CFF powder was dried in a vacuum oven at 80°C for 24 hours. Dried CFF was then mixed thoroughly with PBS polymer granules with 3 different weight ratios (2%, 1%, and 0.5%). A Filabot EX6 extruder was used to extrude different 1.75 mm 3D printing filaments using pure PBS granules and CFF/P BS mixtures. Four types of filaments were made, including pure PBS, 2 wt% CFF/PBS, 1 wt% CFF/PBS, and 0.5 wt% CFF/PBS. These filaments were loaded into a Qidi Tech X-CF Pro 3D printer to print with a 0.6 mm printing nozzle.

In this study, an INSTRON 5582 Universal Testing Machine (UTM) was used for all tensile and flexural tests. The ultimate tensile strengths were recorded with the maximum tensile stresses achieved in the tests, and elastic moduli were later obtained by calculating the average slope of tensile stress-strain curves of the five samples tested. The ultimate flexural strengths were recorded with the maximum tensile stresses achieved in the tests, and flexural moduli were later obtained by calculating the average slope of flexural stress-strain curves of the five samples tested. A JEOL

JSM-6010LA Analytical Scanning Electron Microscope (SEM) was used for SEM imaging of failed pure PBS and CFF/PBS test specimens from tensile tests. A Perkin Elmer Diamond TG/DTA thermogravimetric/differential thermal analyzer was used to perform the TGA analysis of the pure PBS and CFF/PBS biocomposites.

Results:

The mechanical test results are shown in Fig. 1 below. It can be seen from Fig. 1 (a and b) that the addition of ground CFF tends to decrease the tensile strength of the 3D-printed PBS polymer, while the elastic modulus is not significantly affected by the increasing amount of ground CFFs added to the PBS polymer. The flexural strength of 3D-printed PBS polymer (shown in Fig. 1 (c))

decreased when 0.5 wt% ground CFF was added, but was then gradually increased if more ground CFF was added to the polymer. A similar trend was observed for the flexural modulus of 3D printed CFF/PBS polymers (shown in Fig. 1 (d)), where a big decrease when 0.5 wt% ground CFF was added and then gradually increased with more CFF added.

Figure 1: Mechanical properties comparisons of 3D printed pure PBS and CFF/PBS biocomposites: (a) Flexural strength; (b) Flexual modulus.

The SEM images of the cross sections at the failed pure PBS and CFF/PBS tensile test specimens are shown in Fig. 2. It can be seen from (a) that the pure PBS polymer had a consistent texture and no voids were found on the cross-section. This indicates the pure PBS layers bonded well to each other and formed a uniform material. CFFs were found in figures (b-d) and most of the CFFs were well imbedded inside the PBS polymer. No apparent voids were found in all three figures, indicating a good mixture of the CFFs and PBS polymer. The mechanical properties of the 3D printed biocomposite objects were mainly determined by the CFF filler and the CFF-PBS bonding interfaces.

Figure 2: SEM images of (a) pure PBS, and CFF/PBS biocomposites: (b) 0.5% CFF, (c) 1% CFF, and (d) 2% CFF.

The weight loss-temperature curves of the pure PBS and CFF/PBS biocomposites are illustrated in Fig. 3. It can be seen from Fig. 3 that the pure PBS polymer and CFF/PBS biocomposites showed a single degradation step over the temperature range of this study, indicating that their thermal degradation consisted of one step weight loss in accordance with the random chain scission reaction [10]. Generally, the CFF additives did not have a significant impact on the thermal stability of the PBS polymer, but slightly increased it. The major weight losses of all materials tests took place at around 400°C. However, CFFs increased the major initial degradation temperature from around 250°C (pure PBS) to close to 300°C (2% CFF/PBS). The residue contents of pure PBS were close to zero starting at 460°C, while this did not happen until the temperature reached around 530°C after CFFs were added. This is because, after the pyrolysis of chicken feathers, a total weight loss of ~70 % can be observed [11]

2% CFF/PBS

Figure 3: TGA weight loss vs. temperature curves of pure PBS and CFF/PBS biocomposites.

Significance/Impact:

This research will be presented at the 2024 ASC Annual Technical Conference to be held in San Diego, CA, in October and published as a conference paper. The 3D printing attempt using this new sustainable and biocompatible material will be a sustai nable additive manufacturing process using fully biodegradable and biocompatible polymers that are reinforced by protein-based short fibers reclaimed from one of the most abundant agricultural wastes in the U.S. It will revolutionize the additive manufacturing of natural fiber-reinforced biopolymers and also bring a breakthrough to many industries, especially the bioengineering field where shape memory biocompatible materials are highly desirable during the so-called “4D printing” process [3, 12]. Research results could also lead to the reclaiming of one of the most abundant agricultural wastes that are currently being discarded in the U.S.

References:

1. Y. Deng and N. L. Thomas, "Blending poly(butylene succinate) with poly(lactic acid): Ductility and phase inversion effects," European Polymer Journal, vol. 71, pp. 534-546, 2015.

TGA Curves

2. C. Lin, L. Liu, Y. Liu and J. Leng, "The compatibility of polylactic acid and polybutylene succinate blends by molecular and mesoscopic dynamics," International Journal of Smart and Nano Materials, vol. 11, no. 1, pp. 24-37, 2020.

3. C. Lin, L Liu, Y Liu and J Leng, "4D printing of shape memory polybutylene succinate/polylactic acid (PBS/PLA) and its potential applications," Composite Structures, vol. 279, p. 114729, 2022.

4. M. Gigli, M. Fabbri, M. Lotti, R. Gamberini, B. Rimini and A. Munari, "Poly(butylene succinate)-based polyesters for biomedical applications: A review," Biology, Engineering, Materials Science, European Polymer Journal, vol. 75, pp. 431-460, 2016.

5. M. J. Mochane, S. I. Magagula, J. S. Sefadi and T. C. Mokhena, "A Review on Green Composites Based on Natural," Polymers, vol. 13, p. 1200, 2021.

6. M Shahbandeh, "Chicken meat production worldwide in 2022 and 2023, by country (in 1,000 metric tons)," statista, Apr 2023. [Online]. Available: https://www.statista.com/ statistics/237597/leading-10-countries-worldwide-in-poultry-meat-production-in2007/#:~:text=Global%20chicken%20meat%20production%202022%20%26%202023%2C% 20by%20selected%20country&text=In%202022%2C%20about%2021%20million,chicken% 20. [Accessed 16 July 2023].

7. EMBARGOED FOR RELEASE, "Advance toward making biodegradable plastics from waste chicken feathers," ACS, 31 Mar 2011. [Online]. Available: https://www.acs.org/pressroom/ newsreleases/2011/march/advance-toward-making-biodegradable-plastics-from-waste-chickenfeathers.html#:~:text=Annually%20there%20are%20more%20than,in%20the%20United%20 States%20alone.. [Accessed 16 Jul 2023].

8. A. Khan, H. Parikh and M. R. N. Qureshi, "A Review on Chicken Feather Fiber (CFF) and its application in Composites," Journal of Natural fibers, vol. 19, no. 16, pp. 12565-12585, 2022.

9. M Zhan and R. P Wool, "Mechanical properties of chicken feather fibers," Polymer composites, vol. 32, no. 6, pp. 937-944, 2011.

10. Y. Y. Then, N. A. Ibrahim, N. Zainuddin, H. Ariffin, B. W. Chieng and W. M. Z. W. Yunus, "Influence of Fiber Content on Properties of Oil Palm Mesocarp Fiber/Poly(butylene succinate) Biocomposites," BioResources, vol. 10, no. 2, pp. 2949-2968, 2015.

11. S. Sharma, A. Gupta, S. M. Saufi, C. Y. G. Kee, P. K. Podder, M. Subramaniam and J. Thuraisingam, "Review of Different Treatment Methods on Chicken Feather Biomass," IIUM Engineering Journal, vol. 18, no. 2, pp. 47-55, 2017.

12. H. Cheung, M. Ho, K. Lau, F. Cardona and D. Hui, "Natural fibre -reinforced composites for bioengineering and environmental engineering applications," Composites: Part B, vol. 40, pp. 655-663, 2009.

Exploring the Versatility of Electrospun Polyethylene Oxide Nanofibers: Morphological Insights

Paul Okoli, Aicha Cisse and Nabila Shamim Ph.D.*

Department

of Chemical Engineering, College of Engineering

Introduction:

Nanofibers made from Polyethylene Oxide and Graphene Oxide have gained significant attention due to their unique properties and potential applications in various fields. These composite nanofibers offer a synergistic blend of mechanical robustness, electrical conductivity, flexibility, biocompatibility, ample surface area, and customizable properties (Ali et al., 2021). This makes them suitable for various applications, including drug delivery systems, tissue engineering scaffolds, wearable electronics, sensors, and energy storage devices (Ibrahim et al., 2023; Cao et al., 2011). Renewable and biodegradable materials in developing bio-nanocomposites have become increasingly important in recent years. This is due to the growing need for sustainable and eco-friendly materials in various industries. By incorporating renewable and biodegradabl e materials into the fabrication of nanofibers, such as polyethylene oxide and graphene oxide, we can harness their unique properties and contribute to a more sustainable future (Faldu, 2021). Overall, utilizing Polyethylene Oxide and Graphene Oxide composite nanofibers presents a promising opportunity to address key challenges in various sectors, such as medicine, electronics, textiles, and environmental conservation. In conclusion, using Polyethylene Oxide and Graphene Oxide composite nanofibers offers many benefits and potential applications in diverse fields (Pucić & Jurkin, 2012).

Objectives and Goals:

The objectives of fabricating Polyethylene Oxide (PEO) nanofibers and Polyethylene Oxide (PEO) combined with Graphene Oxide (GO) nanofibers, with varying concentrations of GO is to 1. analyze the morphology of the nanofibers using techniques like scanning electron microscopy (SEM) to observe fiber distribution, and surface structure 2. Optimize the electrospinning parameters (e.g., voltage, flow rate, needle-to-collector distance) to produce uniform and consistent nanofibers.

Materials and Methods:

The polyethylene oxide spinning solution was prepared by dissolving 30 wt.% of polyethylene oxide powder (Mv. 100,000 g/mol) in 10 mL of deionized water. The polyethylene oxide and graphene oxide spinning solution were prepared by incorporating 0.1wt.%, 0.5wt.% and 1wt.% of water-based graphene oxide into the 30 wt.% polyethylene oxide solution. The prepared solutions were then transferred into a 30 mL Beckton Dickinson (BD) plastic syringe equipped with a rubber plunger. Fabrication of the polyethylene oxide and polyethylene + graphene oxide nanofibers were carried out at room temperature using a Fluidnatek LE-50 electrospinning machine from Nanoscience with the following parameters. Preset all parameters for horizontal electrospinning as follows:

• HV+ = +21 kV

• HV- = -2 kV

• Flow rate = 1 mL/h

• Syringe diameter = 21.59 mm

• Needle-to-collector distance = 19 cm

• Drum collector speed = 1000 rpm

Fabricated nanofibers were air-dried at room temperature for 48 –72 hours post-electrospinning before being subjected to characterization.

The morphology of the nanofibers was assessed using a JEOL JSM -6010LA scanning electron microscopy (SEM), while Fourier-transform infrared spectroscopy (FTIR) was employed using a Thermo Scientific Nicolet iS5 using Ominic software to analyze their chemical composition, thereby providing insights into their structural properties.

Results and Discussion:

Figure 1: Images of the electrospun a) PEO and b) PEO-GO nanofiber.

The nanofibers fabricated using the FLUIDNATEK LE-50 electrospinning machine are shown

Figure 1. Figure 1a shows the electrospun pure polyethylene oxide (PEO) nanofiber, while Figure 1b shows the electrospun polyethylene oxide-graphene oxide (PEO-GO) nanofiber. The PEO nanofiber appears brighter than the PEO-GO nanofiber due to the presence of graphene oxide in the latter.

FTIR Results

Figure 2: FTIR images showing the peaks associated with a) PEO and b) PEO-GO nanofiber.

Figure 2 displays the FTIR images showing the peaks associated with PEO and PEO-GO nanofiber. Figure 2a shows the FTIR image of the PEO nanofiber while figure 2b shows the FTIR image for PEO-GO nanofiber.

Table 2a shows the wavelengths and chemical bonds associated with PEO. The peaks associated with PEO occurred around 1100-1300 cm-1, which corresponds to the C-O stretching vibration in the polymer backbone. Table 2b shows the peaks associated with GO. The peaks associ ated with

GO are the stretching vibration of the carbonyl (C=O) group, which was observed around 17201740 cm-1

Table 2: Wavelengths and chemical bonds associated with a) PEO and b) PEO-GO

b) PEO-GO

a) PEO

SEM Results

Figure 3: SEM images of the fabricated nanofibers, a) 13 wt.% PEO (200,000 g/mol) b) 30 wt.%

PEO (100,000 g/mol) in Di - H2O c) 30 wt.% PEO (100,000 g/mol) + GO (1wt.%) d) 30 wt.% PEO (100,000 g/mol) + GO (0.5wt.%) and e) 30 wt.% PEO (100,000 g/mol) + GO (0.1wt.%) in Di-H2O

Figure 3 shows the SEM images of the fabricated nanofibers. The nanofibers fabricated using higher molecular weight PEO (Mv. 200,000 g/mol) are more aligned compared to those fabricated using lower molecular weight PEO (Mv. 100,000 g/mol). The dark background in the SEM images is the carbon black substrate; it was challenging to remove the fabricated fibers from the substrate due to their thin diameter. The beadlike structures observed in the SEM images are droplets of the spinning solution on the carbon black substrate, resulting from an unstable flow rate of the solution. Comprehensive understanding of the shape and structure of these nanofibers is crucial for potential advancements in mechanical properties. Insights gained from this research can inf orm the development of enhanced filtration membranes for diverse applications.

Impact/Benefit:

This research on Polyethylene Oxide (PEO) and Polyethylene Oxide-Graphene Oxide (PEO-GO) nanofibers highlights their significant potential across various sectors due to their unique properties. These nanofibers are ideal for drug delivery, tissue regeneration, and wound dressings, thanks to their fine-tunable mechanical robustness and biocompatibility. Environmentally and industrially, PEO-GO nanofibers can be used in advanced filtration systems and renewable energy solutions due to their mechanical strength, conductivity, and large surface area. In technology, their flexibility and conductivity pave the way for novel electronic devices and smart textiles. The research also offers valuable insights into nanofiber fabrication and characterization, providing a foundation for future studies and fostering innovation in the scientific community.

References:

1. Ali, M., Al-Shukri, A A., Maghami, M., & Gomes, C. (2021, Febr uary 1). Nano and biocomposites and their applications: A review. IOP Publishing, 1067(1), 012093-012093. https://doi.org/10.1088/1757-899x/1067/1/012093

2. Pucić, I., & Jurkin, T. (2012). FTIR assessment of poly(ethylene oxide) irradiated in solid state, melt and Aqeuous Solution. Radiation Physics and Chemistry, 81(9), 1426–1429. https://doi.org/10.1016/j.radphyschem.2011.12.005

3. Ibrahim, A. M. M., Abou Elfadl, A., El Sayed, A. M., & Ibrahim, I. M. (2023). Improving the optical, dielectric properties and antimicrobial activity of Chitosan –PEO by go/mwcnts: Nanocomposites for energy storage and food packaging applications. Polymer, 267, 125650. https://doi.org/10.1016/j.polymer.2022.125650

4. Cao, Y.-C., Xu, C., Wu, X., Wang, X., Xing, L., & Scott, K. (2011). A poly (ethylene oxide)/graphene oxide electrolyte membrane for low temperature polymer fuel cells. Journal of Power Sources, 196(20), https://doi.org/10.1016/j.jpowsour.2011.06.074 8377–8382.

5. Faldu, Nehal, "Electrospinning of PEO Nanofibers" (2021). Electronic Theses and Dissertations. 8518. https://scholar.uwindsor.ca/etd/8518

High Performance Computing Architecture Using FPGA for Embedded Intelligence in Industrial Internet of Things

Dominic Okeke and Sarhan Musa Ph.D.*

Department of Electrical & Computer Engineering, College of Engineering

Introduction:

High-Performance Computing is the means of optimizing computing systems for large and complex computation problems. It involves the customization of compute clusters when running applications on an architecture of a highly parallel computing nature. In other words, it is the ability to perform sophisticated calculations and process data at high speed to enhance low latency, and high throughput and ensure the performance of the computing system. Embedded Intelligence is the ability of a device, process, or product to self-reflect on its sensing, process, communicate, and actuate based on information obtained from its system as a subs ystem and the overall system for the enhancement of its performance. Field Programmable Gate Array (FPGA) is a semiconductor integrated circuit made of a matrix of internal configurable blocks connected through an interconnect bus, for user reconfigurability and programmability after manufacturing of the device. Industrial plants range from manufacturing plants through chemicals, construction equipment, oil and gas exploration to power generation. This work seeks to address the architecture of hardware and software Industrial Internet of Things (IIoT) challenges considered when optimizing datadriven industrial plants based on artificial intelligence.

Therefore, the economic benefits of high-performance computing for industrial processes and manufacturing due to embedded intelligence cannot be overemphasized in the contemporary world of quick-to-market products. In this regard, studies have been extensively carried out to enhance the performance of complex computation of industrial data due to machine-to-machine connectivity in business decision-making.

FPGA is used in this research with an ARMS processor as a programmable SoC to investigate the various architectures for the different machine learning workloads with trade-offs. The system is tested and simulated with different machine-to-machine connectivity in the IIoT setting to obtain the optimum results.

Objectives:

• investigate means of improving high computational processing in FPGA architectures.

• To obtain processes for determining cost efficiency and low power consumption for the AI accelerator.

• To examine various techniques of scaling the architecture for different configurations, sizes, and networks.

Methodology:

RTL and SPICE simulators were used to test and simulate different machine learning algorithms and artificial neural networks with datasets to investigate system behaviors in the architecture of the accelerator. Different proposed configurations, networks and sizes were used to further investigate the computing performance of the architecture based on the performance benchmark for other accelerators in such category. Trade-offs were considered to obtain optimized computing for performance, cost-effectiveness, and low power consumption.

Results and Significance:

The results were expected to show how the benchmark performance criteria are considered for the investigation of such a high-performance accelerator specifically, designed to tailor recent challenges in computing large industrial data for business decision-making. Accuracy of operational intelligence, throughput, latency, and enhancing error reduction were considered as the performance features for critical observation. The main goal in the recent experiments was to deliver real-time data for a rapid-responding advisory plant system.

Key References:

1. Z. Qi, W. Chen, R. Naqvi and K. Siddique, “Designing Deep Learning Hardware Accelerator and Efficiency Evaluation.” Computational Intelligence and Neuroscience. Pp.1-11. 2022.

2. H. Shi, “FPGA Hardware Acceleration Design for Deep Learning.” Highlights in Science, Engineering and Technology. Vol.39, pp.299-304. 2023.

3. Guo, Bin & Zhang, Daqing & Yu, Zhiwen & Liang, Yunji & Wang, Zhu & Zhou, Xingshe, “From the internet of things to embedded intelligence.” World Wide Web. Vol.16, no.4, 2016.

4. Dundar, J. Jin, M. Berin, C. Eugenio, “Embedded Streaming Deep Neural Networks Accelerator with Applications”. IEEE Transactions on Neural Networks and Learning Systems. Vol. 28. pp.1-April 2016.

5. H. Park and S. Kim, “Hardware accelerator systems for artificial intelligence and machine learning”. Advances in Computers. December 2020.

6. W.F. Diniz, V. Frémont, I. Fantoni, E.G. Nóbrega, “An FPGA-based architecture for embedded systems performance acceleration applied to Optimum-Path Forest classifier.” Microprocess. Microsyst. Vol. 52,pp.261–271, 20. 2017.

7. Y.H. Yoon, D. H. Hwang, J. H. Yang, S.E. Lee, “Intellino: Processor for Embedded Artificial Intelligence.” Electronics. Vol. 9, pp.1169, 2020.

8. R. J. Struharik, B. J. Vukobratovi´c, A. M. Erdeljan, D. M. Rakanovic, D.M. CoNNa–“Hardware Accelerator for Compressed Convolutional Neural Networks.” Microprocess. Microsyst. pp73, 2020.

9. Y. Ma, N. Suda, Y. Cao, S. Vrudhula, J. S. Seo, “FPGA Acceleration of Deep Learning Algorithms with a Modularized RTL Compiler.” Integration. vol. 62, pp14–23, 2018.

10. J. Faraone, M. Kumm, M. Hardieck, P. Zipf, X. Liu, D. Boland, P. H. Leong, “Deep Neural Networks Using FPGA Optimized Multipliers.” IEEE Trans. Very Large Scale Integr. Syst. Vol. 28, pp115-128, 2019.

11. F. Sironi, M. Triverio, H. Hoffmann, M. Maggio and M. D. Santambrogio, "Self-Aware Adaptation in FPGA-based Systems," 2010 International Conference on Field Programmable Logic and Applications, pp. 187-192, 2010.

12. M. D. Santambrogio, H. Hoffmann, J. Eastep and A. Agarwal, "Enabling technologies for self-aware adaptive systems", Adaptive Hardware and System, 2010.