FYR 2023 Graduate RISE Impact Report- Research & Innovation- Prairie View A&M University

Research & Innovation for Scholarly Excellence Grant Program

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

The Division of Research & Innovation (R&I) is committed to fostering and growing the research and innovation enterprise of Prairie View A&M University (PVAMU). The Faculty RISE-Graduate Research grant program supports faculty-mentored graduate students’ research and innovation activities. The program enables faculty researchers to sustain and expand their research projects while mentoring graduate students to become the next generation of experts.

The RISE-graduate students are able to devote more time and effort to their research because of the assistantships they receive. Many of these students participated in the TAMUS Pathways Student Research Symposium—a Systemwide event where the students from the 11 memberinstitutions present posters and talks on their research projects. Three RISE graduate students won awards for excellence in research.

R&I is pleased to present the research reports of the Faculty-RISE graduate students in this compendium. The research reports compiled in this booklet come from the seven colleges and one school in the university.

R&I is proud to support graduate research through the Faculty-RISE Graduate Research Grant program as it serves as a vehicle to produce future scholars, educators, engineers, scientists, nurses, and architects. The program also celebrates and promotes the spirit of interdisciplinary collaborations across the university.

Arts and Sciences

Green Synthesis of Silver Nanoparticles Using a Traditionally Medicinal Plant

Naiyah McDaniel and Harshica Fernando*

Department of Chemistry and Physics, College of Arts and Sciences

Introduction:

Traditional medicine consists of health practices, approaches, knowledge, and beliefs incorporating plant-based medicines to treat or prevent illnesses [1]. Research has found the increased acceptance of traditional medicine as a reliable source of treatment because of its ease in accessibility and affordability [2]. 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 [2-4]. 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 compounds 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.

Objectives/goals:

Our project aims to complete the characterization of E. Variegata’s bark and compare compound similarity to prior research characterizing the plant’s flowers, leaves, and roots to determine if the bark is also suitable for medicinal purposes. Additionally, we are examining an environmental component by testing the synthesis of silver nanoparticles using the plant’s extract.

Materials and Methods:

E. Variegata bark is finely ground into a powder using a food processor to obtain the plant’s extract. 100 mL of distilled water is added to the powder and boiled at 265 degrees Celsius for 25 minutes. For the silver nanoparticle synthesis, 7 mL of plant extract was added to 63 mL of 1 mM silver nitrate solution and placed in the microwave synthesizer for 15 minutes at 90 degrees Celsius.

Results and Discussion:

The formation of the nanoparticles was observed by the color change occurred in the solution. Further characterization was performed using ultraviolet-viisble (UV-Vis) and Fourier transfor infrared spectroscopy (FTIR). The figures below show the UV-Vis, FTIR and scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) profiles of the nanoparticles.

UV-Visible and FTIR spectrum of nanoparticles

SEM and EDS results of the nanoparticles:

The UV-Vis results show the surface plasmon resonance peak of the NPs and FTIR data indicates the groups involved in the nanoparticle formation. The morphology of the nanoparticles were obtained using SEM and the presence of Ag confirmed from the data obtained using EDS.

Impact/Significance:

These results prove that an environmentally friendly method for metal nanoparticle synthesis using E. Variegata’s extract is possible and, coupled with the plant’s medicinal properties, provides a potentially low-cost alternative for treating various ailments. In future work, we will further explore medicinal and environmental applications of E.Variegata’s extract.

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. doi:10.4314/ajtcam.v8i3.65276

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. Buyel J. Plants as sources of natural and recombinant anti-cancer 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:10.1155/2022/9089360

5. Oyenihi 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

Developing Advanced Soil Conditioner Nanocomposites for Improved Water Retention

Adewumi A. Adeloye and Yunxiang Gao* Department of Chemistry and Physics, College of Arts and Sciences

Introduction:

The summer of 2022 and 2023 keep breaking the temperature records as the hottest summer in recorded history. To respond to the growing challenges of global warming, mostly caused by the release of greenhouse gases such as carbon dioxide (CO2), previous investigators studied CO2 capture materials intensively,1 among which, amides became well-known for their ability to exhibit high CO2 capture capacity.2 Many porous materials including carbon,3 polymers,4 and hydrogels,5 have been functionalized with amide or amine species for CO2 capture. Such amidefunctionalized porous composites (Am-PC) takes advantage of large surface area/pore volume and the high CO2 affinity to provide high CO2 capture capacity selectivity.6 However, most previous efforts on Am-PCs development were not for in-soil applications, probably due to the high cost of the porous support materials, the mechanical confinement from the soil, and the faster degradation of polymers in soil.7 However, opportunities still exist if these shortcomings can be solved via innovated material design.

Objectives/goals:

The main objective of this project is to embed crosslinked carbon nanotubes (XCNTs) as light, robust nano-skeletons into low-cost Am-PCs to support maximized in-soil hydrogel swelling, long-term stability, and potentially prolong CO2 capture.

Materials and Methods:

Nano-composite Synthesis: Polyacrylamide (PAAm) microgels providing amide groups can be easily synthesized at a relatively low cost.8-9 Acrylamide monomers are mixed with a crosslinker N, N’-methylene bis(acrylamide) in different volumes of ethanol. By adding catalyst potassium persulfate, hydrogel formation occurs after a few hours of incubation at 60 °C. Specific Details are listed below:

The fraction of the monomer (AAm) utilized was 1.44 g. 1/80 of the crosslinker which corresponds to 0.039g was adopted for this synthesis while 1/100 of the initiator AIBN corresponding to 0.031g was adopted for the synthesis. Each of these elements were carefully introduced into separate 7.2 ml glass containers of ethanol and methanol solutions respectively. The resultant mixture from the combination of the monomer, crosslinker and initiator was thoroughly mixed for about 5 minutes to ensure proper dissolution. Thereafter, the solution was sonicated for about 5 minutes to further ensure a total dissolution. Afterwards, Argon gas was used to purge each of the mixture for 20 minutes. Immediately after the Argon purging, parafilm was used to seal each of the lids to prevent the escape of the bubbled gas. A water bath was prepared in a glass beaker and the temperature was set to 60 °C as shown in Figure 1.

After obtaining the PAAm microgel, the nanocomposites were then synthesized by mixing fluorinated carbon nanotubes (FCNTs) with PAM microgels in water with varied FCNT/PAM mass ratio. The mixture solution is then sonicated using a 300W ultrasonic nanoparticle dispenser probe. The FCNTs in the composites will then be crosslinked via a method reported by the PI previously to form XCNT network.10 Fourier transform infrared spectroscopy is used to characterize functional groups of reactants and hydrogels. Water-retention studies are carried out via tracking the mass change of nanocomposites absorbed with water over 10 days.

Results and Discussion:

As a result of PAAm synthesis, opaque white power-like solid were observed to have formed at varied concentration of ethanol in each the containers. This is revealed in Figure 2.

The hydrogels synthesized in 7.2 ml, 9.6 ml, 14.5 ml, and 28.5 ml ethanol were then transferred into test tubes and mixed with 10 ml of distilled water for washing purposes. Microgels need time to swell, and because of the short soaking time, and thus, insufficient time for microgel swelling, they can be enriched via centrifuge after mixing with water. The larger the microgel size, the easier the centrifugal separation of them from water. Indeed, figure 3 shows that, after centrifuged at 4000 rpm, milky microgels were noticed at the tip of each tube. The smaller the volume of ethanol used in synthesis (or the higher the monomer solution), the opaquer the

Figure 1. PAM microgel synthesis in 7.2 ml ethanol at 60 °C

Figure 2. PAAm microgels made at various concentration levels.

enriched milky microgels. This indicates that the higher the monomer concentration in microgel synthesis, the larger the size of the microgel, since larger microgels need longer time to be fully swelled and dissolved, and subjects to easier separation and enrichment after same soaking time.

We also studied the effect of inert gas purging for microgel synthesis. We observed that after centrifuging the redispersed microgels synthesized with and without Argon gas purging, bigger sized microgels would be formed in the argon gas purged synthesis. To comparison, argon purging impacts were studied for the microgel synthesis in 9.6 ml and 14.5 ml ethanol solution, respectively. In figure 4, the Argon-purged synthesis showed more slow-swelling larger microgel formed.

The preparation of FCNT/PAAm microgel composites were carried out via sonicating FCNTs in water solution of swelled microgels. Our results show that sonicating FCNTs alone in water does not help to disperse FCNTs in water, instead, they will float on the air/water interface (Figure 5, left), this is because FCNTs are naturally light and insoluble in water (Figure 5, right). However, if we sonicate FCNTs with PAAm microgels, they form uniform dark suspensions in water. It is the PAAm microgels that brought the FCNTs into the aqueous environment, indicating the possible formation of FCNT/PAAm microgel self-assembly.

Figure 3. Images depicting increased opacity with increased monomer concentration level in microgel preparation.

Figure 4. Comparison of the solution textures at 7.2 ml and 9.6 ml with (left pair) and without (right pair) Argon purging.

The formed FCNT/PAAm self-assembly was then treated with our previously published method to crosslink the FCNTs via reductive defluorination.10 We named the composites with the crosslinked CNTs the XCNT/Gel composite and the un-crosslinked one FCNT/Gel. Our water retention via monitoring the sample weight change due to the loss of moisture over time showed that XCNT/Gel lose less water in comparison to the un-crosslinked XCNT/Gel sample (Figure 6).

Impact/Significance:

Through the above efforts supported by the RISE Graduate Research Assistantship, we now can synthesize micro-hydrogels with controlled size. We found that fluorinated carbon nanotubes can form self-assembled composites with our synthesized microgels, this observation is the first time of its type in the field. Initial water retention study shows that crosslinked CNT skeleton helps improves the water retention efficiency compared to the non-crosslinked ones. These findings pave the way to our next plan for our USDA and Shell projects. The FCNT/Gel self-assembly findings also provide us with a novel foundation for our next NSF proposal as preliminary data.

Figure 5. Formation of FCNT/PAAm Microgel Self-assembly.

Figure 6. Water retention measurement shows that the crosslinked carbon nanotubes (XCNTs) retarded the water loss.

References:

1. Yu, C.-H., Huang, C.-H. & Tan, C.-S. A Review of CO2 Capture by Absorption and Adsorption. Aerosol and Air Quality Research 12, 745-769, doi:10.4209/aaqr.2012.05.0132 (2012).

2. Zulfiqar, S., Sarwar, M. I. & Yavuz, C. T. Melamine based porous organic amide polymers for CO2 capture. RSC Advances 4, 52263-52269, doi:10.1039/c4ra11442f (2014).

3. Kamran, U. & Park, S. J. Chemically modified carbonaceous adsorbents for enhanced CO2 capture: A review. J Clean Prod 290 (2021).

4. Sattari, A., Ramazani, A., Aghahosseini, H. & Aroua, M. K. The application of polymer containing materials in CO2 capturing via absorption and adsorption methods. Journal of CO2 Utilization 48, 101526, doi:https://doi.org/10.1016/j.jcou.2021.101526 (2021).

5. Xu, X. G., Heath, C., Pejcic, B. & Wood, C. D. CO2 capture by amine infused hydrogels (AIHs). J Mater Chem A 6, 48294838 (2018).

6. Suresh, V. M., Bonakala, S., Atreya, H. S., Balasubramanian, S. & Maji, T. K. Amide Functionalized Microporous Organic Polymer (Am-MOP) for Selective CO2 Sorption and Catalysis. ACS Applied Materials & Interfaces 6, 4630-4637, doi:10.1021/am500057z (2014).

7. Xiong, B. et al. Polyacrylamide degradation and its implications in environmental systems. NPJ Clean Water 1, 17, doi:10.1038/s41545-018-0016-8 (2018).

8. Nie, L., Jin, J., Chen, J. & Mi, J. Preparation and performance of amine-based polyacrylamide composite beads for CO2 capture. Energy 161, 60-69, doi:https://doi.org/10.1016/j.energy.2018.07.116 (2018).

9. Zhao, Y., Shen, Y., Bai, L. & Ni, S. Carbon dioxide adsorption on polyacrylamideimpregnated silica gel and breakthrough modeling. Applied Surface Science 261, 708716, doi:https://doi.org/10.1016/j.apsusc.2012.08.085 (2012).

10. Gao, Y. et al. Direct Intertube Cross-Linking of Carbon Nanotubes at Room Temperature. Nano Letters 16, 6541-6547, doi:10.1021/acs.nanolett.6b03184 (2016).

Synthesis and Characterization of Histidine-Metal Complexes

Coddy Cash and Gina Chiarella*

Department of Chemistry and Physics, College of Arts and Sciences

Introduction:

L-histidine is an amino acid that plays a unique role in different biological systems like signal transduction, which is crucial to the structural part of enzymes. This research aims to determine the outcomes of the reaction of L-histidine amino acid with transition metal complexes in different solvents. The procedure utilizes copper (II), nickel (II), manganese (II), and zinc (II) metallic salts. L-histidine, L-histidine methyl ester, and L-histidine hydrochloride are ligands used in this research. The reactions take place in an aqueous and methanol solution. The procedure consists in dissolving the amino acid and adding the metal salt. The preparation may proceed by refluxing (the traditional way) or by microwave-assisted synthesis. The procedure using solvent methanol is challenging due to the low solubility of the amino acid; the advantage is the easy formation of single crystals for structural characterization. The preparation in water solvent is simple due to the higher solubility of L-histidine, but the purity of the product is lower; in this case, the crystallization process requires increasing the pH of the solution. The traditional preparation method usually takes place in one week. By using a microwave synthesizer the procedure occurs in around 20 minutes. It leads to the formation metal complex, which is purified by crystallization. The resulting metal complexes were analyzed and characterized by FTIR, UV-visible, x-ray single-crystal diffraction, scanning electron microscopy, and Zetasizer. The redox and optical properties are analyzed by cyclic voltammetry and fluorimetry. Currently, we have attained the complete characterization of the L-histidine-nickel (II) complex, and we are on the way to concluding the study of the remaining metal complexes.

Materials and Methods:

Synthesis Procedure of Cu (II) and Histidine.

• In a 100 mL round bottom flask 0.0027 moles (0.42g) of L- Histidine, were dissolved in 20ml of water are stirring at neutral pH

• Added 0.00135 moles (0.27g) of Copper Acetate monohydrate into the flask.

• The reaction mixture changes into a royal blue color. Keep stirring for 10 minutes

• Remove the 20ml of water out of the complex by evaporation in a vapor bath for approximately 30 minutes to an hour.

• To the dried mixture, 10ml of ethanol and 2ml acetylacetone was added and let’s settle.

• After one-day blue/purple crystals were formed.

Synthesis Procedure of Ni (II) and Histidine

• In a 100ml round bottom flask, 0.0027 moles (0.42g) of L- Histidine, were dissolved in 20ml of water are stirring at pH initial was around 5

• Added 0.00135 moles (0.34g) of Nickel Acetate tetrahydrate into the flask.

• The reaction mixture changes into a blue color. Keep stirring for 10 minutes, then added approx. 1ml of Potassium Hydroxide (KOH) or until the pH change to neutral

Results and Discussion:

• After preparing the metal complex I was able to obtain the crystals for both Ni (II) at pH 7 and Cu (II)

• After running the experiment in different ways, I found in the case of Nickle by adjusting the pH 7 and 12 I was able to obtain the crystals at each pH.

• In the case of Cu (II), no adjusting of the pH was needed to obtain crystals.

• Below shows the FTIR for Ni (II) and Cu (II) and it’s color-coded to represent the different steps in the synthesis.

• The numbers shown are a representation of the different functional groups present in each case and show the change and movement in each spectrum.

• Cyclic voltammetry and fluorescent experiments have performed on the nickel complex showing that the compound is highly luminescent and shows redox reversibility at Ph 12

The nickel-L-histidine complex crystal structure shows the formation of an extended network. The spectrophotometric characterization shows the nitrogen-nickel and oxygen-nickel bonding interactions by the flat signals on the NH2 groups and the shift of the CO peak in the IR. Those results confirm the findings in the crystal structure. The luminescence properties indicate the presence of relaxation transitions (from MO of high energy to low energy). The redox reversible results at high pH indicate that the possible redox activation requires deprotonation of amino and carboxylic groups. Studies on Copper-L-histidine complex have just started a few weeks ago. The production of single crystals for this compound is a challenge that has almost been attained. About Mn (II) and Zn (II), experiments are ongoing and in the process of being synthesized. The metal Nickle (ll) and Copper (II) Histidine complexes has been synthesized.

Impact/Significance:

The study of histidine complexes it is important to understand the behavior of the amino acid in biological systems as well as to explore the possibility of use this compound to prepare green catalysts and luminescent materials.

References:

1. G.C. Boles; R.A. Coates; G. Berden; J. Oomens, P.B. Armentrout. J.Phys.Chem. B, 2016, 12486−12500

2. Lei Zhou, Shenhui Li, Yongchao Su, Xianfeng Yi, Anmin Zheng, and Feng Deng. J. Phys. Chem. B, 2013, 117, 8954−8965

3. Vladimír Hejtmánek, Martin Dracínský and Jan Sýkora. Crystals 2019, 9, 159.

Agriculture and Human Science

Impact of Spatial Social Networks and Environmental Exposure on Minority Youths’ Mental Health

Bargavi Krishnan and Iyanda Ayodeji*

Department of Agriculture and Nutrition, College of Agriculture and Human Sciences

Introduction:

The increasing trend of mental health (MH) in the US requires urgent attention, especially among youths who face a growing gap in MH care (Merikangas et al., 2011; Liu et al., 2019;). This project aims to understand the prevalence of MH among minority youths from spatial and social perspectives. MH is crucial for psychological processes, healthy relationships, and overall fulfillment. Promoting, protecting, and restoring MH is essential for groups, communities, and societies. Targeted programs for vulnerable individuals, including minority youths, are effective strategies to enhance MH responses (Colizzi et al., 2020). Research on social determinants of health indicates that factors such as living in disrupted neighborhoods, rural areas, belonging to minority groups, youth, history of psychiatric disorder, limited support systems, poverty, low socioeconomic status (SES), and dysfunctional social and familial networks increase MH risks (Alegría et al., 2022; World Health Organization, 2014). Conversely, social connections, networks, and support are crucial protective factors for MH. (Kawachi & Berkman, 2001; Balaji et al., 2007; Kim et al., 2012).

Spatial social networks (SSN) are vital in MH research because they can serve as risk and protective factors at the community level. Sociologists emphasize kinship and shared geographic space as important elements in defining SSN (Piselli, 2007). Geographers defined SSN as “a set of agent-based connections that are embedded in geographic space” and acknowledged that this definition lacks social and personal dimensions.8 People’s social networks/ interactions and location affect the environments where activities occur, and current evidence suggests that they should be jointly examined (Kestens et al., 2017). Although people’s activity spaces might be constrained and spatiotemporally distinct from others, individuals can still be linked through their shared virtual social networks.

Objectives/goals:

The project aims to determine the occurrence of mental health (MH) conditions in minority youths and identify spatial clusters of MH for targeted interventions. It also investigates the combined impact of social support networks (SSN) and environmental exposure on the mental health of minority youths in local communities.

Materials and Methods:

Data collection began on February 1, 2023, using convenience sampling through social media ads, word of mouth, and snowballing. Inclusion criteria required participants to be aged 18-29, possess phone operation or high-school-level reading skills, and reside in the US. Flyers were used to distribute Qualtrics links and QR codes. Virtual prevention protocols in Qualtrics were implemented to identify and prevent non-US residents. By the end of March 2023, the survey had received over 700 responses. After removing duplicates and non-residents using VPN, a total of 424 genuine responses remained with the assistance of a hired graduate student.

Results and Discussion:

Of the 424 participants with genuine responses, 70% were between 18-24 years and 58.7% were students. Non-white was 33.7%, indicating that the majority were identified as white which mimicked the racial landscape of the United States. Over 45% of the participants belong to the LGBTQ+ community. Based on the analysis of the Patient Health Questionnaire (PHQ9), which was used to assess major depressive disorder (MDD) among subjects, 52.6% fell into the moderate-severe MDD, 29.9% had mild MDD, and 18.3% showed no symptoms of major depression. Moderate-Severe MDD was higher among the minority sexual group, while mild MDD was higher among the heterosexual group.

Impact/Significance:

The PI attended the 2023 Association of American Geographers Annual Meeting in Denver, where he presented the preliminary results of the project. Alongside the presentation, the PI collected and chaired two paper sessions based on the major themes of the project: Spatial Social Network and Mental Health. The sessions led to insightful discussions, with several attendees showing interest in the published results and the opportunity to collaborate on similar projects. At the completion of the project, several manuscripts will be submitted to High-Impact Journals such as the Journal of Psychiatric Research. Additional results will be presented in the next Race, Ethnicity, and Place Conference in Washington, DC, in October 2023 and Annual AAG Meeting in Hawai’i in April 2024.

References:

1. Alegría, M., CRUZ‐GONZALEZ, M. A. R. I. O., Alvarez, K., Canino, G., Duarte, C., Bird, H., ... & Shrout, P. E. (2022). How ethnic minority context alters the risk for developing mental health disorders and psychological distress for Latinx young adults. The Milbank Quarterly, 100(2), 424-463.

2. Balaji, A. B., Claussen, A. H., Smith, D. C., Visser, S. N., Morales, M. J., & Perou, R. (2007). Social support networks and maternal mental health and well-being. Journal of women's health, 16(10), 1386-1396.

3. Colizzi, M., Lasalvia, A., & Ruggeri, M. (2020). Prevention and early intervention in youth mental health: is it time for a multidisciplinary and trans-diagnostic model for care?. International journal of mental health systems, 14(1), 1-14.

4. Kawachi, I., & Berkman, L. F. (2001). Social ties and mental health. Journal of Urban health, 78, 458-467.

5. Kestens, Y., Wasfi, R., Naud, A., & Chaix, B. (2017). “Contextualizing context”: reconciling environmental exposures, social networks, and location preferences in health research. Current environmental health reports, 4, 51-60.

6. Kim, I., Chen, J., & Spencer, M. S. (2012). Social determinants of health and mental health among Asian Americans in the United States. Journal of the Society for Social Work and Research, 3(4), 346-361.

7. Liu, C. H., Stevens, C., Wong, S. H., Yasui, M., & Chen, J. A. (2019). The prevalence and predictors of mental health diagnoses and suicide among US college students: Implications for addressing disparities in service use. Depression and anxiety, 36(1), 817.

8. Merikangas, K. R., He, J. P., Burstein, M., Swendsen, J., Avenevoli, S., Case, B., ... & Olfson, M. (2011). Service utilization for lifetime mental disorders in US adolescents: results of the National Comorbidity Survey–Adolescent Supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 50(1), 32-45.

9. Piselli, F. (2007). Communities, places, and social networks. American Behavioral Scientist, 50(7), 867-878.

10. World Health Organization. (2014). Social determinants of mental health.

An integrated approach to quantify carbon sequestration potentials using satellite data and model for different ecosystems.

Oyomire Akenzua and Ram L Ray*

Cooperative Agricultural Research Center, College of Agriculture and Human Sciences

Introduction:

Climate change and variability significantly impact natural resources, environment, and agriculture. Human-driven greenhouse gas (GHG) emissions are causing climate change risks that should not be ignored. Sustaining net zero global anthropogenic CO2 emissions and declining net non-CO2 radiative forcing would halt anthropogenic global warming on multidecadal time scales. Therefore, quantifying carbon emission and carbon sequestration potentials for different ecosystems is critical to developing future climate-resilient management strategies to mitigate socio-economic and environmental damages.

Terrestrial ecosystems are important sources and sinks of GHG, and the changes in terrestrial ecosystems have significant impacts on GHG emissions or uptakes (Li et al., 2020; Fang et al., 2018; Dijkastra et al., 2012). The carbon sequestration capacity of any ecosystem can be enhanced through changes in land use and land cover (e.g., converting marginal cropland to forest or wetland) and changes in land management (such as increased use of prescribed burning to manage wildland fires) (Bergamaschi et al., 2010). Although GHG gases sequestrated by ecosystems significantly impact the global carbon cycle and climate regulation, in-situ measurement is time-consuming and laborious to analyze the spatiotemporal variations of carbon sequestration at a larger scale (Li et al., 2020). Therefore, an integrated approach that combines carbon model, satellite, and in-situ measurements can quantify the carbon sequestration potentials for different ecosystems at a larger scale.

Objectives/goals:

The main goal of this project was to develop an integrated approach to quantify carbon sequestration potentials of four selected ecosystems (cropland, pastureland, hayland, and horticultural land) using publicly available remote sensing data, in-situ measurements and carbon model at 775-acres PVAMU Research Farm under south Texas environment. The specific objectives of this project are as follows:

(i) Quantify daily carbon flux using in situ and satellite data.

(ii) Develop an integrated approach to quantify carbon sequestration.

Materials and Methods:

The graduate research assistant conducted a comprehensive literature review to learn how to download and analyze satellite data to quantify soil organic and atmospheric carbon on the PVAMU research farm. We used Soil Moisture Active Passive (SMAP) Level 4 carbon products (L4C) available at 9 km spatial and daily temporal resolutions. The SMAP, an environmental research satellite, was launched on January 31, 2015, by the National Aerospace Space Administration (NASA) to monitor soil moisture and freeze/thaw state at different spatial and temporal resolutions using radar and radiometric instruments instrument (Jones 2017; Ray et al. 2017; Ray et al. 2019).

Results and Discussion:

It is good to see a continuous increment of SOC on the PVAMU research farm and surroundings from 2015 to the present. Results showed a linear increase in SOC. For example, SOC was 2200 gC/m2 in 2015, which was increased to 2700 gC/m2 (Fig. 1). Regarding atmospheric CO2, it is clear that carbon uptakes and emissions are consistent until 2019. However, carbon uptakes increased, and emissions decreased until 2021. Interestingly, since the COVID-19 pandemic ended, carbon emissions have increased (after 2021), and carbon uptakes have decreased as before the Pandemic (Fig. 1).

Impact/Significance:

Using satellite data, the developed approach to quantify carbon sequestration showed an interesting carbon distribution pattern at PVAMU and surrounding. It helped us to understand its suitability to quantify carbon sequestration potentials using satellite data, which is the most economical approach. Next, further assessment and review of the evaluation results will be conducted to explore the benefits and limitations of the developed approach.

References:

1. Bergamaschi, B.A.; Bernknopf, R.; Clow, D.; Dye, D.; Faulkner, S.; Forney, W.; Gleason, R.; Hawbaker, T.; Liu, J.; Liu, S.-G.; et al. A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios; 2010-5233; Reston, VA, 2010.

Figure 1: Daily Soil Organic Carbon (SOC) and CO2 distributions (2015 – 2022)

2. Dijkstra, F.A.; Prior, S.A.; Runion, G.B.; Torbert, H.A.; Tian, H.; Lu, C.; Venterea, R.T. E_ects of elevated carbon dioxide and increased temperature on methane and nitrous oxide fluxes: Evidence from field experiments. Front. Ecol. Environ. 2012, 10, 520–527.

3. Fang, J.; Zhu, J.; Yue, C.; Wang, S.; Zheng, T. Carbon Emissions from China and the World Some Views on Relationships between Carbon Emissions and Socio-Economic Development; Science Press: Beijing, China, 2018.

4. Jones, L.A., J. S. Kimball, J.S., Reichle, R.H., Madani, N., Glassy, J., Ardizzone, J.V., Colliander,

5. A., Cleverly, J., Desai, A.R., Eamus, D., Euskirchen, E.S., Hutley, L., Macfarlane, C.,

6. Scott, R.L. The SMAP Level 4 Carbon Product for Monitoring Ecosystem Land–Atmosphere CO2 Exchange. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55, 6517-6532

7. Li, M.; Cui, Y.; Fu, Y.; Li, N.; Tang, X.; Liu, X.; Run, Y. Simulating the Potential Sequestration of Three Major Greenhouse Gases in China’s Natural Ecosystems. Forests 2020, 11, doi:10.3390/f11020128.

8. Ray, R.L., Fares, A., He, Y., & Temimi, M. Evaluation and Inter-Comparison of Satellite Soil Moisture Products Using In Situ Observations over Texas, U.S. Water, 2017, 9, 372

9. Ray, R.L., Ibironke, A., Kommalapati, R., & Fares, A. Quantifying the Impacts of LandUse and Climate on Carbon Fluxes Using Satellite Data across Texas, U.S. Remote Sensing, 2019, 11, 1733

Architecture

Hands-On Preservation Experience (HOPE Crew): Utilizing Graphic Design and UX for the Preservation of Historic African-American Burial Sites

Charity Holland and Tracey Moore*

Department of Architecture, School of Architecture

Introduction:

In 2022, Olivewood Cemetery, Houston’s First Incorporated African American cemetery, was designated by the National Trust for Historic Preservation as one of America’s 11 Most Endangered Historic Places. The cemetery is included in the Slave Route Project sponsored by UNESCO. Olivewood is an eight-acre burial ground for nearly 4000 African Americans that date back to pre- and post-emancipation. Digital Media Arts students were invited to work with the Nation Trust’s H.O.P.E. Crew to develop a brand identity and use digital documentation to aid in increasing Awareness of, Descendants of Olivewood.

Objectives/goals:

The aim of this project is to develop a method for data collection in the form of an app and to draft a standard operating procedure (SOP) expanding on qualitative research for future historic preservation projects for the DesignView Media Center.

Materials and Methods:

In this qualitative study graphic design students volunteered to be observed utilizing in-person site visits to think of ideas and refine research. The Creative Thinking Process involves using 5steps to solve design problems, which in this case is creating and designing digital spaces for historic preservation; 1. Define the Problem, 2. Research, 3. Ideation, 4. Prototype, and 5. Implement.

Results and Discussion:

After the project, students who visited the site realized they had a better understanding of what the client wanted compared to those who did not. Also, the brand solutions favored most by the non-profit organizers were designed by students who completed the site visit.

Conclusion:

In conclusion, qualitative research proved that it needed an additional guideline that emphasizes qualitative research to enhance the Creative Thinking Process. Finally, after 1.5 months of observations, I was able to create an app for housing burial records and genealogical information. So anyone can navigate and discover more of Olivewood Cemetery with just a tap.

Business

Deregulation, Innovation, Demurrage, and Shipper Adjustments in the Freight Railroad Industry

Chinagolum Osasah and Elvis Ndembe* Department of Management and Marketing, College of Business

Introduction:

The Class I freight railroad industry has been transformed since it was partially deregulated by the 1976 Railroad Revitalization and Regulatory Reform Act, 4R Act and the 1980 Staggers Act, SRA[1]. Partial deregulation gave railroads flexibility and freedom in the provision and pricing of their services. The increased level of competition and flexibility from deregulation compelled freight railroads to innovate in the areas of marketing, technology, operations, and governance that facilitated their responsiveness to shipper preferences (Winston 1998). Regulation stifled innovation whereas deregulation has led to improvement in railroad operation and service (Gallamore 1999).

In the last couple of decades, reports have pointed to Class I freight railroads adoption of precision scheduled railroading PSR, that has directly altered freight railroad operations[2]. PSR is set of business practices used by Class I freight railroads to increase profitability by optimizing point-to-point train schedules and maximizing utilization of assets including railcars and locomotives (GAO 2002). The PSR strategy uses long trains to reduce operating costs associated with railcars and locomotives while simultaneously reducing transit time (Harrison 2005). To effectively implement both strategies, PSR emphasizes the use of general purpose or manifest trains (Dick 2021). For example, Canadian National Railway CN) the earliest reported PSR adopter witnessed a decline in operating ratio from 89 percent in 1998 to 61 percent in 2006, the lowest of any Class I freight railroad during that period (Barrow 2019). Lower operating ratios reflect a reduction in operating expenses or increased revenue. The timeline for PSR adoption is shown below:

Figure 1: PSR Adoption Timeline Class I Freight Railroads Source: U.S. Government Accountability Office (GAO 2022).

In addition to innovation fostered by the deregulatory environment, Congress transferred authority to determining and collect demurrage from the regulatory body the Inter State Commerce Commission, ICC to freight railroads in a manner a that would enhance the utilization and distribution of freight cars. Demurrage is the charge levied by a railroad to a shipper for holding freight cars for loading and unloading beyond a stipulated amount of time or free time. Enhancing and maintaining an adequate railcar supply is a statutory requirement under 49 U.S. Code § 10746.

In recent years, the Surface Transportation Board, STB the regulatory body that replaced the ICC in 1996 has held a several hearings on shipper complaints about the demurrage. Rail shippers have persistently complained that the operational principles of PSR has led to higher than normal demurrage. In response to shipper complaints and Congressional hearings, the STB published new rules guiding demurrage on April 6 2021 indicating how the reasonableness of demurrage would be adjudicated and minimum billing information requirements.

While precision scheduled railroading (PSR) has altered Class I freight railroad operations and improved operational performance, the effect of PSR on rail services provided to shippers including on demurrage has not been studied. Given the dearth of empirical studies, reported impacts of PSR on shippers have been limited to anecdotes. Even though new rules and monitoring efforts provide some clarity about freight rail service, the effect of PSR on demurrage is still an empirical question. The trend (linear trend) in real total demurrage per car mile or that normalized by output in 2002 dollar for each Class I freight railroad between 2002 and 2017 is shown below:

Objectives/goals:

The principal aim of this study is to examine the potential nexus between PSR and demurrage. Specifically, we assess if Class I freight railroad adoption of PSR has led to escalating freight car loading and unloading delay charges by comparing the nature of demurrage before and after PSR adoption. PSR is not monolithic. It is possible that other Class I freight railroads are actively using PSR strategies including the extensive use of longer trains. We based the timeline for PSR adoption on the Government Accountability Office report (GAO 2022).

Materials and Methods:

Figure 2: Trend Real Total Demurrage per Car Mile, Class I Freight Railroads, 2002-2017

We make use of railroad financial reports (R-1 reports) between 2002 and 2017 published annually by the Surface STB to examine the relationship between PSR adoption and demurrage. We are interested in this period because CN and Canadian Pacific CP were reported to have adopted PSR in 1998 and 2012 respectively (GAO 2022). Four other Class I freight railroads (including CSX Transportation, Union Pacific UP, Kansas City Southern KCS, and Norfolk Southern NS) were reported to have adopted PSR between mid-2017 and early 2019. The shorter period after 2017 prior to 2020, the onset of the Covid-19 pandemic limits our analysis to the 2002 to 2017 period. Moreover, the period prior to 2002 involved significant merger activity. Including periods prior to or during the Covid-19 pandemic and the years before 2002 could capture unrelated effects. Our data represents a panel of the seven Class I freight railroads for the sixteen- year period.

We apply an econometric panel fixed effects model to estimate the demurrage equation. The general specification for the demurrage equation is a standard demand equation, with demurrage per car miles as proxy for demurrage fee or price and total car miles and the private share of car miles representing output measures. Railroad dummies capture fixed effects associated with each railroad’s demurrage policy compared to the base railroad. A PSR dummy variable is included to capture the innovation effect on demurrage. An adjustment factor which is the interaction between the PSR dummy variable an incremental time variable captures potential shippers’ adjustment over time.

Results and Discussion:

In examining the effect of PSR on demurrage in the Class I freight railroad industry, our empirical econometrics estimation model at high statistical significance suggests that PSR has contributed positively to higher-than- normal demurrage charged to shippers. Specifically, Class I freight railroad PSR application was associated with an estimated 71 percent increase in real demurrage per car mile. Considering a railroad’s demurrage policy independently, six Class I freight railroads charged shippers less in freight car related delays per car mile compared to the base railroad at a high level of statistical significance.

The time trend suggests that real demurrage per car mile has been increasing over time. However, the adjustment factor which captures likely savings from freight rail shippers’ adjusting to PSR adoption is not significant at traditional levels of statistical significance. Additionally, a statistically significant difference in real demurrage per car mile was observed between traffic moving in privately-owned and railroad owned freight cars. Class I freight railroads charge 0.43% less in demurrage for delays associated with traffic moving in shipperowned freight cars.

Policy Implication:

We caution against attributing the higher than-normal-demurrage entirely on PSR linked changes. It is therefore important that freight carriers consider tailoring their demurrage policies

to their specific shipper requirements given likely differential effects on rail shippers from the regionalized nature of the Class I freight railroad industry and the heterogenous characteristics of shippers. Moreover, while the STB should continue to examine potential unintended consequences of PSR, it should also remember the harm that can be caused by being overly prescriptive in interfering with railroad innovation. More study is needed to understand why shippers don’t seem to have adjusted to PSR over time. With Class I freight railroads likely to expand their use of PSR, an in depth understanding of the effects of PSR on freight railroad operations as well as benefits to shippers is warranted in future studies. This is particularly important given recent disruptions generated by the Covid-19 pandemic.

References:

1. Barrow, K., 2019. Precision scheduled railroading-evolution or revolution? International Railway Journal, September. https://www.railjournal.com/in_depth/precisionscheduledrailroading-evolution-revolution (accessed November 21, 2022).

2. Gallamore, R.E., 1999. Regulation and Innovation: lessons from the American Railroad Industry. In Essays in Transportation Policy and Economics: A handbook in honor of John R. Meyer, Eds Jose, A, Gomez-Ibanez, William B, Tye and Clifford Winston. Brookings Institution Press, Washington, D.C.

3. Dick, C.T., 2021a. Precision scheduled railroading and the need for improved estimates of yard capacity and performance considering traffic complexity. Transportation Research Record 2675 (10), 411-424.

4. Harrison E.H., 2005. CN-how we work and why: running a precision railroad. Canadian National Railway Company, Montreal, PQ, Canada.

5. United States Government Accountability Office., 2022. Freight rail: information on precision- scheduled railroading. Report to Congressional requesters, Washington, D.C. GAO-23-105420. https://www.gao.gov/products/gao-23-105420

6. Winston, C., 1998. US industry adjustment to economic deregulation. Journal of Economic. Perspective 89–110.

Computer Science

An ML-based System for Predicting Conductive Heat Transfer Topologies

Farissa Tafannum and Ahmed Ahmed*

Department of Computer Science, College of Computer Science

Introduction:

In today's fast-paced, technology-driven world, the pursuit of efficiency and optimization has become more critical than ever. At the heart of this movement is topological optimization, a mathematical technique that refines material distribution within a set design space. This approach aims to maximize system performance by considering a range of factors, including various loads, boundary conditions, and constraints.

Topological optimization is particularly relevant when it comes to managing heat sources, a vital aspect across several industries - from electronics to automotive to aerospace. As systems grow increasingly complex and miniaturized, the challenge of effectively managing heat becomes paramount. Poorly managed or unregulated heat sources can lead to system inefficiencies, early failures, and potentially, safety hazards. Consequently, optimizing the design and management of heat sources can greatly improve operational efficiency, longevity, and safety.

The core goal of applying topological optimization to a heat source problem is to perfect the geometry of the design. This optimization aims to ensure efficient heat dissipation, maintain structural integrity, and minimize weight and material use. In essence, the process involves tailoring the material layout within the system to enhance the conduction of heat away from hot spots and its subsequent dissipation, thereby improving overall system performance.

Our study explores the intersection of topological optimization and heat source management, bringing a new lens to this crucial issue. However, we go one step further: our aim is not just to leverage the power of topological optimization, but to incorporate the potential of neural networks into the process. In this research, we aspire to harness the predictive capabilities of neural networks to enhance traditional topological optimization methods.

By combining these advanced techniques, we seek to devise innovative solutions that can better manage heat and optimize system performance. Our hope is that our findings will have significant implications, not just in improving heat management efficiency, but also in informing future research in this exciting and vital field of study.

Objectives/goals:

The principal objective of our study was to effectively utilize machine learning to address the issue of dimensional constraints found in MATLAB-based topology optimization, specifically in

the context of heat source problems. Our focus was centered around the development and finetuning of a robust machine learning model that could successfully predict the structure and accurately locate the heat source.

In light of this, our approach was geared towards exploring the depth and complexity of various machine learning models like Variational Autoencoder, GAN, TOUNN etc with the ultimate aim of identifying the most effective model that could serve our needs.

We were aware of the challenges involved in this endeavor, such as handling high-dimensional data and making accurate predictions. However, we believed that with a well-designed machine learning model and appropriate optimization techniques, we could surmount these challenges and make significant strides towards achieving our objective.

Materials and Methods:

Our approach was a combination of machine learning, image processing, and topology optimization techniques. Initially, we tried using a Variational Autoencoder (VAE) as our primary machine learning model. However, we encountered some difficulties.

We then turned our attention to image processing techniques. We used these to detect the heat source location in the previously generated MATLAB images. This approach proved successful in identifying the heat source location, but it did not fully serve the goal of our project.

To overcome this challenge, we turned to the literature on topology optimization, specifically the technique used in paper ‘TOuNN: Topology Optimization using Neural Networks’. We integrated this into our machine learning approach in an attempt to enhance the model's capability to predict both the structure and the heat source location.

Results and Discussion:

Our exploration and experimentation with machine learning techniques yielded interesting results. As an initial step, we attempted to implement the Variational Autoencoder (VAE) model. While this approach seemed promising at first, we discovered that it was unable to successfully predict the structure and heat source location as the loss function approached zero. This led us to explore other methods of loss function, including the use of sigmoid cross entropy with logits. While this alternative prevented the loss from reaching zero, it unfortunately did not significantly improve the model's predictive capability.

Simultaneously, we sought to leverage image processing techniques to pinpoint the heat source location while changing the dimension of images. This technique proved to be more successful than our earlier attempts. While this method provided the necessary data for heat source location, it was unable to provide insights into the structure of the system, leaving a gap in our objectives. To overcome the shortcomings of the previous models, and to fill the gap left by image processing techniques, we turned our focus to a topology optimization technique known as TOUNN, as outlined in a specific research paper. Our work on implementing TOUNN is

currently ongoing, and we are optimistic that it will provide a more comprehensive solution, capable of identifying both the structure and the heat source location. While the task has proven complex and challenging, we remain committed to navigating this promising avenue.

Our results so far, while not without their setbacks, have shed light on potential pathways to an effective solution. Each failure and breakthrough has added to our understanding of the problem space, bringing us one step closer to our ultimate goal. We anticipate that, with continued research and optimization, we can refine our approach and successfully implement machine learning to solve the heat source problem.

Impact/Significance:

The potential impact of our research is truly transformative, with implications that extend beyond academia and into various sectors that rely on effective heat management and innovative design processes.

Firstly, we foresee advancements in the realm of design tools. By integrating topological optimization principles and machine learning algorithms, we aim to develop systems capable of creating more efficient, resilient, and lightweight designs. This has immense potential across various industries - for example, it could lead to the creation of more energy-efficient computer hardware, more resilient aerospace components, or lighter and stronger structures in automotive design.

Furthermore, our exploration of machine learning in the context of topological optimization could herald a new era of design methodology. By developing models that can predict the most effective designs in different scenarios, we can expedite the design process and respond more swiftly to emerging design challenges.

Our research also holds the promise of significantly enhancing automation in design processes. In particular, our work could pave the way for self-optimizing systems that learn from and adapt to their environment. This could result in highly efficient design solutions in a variety of fields, from optimizing the structural integrity of buildings in architecture to improving the thermal management of electric vehicle batteries, and even enhancing the thermal performance of highperformance computers.

Lastly, our work carries an important sustainability dimension. Improved heat management, brought about by topological optimization, can contribute to global efforts to reduce energy consumption. For instance, more efficient designs of electronic systems or machinery can reduce their operating temperatures and hence the energy required to cool them, thus contributing to overall energy savings.

In essence, our research is poised to make a significant impact across multiple industries, paving the way for improved design efficiency, enhanced application of machine learning, and substantial contributions to sustainability goals. This potential for widespread positive change underscores the far-reaching significance of our work in this exciting interdisciplinary field.

References:

1. Chandrasekhar, A. and Suresh, K., 2021. TOuNN: Topology optimization using neural networks. Structural and Multidisciplinary Optimization, 63, pp.1135-1149.

2. Li, B., Huang, C., Li, X., Zheng, S. and Hong, J., 2019. Non-iterative structural topology optimization using deep learning. Computer-Aided Design, 115, pp.172-180.

3. Lin, Q., Liu, Z. and Hong, J., 2019. Method for directly and instantaneously predicting conductive heat transfer topologies by using supervised deep learning. International Communications in Heat and Mass Transfer, 109, p.104368.

4. Lin, Q., Hong, J., Liu, Z., Li, B. and Wang, J., 2018. Investigation into the topology optimization for conductive heat transfer based on deep learning approach. International Communications in Heat and Mass Transfer, 97, pp.103-109.

5. Sigmund, O., 2001. A 99 line topology optimization code written in Matlab. Structural and multidisciplinary optimization, 21, pp.120-127.

6. Gladstone, R.J., Nabian, M.A., Keshavarzzadeh, V. and Meidani, H., 2021. Robust topology optimization using variational autoencoders. arXiv preprint arXiv:2107.10661.

Ransomware Behavioral Analysis on Infected Machines

George Cardoso and Na Li

Department of Computer Science, College of Computer Science

Introduction:

The rise of malware attacks poses significant threats to computer systems and networks. In this report, we present a machine learning-based approach to detect malware at an early stage, focusing on the Wannacry ransomware. By leveraging Python scripts, Cuckoo sandbox analysis, and preprocessing techniques. We then use machine learning algorithms and evaluate their performance using tenfold crossvalidation.

Materials and Methods:

Our methodology consists of several key steps. Firstly, we create Python scripts that imitate human activity to interact with the malware samples. These scripts are executed using the Cuckoo sandbox, outputting the analysis logs. Half of the scripts contain the Wannacry virus, while the other half serve as benign scenarios.

We apply different preprocessing techniques to filter the analysis logs. We consider four types of preprocessing: normal, pre-encryption, generalized, and removed. Normal filters the file paths of the logs, pre-encryption removes any file paths after encryption starts, and generalized generalizes the file paths, and removed only uses the file name and extension.

To convert the preprocessed text files into numerical representations, we employ the Term FrequencyInverse Document Frequency (TF- IDF) technique. This approach assigns weights to terms or file paths based on their frequency and inverse document frequency, enabling us to capture the importance of each file path in the context of the entire dataset.

Next, we label the infected and benign scenarios based on their corresponding scripts and preprocessed data. We utilize four popular classifiers for our experiments: Extra Trees (ET), Random Forest (RF), Gradient Boosting (GB), and Support Vector Machines (SVM).

Results and Discussion:

To assess the accuracy of our ML algorithms we perform tenfold cross-validation on each combination of classifier and preprocessed data.

The overall accuracy of the classifiers is as follows: Extra Trees (ET), Random Forest (RF), and Gradient Boosting (GB) achieve an average accuracy of 98%. Support Vector Machines (SVM) attain an average accuracy of 95%.

Regarding the preprocessing techniques, the average accuracy is as follows: Pre-Encryption (PE) and Generalized (G) achieve an overall average accuracy of 98%.

Normal (N) and Removed (R) preprocessing techniques achieve an average accuracy of 97%.

These results indicate that our approach shows great performance in detecting Wannacryinfected scenarios accurately, with consistently high accuracy across multiple classifiers and preprocessing techniques.

Conclusion:

In this study, we demonstrated the effectiveness of using machine learning algorithms in the early detection of malware, specifically on the Wannacry ransomware. By leveraging Python scripts, Cuckoo sandbox analysis, and various preprocessing techniques, we successfully identified infected scenarios with high accuracy.

Our findings indicate that the combination of Extra Trees, Random Forest, and Gradient Boosting classifiers performs exceptionally well, achieving an average accuracy of 98%. The Pre-Encryption and Generalized preprocessing techniques yield the highest average accuracy of 98%.

The proposed approach holds promise for enhancing cybersecurity measures by providing early detection of malware, thereby enabling better mitigation and prevention strategies. Future work could involve exploring other preprocessing techniques and or better machine learning algorithms.

References:

1. Q. Chen and R. A. Bridges, "Automated Behavioral Analysis of Malware: A Case Study of Wanna Cry Ransomware," 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), Cancun, Mexico, 2017, pp. 454460, doi: 10.1109/ICMLA.2017.0-119. URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8260673&isnumber=826059 7

2. Chen, Q., Islam, S.R., Haswell, H., Bridges, R.A. (2019). Automated Ransomware

Behavior Analysis: Pattern Extraction and Early Detection. In: Liu, F., Xu, J., Xu, S., Yung, M. (eds) Science of Cyber Security. SciSec 2019. Lecture Notes in Computer Science(), vol 11933. Springer, Cham. https://doi.org/10.1007/978-3030-34637-9_15

3. S. -C. Hsiao and D. -Y. Kao, "The static analysis of WannaCry ransomware," 2018 20th International Conference on Advanced Communication Technology (ICACT), Chuncheon, Korea (South), 2018, pp. 153158, doi: 10.23919/ICACT.2018.8323680.

URL: https://ieeexplore.ieee.org/stamp/stamp.jsp

tp=&arnumber=8323680&isnumber=8323471

Education

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*

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.

Objectives/goals:

This research 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.

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.

Results and Discussion:

Qualitative data from the surveys were analyzed and student voices informed the resulting recommendations. Quantitative data sets from the Certified Teacher exams were used to assess student progress over the semester. Although this one software test does not mean that students are deemed ready to take the actual test and move on to senior level courses, it is a primary assessment benchmark in this and other TPP programs. Student content exams were grouped according the following: music students, Core Education to grade 6 and math students.

The music students revealed surprising outcomes for this semester’s data. From this group 7 of 12 music students who took practice exams by April 2023, only one did not get above a 240 and 3 were above 270; the required score being a 290. Of the 5 math students, 3 have not taken the proctored exam and only 2 have a score above 287. Of the 6 Core E-C-6 students, only 1 passed all subjects with a 240 or better revealing the need for early advising and refocusing students to content exams where they have strengths.

Based on the data what emerged was a need to support students through greater: mentorship, tutoring that includes test preparation materials and weekly contact and check- ins with faculty.

Impact/Significance:

Preliminary data from this research was presented by the graduate student at the RISE symposium April 2023. The feedback was positive and helped to move this forward to a manuscript. The faculty member shared additional data at this year’s departmental Faculty Retreat in July 2023. The Journal of Education and Cultural Studies has been identified for publication of this manuscript and will be submitted by August 2023. This project has IRB approval.

References:

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

2. 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_mediu m=email&utm_name=&utm_source=govdelivery&utm_term=

3. 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-college-

landscape#:~:text=Some%20of%20the%20most%20heartening,of%20all%20African%2 0American%20graduates.

The Study of African American Educators’ Belief About the Importance of

Culturally Relevant Pedagogy

Ijeoma Eze, Whitlowe Green, Katrina Thomas* Department of Curriculum and Instruction, College of Education

Introduction:

The education system plays a critical role in shaping the lives of individuals, and teachers are key players in this process. Culturally relevant pedagogy (CRP) is an instructional approach that emphasizes the importance of incorporating students' cultural backgrounds and experiences into the learning process. This approach has gained significant attention in recent years, particularly in the context of addressing educational disparities among minority students. African American students are among those who have historically experienced marginalization in the education system, and as such, African American educators' beliefs about the importance of CRP are of particular interest. This research aims to explore the perspectives of African American educators on the significance of CRP in improving educational outcomes for African American students. By examining their beliefs, this study hopes to contribute to a better understanding of the potential of CRP as a tool for addressing educational disparities and fostering inclusive learning environments.

Implementing Culturally Relevant Pedagogy in the K-12 school system involves the input of a diverse group of educators that are currently in school systems. The purpose of this research study is to study the perceptions of African American educators as it relates to the preparation and practice of culturally relevant pedagogy.

Objectives/goals:

The objectives of this research study are to answer the following questions.

1) Are African American educators aware of Culturally Relevant Pedagogy?

2) Do African American educators believe that cultural competence is a critical component for teaching?

Materials and Methods:

The online survey research methodology was utilized, which measured the participant's perception of culturally relevant pedagogy and whether developing students' cultural competence is critical to teaching. The population of the study consisted of African American educators who have a minimum of one college degree and are employed as an educator in public, private, or charter school systems across the US. Participants were asked to identify their age, gender, job position, and years of experience as an educator. Data was collected through online social network survey from members of closed social groups created for African American educators. Responses were compared among different categories of educators using averages and descriptive analysis.

Results and Discussion:

African American K-12 educators participated in the study. Participants were described based on their demographic characteristics such as age, gender, position, level of student they teach, and

years of experience as an educator. The research provided that most participants were either school administrators, instructional coaches and home/room coaches who agree that CRP is relevant. Data was also collected on the perspective of participants on culturally relevant pedagogy. On the question of whether developing students' cultural competence is critical to teaching, 25% of the participant agreed that developing students' cultural competence is critical to teaching, 72% participants strongly agreed while 3% were undecided. On the question of whether the participants have heard about culturally relevant pedagogy, 86% participants answered yes, while 14% answered No.

Educators with 11 to 25 years of experience report that they have heard of culturally relevant pedagogy (CRP), however only 66% of classroom teachers strongly agree that developing student’s cultural competence is relevant. It is critical for more awareness of CRP to be created.

Impact/Significance:

The research showed that most of the participants have heard of culturally relevant pedagogy and strongly agree that cultural competence is critical to teaching. The result of the research also showed that most participants were either school administrators, instructional coaches and home/room coaches. Based on the findings it is important to include more professional development that focuses on culturally relevant teaching practices.

References:

1. Ashby Bey, J. (2007). An exploration of identity development and culturally relevant

2. teaching practices among African American elementary pre -service teachers in urban communities (Ph.D.). Available from ProQuest Dissertations & Theses Global. (304757886).

3. Gay, Geneva. Culturally Responsive Teaching: Theory, Research, and Practice. 3rd

4. ed., New York, NY, Teachers College Press, 2018.

5. Ladson-Billings, G. (1995). Toward a Theory of Culturally Relevant Pedagogy.

6. American Educational Research Journal, 32(3), 465–491. https://doi.org/10.2307/1163320

7. Howard, T., & Terry Sr, C. L. (2011). Culturally responsive pedagogy for African

8. American students: Promising programs and practices for enhanced academic performance. Teaching Education, 22(4), 345-362.

9. Irvine, J. J. (2003). Educating teachers for diversity: Seeing with a cultural eye. Teachers College Press.

The Importance of Minority Teacher Preparation:

Tapping the Community College

Pipeline to continue the legacy of HBCU’s Myriah Hampton and Britine Perkins*

Department of Cirriculmn 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 elaborating 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/Significance:

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, 263276.

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.

Cloud Computing and its Growing Interests

Blessing Funmilayo Ibekeh, Daniel Ikechukwu Ezeh and Beverly Sande* Department of Curriculum and Instruction, College of Education

Introduction:

Cloud computing has emerged as a disruptive technology that has revolutionized data management and collaboration in educational institutions. This report explores the growing interest and benefits of cloud adoption within the context of educational settings with a particular focus on Texas higher educational institutions. By leveraging selected references, we examined the advantages of cloud computing in education, including improved collaboration, resource sharing, accessibility, and data security.

The study by Lakshminarayanan et al. (2013) emphasizes the positive impact of cloud computing adoption in educational institutions. Through enhanced collaboration among students and educators, efficient resource sharing, and anytime, anywhere accessibility to educational materials, cloud technologies offer a transformative learning experience.

Data security remains a critical concern in cloud-based educational systems. Jiang et al. (2023) propose the Adaptive Ensemble Random Fuzzy (AERF) algorithm for anomaly detection in cloud computing, which can be adapted to educational settings to strengthen data security and protect against potential cyber threats.

Moreover, Lin et al. (2022) presents an innovative approach by integrating cloud computing and multifeatured extraction extreme learning machine, enabling seamless collaboration and resource sharing among educational stakeholders. Understanding the determinants of cloud computing adoption in educational institutions is essential for informed decision-making. Hassan et al. (2022) investigates the factors influencing the adoption of cloud technologies, shedding light on considerations that educators and administrators should consider. The significance of cloud computing security models in educational environments is highlighted by Khoda Parast et al.

(2022). Implementing best practices and protective measures is crucial to safeguard educational data and maintain user privacy within the cloud.

Lastly, Cotroneo et al. (2023) propose a non-intrusive event analysis technique for run-time failure detection in large-scale cloud computing platforms, specifically applicable to educational institutions. This method promptly identifies potential failures within the cloud infrastructure, ensuring uninterrupted access to educational resources.

Objectives/goals:

The primary objectives of this project are as follows:

• To assess the current level of cloud computing adoption in higher institutions in Texas.

• To identify the motivations and challenges faced by these institutions in adopting cloud computing and to analyze the impact of cloud computing on the academic and administrative processes within these institutions.

• To evaluate the benefits and drawbacks of cloud computing integration.

• To provide recommendations for effective cloud adoption strategies in higher institutions.

Materials and Methods:

Data Collection: The research involved collecting both quantitative and qualitative data. Surveys were distributed to IT administrators, faculty members, and students of various higher institutions in Houston. Additionally, interviews and focus group discussions were conducted to gain in-depth insights into the challenges and benefits experienced firsthand.

Data Analysis: The collected data was analyzed using statistical software to determine the percentage of institutions that have adopted cloud computing and to identify key trends and patterns. Qualitative data from interviews and focus groups were transcribed and thematically analyzed to extract meaningful information.

Results and Discussion:

Current Cloud Computing Adoption: The study found that approximately 75% of higher institutions in Texas have integrated some form of cloud computing into their infrastructure.

Motivations for Adoption: The main motivations for cloud adoption were identified as cost savings, improved collaboration among faculty and students, enhanced data security, and simplified access to educational resources.

Challenges Faced: The challenges encountered during the cloud adoption process included concerns about data privacy, integration with existing systems, and initial training for staff and faculty.

Impact on Academic and Administrative Processes: Cloud computing has significantly streamlined administrative tasks, such as student record management and registration processes.

It has also enabled more flexible and accessible learning opportunities, allowing students to access course materials and collaborate with peers remotely.

Impact/Significance:

Cost Savings: Cloud computing has reduced the need for extensive physical infrastructure, resulting in cost savings for institutions.

Enhanced Collaboration: Cloud-based tools and platforms have facilitated seamless collaboration among faculty and students, fostering a more dynamic learning environment.

Scalability: Cloud infrastructure allows institutions to easily scale their computing resources based on demand, ensuring optimal performance during peak times.

Improved Accessibility: Cloud-based resources can be accessed from any location and on various devices, enabling greater accessibility to educational materials.

Data Security: Cloud providers often offer robust security measures, protecting sensitive institutional and student data from potential threats.

References:

1. Jiang, J., Liu, F., Ng, W.W., Tang, Q., Zhong, G., Tang, X. and Wang, B., 2023. AERF: Adaptive ensemble random fuzzy algorithm for anomaly detection in cloud computing. Computer Communications.

2. Lin, H., Xue, Q., Feng, J. and Bai, D., 2022. Internet of things intrusion detection model and algorithm based on cloud computing and multi-feature extraction extreme learning machine. Digital Communications and Networks.

3. Cotroneo, D., De Simone, L., Liguori, P. and Natella, R., 2023. Run-time failure detection via non- intrusive event analysis in a large-scale cloud computing platform. Journal of Systems and Software, p.111611.

4. Hassan, A., Bhatti, S.H., Shujaat, S. and Hwang, Y., 2022. To adopt or not to adopt? The determinants of cloud computing adoption in the information technology sector. Decision Analytics Journal, 5, p.100138.

5. Lakshminarayanan, Ramkumar & Kumar, Binod & Raju, M.. 2013. Cloud Computing Benefits for Educational Institutions.

6. Khoda Parast,F., Sindhav, C., Nikam, S., Izadi Yekta, H., Kent, K. B., & Hakat, S. (2022). Cloud Computing Security: A survey of service-based models. Computer & Security, 114, 102580.

Engineering

RISE: Innovation of Self-Calibrated Smart Sensors and System Integration for Determining In-Situ Filtered Drinking Water Quality in Real-Time

Nafisa Islam and Shuza Binzaid*

Department of Electrical and Computer Engineering, College of Engineering

Introduction:

This project requires to develop an innovative Sensor technology that would provide solutions to overcome challenges to detect the water filtration process by detecting and read out the water quality to make the system adaptive to sustainable living [1]. A methodology has been approached that the electrical conduction characteristics of a media, water in this case, is proportional to the surface area of this special sensor probes. Even though conductance can easily be measured with this sensor and pH levels, somewhat, can be approximated to some ranges using fitted equations found by researchers [2], [3]. Yet, pH information should be measured accurately for human consumption. So, a type of non-conductive sensor is designed in this work during the summer 2023. Prototypes of various shapes and dimensions of finger-probes in this non-conductive sensor has been fabricated and tested in the media of supply tap water.

Objectives/goals:

In this project, the initial goals were to design two innovative non-conductive high-sensitivity digital sensors and analysis for appropriate functions completed with the coded algorithm with digital display to determine the tap water quality by (1) TDS, and (2) pH level [4],[5]. So, reporting here that three designs of non-conductive finger-probe sensors have been designed and tested and found to have working as expected using a high precision multi-tester. The primary steps of the objectives has been met to develop the non-conductive sensor probes. The project will continue to reach the goals to establish this as a valuable application of sensor technology by (1) finalizing the design and (2) completing the design of a microcontroller-based system.

Materials and Methods:

Copper is harmless to humans, and it is a mineral for helping bones in human body non-porous, thus helping prevent osteoporosis [6]. A copper sensor was designed and fabricated successfully by the PI in finger-probe arrangements and layered by 1.5 micron non-conductive thin-films. Figure 1 shows the 1st prototype of the working sensor that was tested safely in supply tap water.

Copper, being a safe material for human body with some benefits has been used in this project successfully. Repeated tests showed no corrosive effects on the surface of the copper and also showed non-reactive to any impurities. Also, no oxidation was observed due to the nonconductive thin-film layers. The sensor exhibited ionic separation of applied voltage in the tap water which did not have any effects on the sensor. Having these ionic effects, the sensor created a capacitance in the tap water in localized concertation of positive and negative charges. Thus, it could be measured for capacitive values while submersing the sensor in water. Figure 2 shows the plot and equation using preliminary test values read by a multimeter connected to sensor probes.

Impact/Significance:

Figure 1: The first prototype of the working sensor Results and Discussion:

Figure 2: Plot of values read by the precision multimeter when connected to the sensor probes.

This sensor can find some investigative answers about impurities in tap water and quality of water filtration process. This sensor is very inexpensive and easy to fabricate. It is a very lowpower sensor and virtually no-maintenance will be introduced to new marketable products that are absolutely needed for consumer and industrial market spaces, health services, etc., thus many areas can expand for improved standards of future smart living. Educate and train our students and make the community aware of drinking water impurities and the quality of filters that process it. The final version of a more accurately designed sensor with its microcontroller-based coded hardware/software solution can secure IPs at PVAMU and register for patents in future. Larger funds can be brought from other funding agencies such as NSF, USDA, FDA, NIH, etc.

References:

1. S. Cohen, “Understanding the Sustainable Lifestyle”, The European Financial Review, December - January 2018, pages 6 - 9.

2. A. Kumar Pal, and A. P. Singh, “Water Quality Monitoring using TDS, Turbidity, Temperature & pH Sensor”, International Research Journal of Engineering and Technology, Volume: 05, Issue: 03, Mach 2018, pages 1333 - 1335.

3. S. Bargrizan, R. J. Smernik, and L. M. Mosley, “Development of a spectrophotometric method for determining pH of soil extracts and comparison with glass electrode measurements,” Soil Sci. Soc. Amer. J., vol. 81, no. 6, pp. 1350–1358, Nov. 2017.

4. N. K. Douglas and R. H. Byrne, “Spectrophotometric pH measurements from river to sea: Calibration of mCP for 0 ≤ S ≤ 40 and 278.15 ≤ T ≤ 308.15 K,” Mar. Chem., vol. 197, pp. 64–69, Dec. 2017.

5. gor A. Pašti, T. Lazarevi´c-Pašti, and S. V. Mentus, “Switching between voltammetry and potentiometry in order to determine H+ or OH− ion concentration over the entire pH scale by means of tungsten disk electrode,” J. Electroanalytical Chemistry, vol. 665, pp. 83–89, Jan. 2012.

6. Harvinder S. Sandhu, M.D., “Trace Elements, Zinc, and Copper: How They Impact Osteoporosis”, Health Central Overview, Update on January 17, 2018, https://www.healthcentral.com/condition/osteoporosis/osteoporosis-trace-elementszinccopper

Energy-efficient Additive Manufacturing of Sustainable Continuous Natural Fiber

Reinforced Biopolymer Composites

Sazidur Shahriar and Lai Jiang* Department of Mechanical Engineering, College of Engineering

Introduction:

Increasing evidence of the rapidly-evolving climate change due to emissions of greenhouse gases, primarily from carbon dioxide (CO2) and methane from fossil fuels, is alarming. Energy consumption from fossil fuels is the primary source of human-induced greenhouse gas emissions. Although scientific breakthrough has facilitated the utilization of renewable energy, fossil fuel energy still accounts for >78%. Therefore, it is imperative to reduce energy consumption while promoting sustainable energy usage and capturing the CO2 from the emission. Particularly, industrial manufacturing accounts for more than one-third of global energy consumption and has become a major source of CO2 emission. The composites industry has been a large contributor to greenhouse gas emissions and low-carbon manufacturing of sustainable composites is critical to global decarbonization. Traditional fiber-reinforced polymer composites are made from high-strength reinforcements such as carbon or glass fibers combined with thermoplastic or thermoset polymers as the matrix. These materials are not environmentally friendly at the end of their service life due to difficulties in the recyclability and decomposition of individual constituents. Current practical disposal methods for these wastes are either landfilling or burning for energy at a high cost to the environment.

The utilization of bast fibers from plants as reinforcements is one possible option to make composite material use more sustainable. Bast fiber is plant fiber collected from the outer bark or bast surrounding the inner woody stem of certain dicotyledonous plants [1] such as flax, industrial hemp, kenaf, sisal, etc. Such fibers are stronger than other natural fibers [2-5] and have comparable mechanical properties to E-glass. However, typical densities of bast fibers (hemp fiber = 1.5 g/cm³, flax = 1.4 g/cm³, jute = 1.46 g/cm³) are generally lower than that of E-glass (2.55 g/cm³). Hence, properties like specific modulus sometimes achieve a better ratio between elastic modulus and density than E-glass reinforced composites. Natural fiber reinforced polymer composites (NFRPC) are good replacements for glass fiber reinforced polymer composites [6] and can be used in many other applications such as transportation vehicle panels, and thermal and sound insulation materials. Short-cut natural fibers had been used for producing biocomposite automobile panels by the Ford company since 1941 [7] and more automobile manufacturers are implementing natural fibers in their production [8]. Continuous fibers are deemed much stronger compared to short fibers as reinforcements in the composites industry, therefore, more efforts can be made toward low-carbon additive manufacturing using continuous natural fibers as reinforcements in polymer matrix composites. The PI hypothesizes that the local frontal curing technique can be implemented in the 3D printing of thermosetting biopolymers with continuous natural fiber reinforcements to make both the process and the product low-carbon toward global sustainability.

Materials and Methods:

• Chemical treatment of natural fiber tows to improve fiber-matrix interface bonding

o Chemically treat obtained flax and hemp fiber tows using a 5 wt% NaOH solution.

o Locate and obtain proper bioresin that will work with the proposed process.

o Make biocomposites using the treated natural fiber tows and obtained bioresin.

o Measure the fiber-matrix bonding strength using one of the ASTM test standards.

Results and Discussion:

• Flex and hemp fiber tows were obtained from Etsy and then chemically treated.

• BioPoxy 36 biopolymer and its hardener were obtained from EcoPoxy.

• Two different biocomposites (i.e., flax-biopolymer and hemp-biopolymer) were made.

• The fiber-matrix bonding strengths of both biocomposites were measured using peel resistance tests per ASTM D1876 test standard and then compared with samples made using green (untreated) bast fibers as reinforcement. The chemically treated bast fibers seem to work well with the BioPoxy bioresin. Both biocomposites were made successfully and their fiber-matrix bonding strengths were measured. Both fibers have shown improved fiber-matrix bondings compared to biocomposite samples made from untreated (green) bast fibers.

Impact/Significance:

Results and outcomes from this research will be disseminated to the broader technical communities, providing a deep and comprehensive understanding of this novel low-carbon manufacturing technique, which significantly promotes its application in the industrial world.

References:

1. Encyclopaedia Britannica, 1998, "Bast fibre," from https://www.britannica.com/technology/bast-fiber

2. Gurunathan, T., Mohanty, S. and Nayak, S.K., 2015, “A review of the recent developments in biocomposites based on natural fibres and their application perspectives,” Composites Part A: Applied Science and Manufacturing, 77, pp. 1–25.

3. Pickering, K.L., Efendy, M.G.A. and Le, T.M., 2016, “A review of recent developments in natural fibre composites and their mechanical performance,” Composites Part A: Applied Science and Manufacturing, 83, pp. 98–112.

4. Tan, B.K., Ching, Y.C., Poh, S.C., Abdullah, L.C. and Gan, S.N., 2015, “A review of natural fiber reinforced poly (vinyl alcohol) based composites: Application and opportunity,” Polymers, 7(11), pp. 2205–2222.

5. Mochane, M.J., Mokhena, T.C., Mokhothu, T.H., Mtibe, A., Sadiku, E.R., Ray, S.S., Ibrahim, I.D. and Daramola, O.O., 2019, “Recent progress on natural fiber hybrid composites for advanced applications: a review,” eXPRESS Polymer Letters, 13(2), pp. 159-198.

6. Todor, M.P., Bulei, C., Kiss, I., and Cioata, V.G., 2019, “Recycling of textile wastes into textile composites based on natural fibres: the reinforcement type and the architecture,” Conf. Ser.: Mater. Sci. Eng., 477, p. 012055.

7. The Henry Ford, 2022, “Popular research topics: Soybean Car,” from: https://www.thehenryford.org/collections-and-research/digital-resources/populartopics/soy-bean-car/

8. Harikrishnan, C., 2020, “Natural Fiber Reinforced Polymer Composites In Automobile Applications,” from: https://www.linkedin.com/pulse/natural-fiber-reinforced-polymercomposites-automobile-harikrishnan-c/

A Preliminary Numerical Study on Combustion of Oxygenated Fuels

Churton Munroe and Yuhao Xu*

Department of Mechanical Engineering, College of Engineering

Introduction:

The research topic identified in this work is the combustion of biofuels, particularly oxygenated fuels. Its relevance derives from the fact that worldwide energy policies have been focusing on exploring green and renewable solutions to reduce the consumption of petroleum-based fuels and harmful emissions. Blending biofuels with petroleum-based liquid fuels is a well-known strategy for this purpose. However, the majority of published studies have focused on the production of biofuels, and less understood is their fundamental combustion performance. This research is to bridge this gap to identify relevant combustion properties of biofuels.

This work is based on the spherical droplet flame to evaluate the combustion properties of renewable fuels. Figure 1b shows a schematic of this geometry. The combustion properties generated from the spherical droplet flame in Figure 1b include the time evolution of droplet (D), soot shell (Ds), and flame (Df) diameters. The droplet burning rate, K = |d(D/Do)2/d(t/Do2)|, can then be obtained by plotting (D/Do)2 vs. t/Do2 (where t is time, and Do is the initial droplet diameter) following the classical theory of droplet burning [1]. The droplet burning rate indicates how fast a particular fuel burns. This work will use the abovementioned combustion properties to characterize the combustion dynamics of various biofuels.

Objectives/goals:

The objectives of this project include the following.

1. Explore various computational platforms for constructing models to simulate the combustion processes of oxygenated fuels.

2. Simulate the multiphase evaporation and combustion process of liquid fuels.

Materials and Methods:

The numerical work includes identifying a suitable platform for the graduate student to build the simulation framework. The tentative plan is to use ANSYS Fluent to simulate the multiphase evaporate process of n-butanol. User-defined functions (UDFs) will be developed by the graduate student to track the boundary of the evaporating fuel droplet. In this process, the student

Figure 1: Schematic of (a) a spray flame and (b) a spherically symmetric droplet flame [2].

will gain valuable experience building an appropriate numerical to simulate an actual physical process.

Results and Discussion:

The student reviewed relevant literature and developed an understanding of the liquid fuel combustion process. A brief summary of this literature review is discussed below. Law [3] introduced progress in the understanding of the fundamental properties that droplet combustion and vapourization are governed by, such as the d2 Law, the combustion of multi-component fuels such as coal-mixtures, droplet heating and accumulation major transient processes, finite rate kinetics, and droplet interactions. Bae and Avedisian [4] performed an experimental study on the droplet combustion of nonane (C9H20) at elevated pressures using low gravity and small droplets to promote spherical gas-phase symmetry. Westbrook et al. [5] reported the chemical kinetic mechanisms that have been developed to describe pyrolysis and oxidation of nine nalkanes larger than n-heptane, and include both high-temperature and low-temperature reaction pathways.

The student also used ANSYS Fluent and followed some instructional examples to get familiar with the software. A summary of performed work includes the following: (1) Familiarized with Fluent and its simulation and solving capabilities used in Computational Fluid Dynamics (CFD),

(2) Ran practice simulations of different tutorials and uses of Fluent such as laminar and turbulent pipe flow, flat plate boundary layer, steady and unsteady flow over a cylinder and flow over an airfoil, and

(3) Began reading into the CHEMKIN module of ANSYS that is used to model combustion reactions and the species and reactions produced.

Impact/Significance:

This project allows the student to gain hands-on experience using simulation software to simulate engineering problems with practical applications. This project lays a good foundation for the student’s graduate studies via engaging research experience.

References:

1. S.R. Turns, An introduction to Combustion, 3rd ed., McGraw-Hill, New York, 2012.

2. Y. Xu, Combustion dynamics of bio-derived, surrogate, and transporation fuel systems, Ph.D., Cornell University, Ithaca, NY, 2017.

3. C.K. Law, Recent advances in droplet vaporization and combustion, Progr. Energy Combust. Sci., 8 (1982) 171-201.

4. J.H. Bae, C.T. Avedisian, High-pressure combustion of submillimeter-sized nonane droplets in a low convection environment, Combust. Flame, 145 (2006) 607-620.

5. C.K. Westbrook, W.J. Pitz, O. Herbinet, H.J. Curran, E.J. Silke, A comprehensive detailed chemical kinetic reaction mechanism for combustion of n-alkane hydrocarbons from n-octane to n-hexadecane, Combust. Flame, 156 (2009) 181-199.

Numerical Experimentation of Mast Cells’ Immunogenicity and Adaptability to Airborne Allergen

Laura Marthe Emilie Ngansop and Kazeem Olanrewaju* Department of Chemical Engineering, College of Engineering

Introduction:

Allergy is the 6th leading cause of chronic illness in the U.S. with an average of over 50 million allergic patients each year and an annual cost of over $18 billion1. Allergic conditions are one of the prevalent pathophysiological conditions among children with over 90,000 emergency room visits due to anaphylaxis, a severe allergic reaction that may sometime lead to death if unattended to promptly 1-3.The most common indoor and outdoor airborne allergens that are highly susceptible to immune cells' inflammatory response (allergic reaction) is the pollen from trees, grass, or weed. It is a general assertion that allergic reaction does not have a perfect cure but can be remediated to a bearable minimum where repeated allergic reaction can be reduced drastically 6. Current remediation and diagnostic procedures for allergic and related diseases are fraught with challenges such as a conjecture approach to immunotherapy recovery rate. Other challenges include prolonged immunotherapy mediation and treatment, unpredicted interactive behavior of species with various physiological units, issues with vital species delivery rate, and bioavailability 7. These challenges are due to limited accessibility to studying the immune system in real-time with in-vivo and in-vitro experimental approaches 8. However, the main processes related to these challenges are transport, transformation, and interactions of species (mast cells and allergen) at various physiological scales (systems, organs, tissues, and cells) 9-11. The research project is designed to fundamentally address some of these challenges and the ascribed mechanisms through computational modeling of the immunodynamics of mast cells and airborne allergens in virtual microvascular and interstitium systems.

Objectives/goals:

Therefore the objective of this research is to quantify Mast cells immunogenicity and predicts their temporal adaptability to airborne allergens using numerical modeling. A process flow scheme is developed to delineate steps involve species transport and transformation mechanisms leading to the immunogenicity and adaptability. The identified transport and metabolism mechanisms are numerically defined to set up the immunogenicity and adaptability numerical scheme in the computational platform. The physiological effect of the various species involved in the sensitization, effector, and adaptability phases as portrayed in the mechanistic models are quantitatively assessed. Numerical experimentation of mast cells inflammatory response and desensitization to allergen show significant potential to offer quantitative insight into improving temporal prediction of mast cells adaptability to allergen.

Materials and Methods:

Develop a mechanistic process scheme to delineate steps involving species transport and transformation mechanisms leading to mast cells hypersensitivity to allergen and the desensitization mechanism. Identify and numerically define specific transport and transformation mechanisms in both the sensitization and desensitization and set up the modeling scheme in MATLAB to quantified these processes. The pathophysiological effect of the variables (pollen,

dendritic cells, antigen, inflammator y mediators (cytokine , chemokine , etc) involved as defined in both mechanistic models are evaluated.

The flow chart has been developed and the relevant equations to model the mechanisms are in progress. Numerical experimentation of the causative mechanism of the immunogenicity and adaptability of mast cells to innocuous pollen is to help improve the predictability of Allergen –Specific Immunotherapy as its relate to patients recovery. The numerical rate scheme for the quantification and analysis of the mast cells immunogenicity and adaptability to airborne allergens will be developed and solved in MATLAB and COMSOL Multiphysics. MATLAB offers a platform where the matrix and ordinary differential equation solver methods can be directly applied to the numerical rate scheme while the COMSOL Multiphysics chemical engineering module provides user interfaces for developing, probing, and reviewing chemical equations, kinetic rates, and transport equations. The model will be validated based on published in-vivo and in-vitro data. Finally, evaluate the effect of these variables, transport mechanism, and transformation mechanisms on both sensitization and desensitization to the allergens.

Results and Discussion:

Process flow scheme: The process flow scheme for the sensitization (immunogenicity) and desensitization (adaptability) of Mast Cells to allergen are shown in Figures 1a and 1b below

Numerical Modeling Scheme for Sensitization Phase Mechanisms

Numerical Modeling Scheme for Sensitization Phase Mechanisms

1st STEP: Flux of Pollen across epithelial cell membrane into tissue (interstitium):

2nd STEP: Transformation of Dendritic Cell (DC) to Dendritic Cell Antigen Presenting Cell (APC):

3rd STEP: Dendritic Antigen Presenting Cell Transport to the Lymph Node

Figure 1a: Mast Cells’ Immunogenicity to Allergens

Figure 1a: Mast Cells’ Adaptability to Allergens

4th STEP: APC Interacting with Naive T-Cells (CD4+ T lymphocytes)

5th STEP: Interleukins Interacting with TnN in the APC_TnN complex to produce T-helper Cells (Th2)

6th STEP: T-helper Cells (Th2) Transport to the Site of Exposure

7th STEP: T-helper Cells (Th2) and Interleukins interacting with Activated B-Cell to produce Plasma and Memory Cells

8th Step : Plasma Cells stimulated by Interleukins to produce/secret Antibody (Immunoglobin)

9th STEP: IgE binding to IgE Receptors (Fc

on Mast and Basophil Cells : Sensitization

The numerical modeling scheme for the early phase and desensitization mechanisms has been developed. However, it will be presented in the future report.

Impact/Significance:

The study offers the opportunity to study mast cells’ immunogenicity and adaptability to airborne allergens in-silico where different scenario leading to the pathophysiological conditions can be assessed. The virtual platform can provide insight into the in-depth mechanisms of allergenicity, immunogenicity, and to some extent allergen specific immunotherapy treatment of the disease. Student was exposed to the concept of numerical experimentation and various

chemical principles that can be applied to studying the immunopathophysiological mechanisms of mast cells to specific antigens (airborne allergens).

References:

1. American College of Allergy, Asthma, and Immunology. Allergy facts. https://acaai.org/allergies/allergies-101/facts-stats/. Updated 2022. Accessed October 4, 2022.

2. Clark S, Espinola J, Rudders SA, Banerji A, Camargo CA. Frequency of US emergency department visits for food-related acute allergic reactions. Journal of Allergy Clinical Immunology. 2011;127(3):682- 683.

3. PJ, Jerschow E, Umasunthar T, Lin R, Campbell DE, Boyle RJ. Fatal anaphylaxis: Mortality rate and risk factors. The Journal of Allergy and Clinical Immunology: In Practice. 2017;5(5):1169-1178.

4. Tkacz JP, Rance K, Waddell D, Aagren M, Hammerby E. Real-world evidence costs of allergic rhinitis and allergy immunotherapy in the commercially insured united states population. Current Medical Research and Opinion. 2021;37(6):957-965.

5. Allergy and Asthma N. Allergy statistics in the US | allergy & asthma network. https://allergyasthmanetwork.org/allergies/allergy-statistics/. Updated 2022. Accessed Oct 11, 2022.

6. Asthma and Allergy Foundation of America. Allergy facts and figures. ttps://www.aafa.org/allergy- facts/. Updated 2022.

7. Hurst S, Loi C, Brodfuehrer J, El-Kattan A. Impact of physiological, physicochemical and biopharmaceutical factors in absorption and metabolism mechanisms on the drug oral bioavailability of rats and humans. Expert opinion on drug metabolism & toxicology 2007;3(4):469-489.

8. Ekmekcioglu C. A physiological approach for preparing and conducting intestinal bioavailability studies using experimental systems. Food Chemistry. 2002;76(2):225-230.

9. Blaustein P. Mordecai, Kao P.Y.Joseph , and Matteson R. Donald. Cellular physiology and neurophysiology. 2nd ed. St.Louis, Missouri 63043: Elsevier; 2011.

10. Truskey GA, Yuan F, Katz DF. Transport in organs. In: Transport phenomena in biological system. Upper Saddle River, New Jersey: Pearson Prentice Hall; 2009:461

11. Ultman JS, Baskaran H, Saidel GM. Biomedical mass transport and chemical reaction: Physicochemical principles and mathematical modeling. Hoboken, New Jersey: John Wiley and Sons; 2016:179-280