Digital Commons Network^™

Meat, The Future: The Role Of Regulators In The Lab-Grown Revolution, Joseph B. Davault, Michael S. Sinha

All Faculty Scholarship

The United States is one of the largest consumers of meat globally. The production of meat contributes substantially to climate change due to the levels of greenhouse gasses emitted and the amount of land, water, feed, and other natural resources required to raise animals used for meat. Traditional meat production is another major source for the emergence of zoonotic diseases and antimicrobial-resistant pathogens. Nevertheless, Americans consume more meat now than at any time in the nation’s history.

Advocates for policy change aimed at addressing the risks associated with meat production have typically focused on reducing meat consumption, alternatives to meat, …

Health Benefits And Adverse Effects Of Kratom: A Social Media Text-Mining Approach, Abdullah Wahbeh, Mohammad A. Al-Ramahi, Omar El-Gayar, Tareq Nasralah, Ahmed El Noshokaty

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Background: Kratom is a substance that alters one’s mental state and is used for pain relief, mood enhancement, and opioid withdrawal, despite potential health risks. In this study, we aim to analyze the social media discourse about kratom to provide more insights about kratom’s benefits and adverse effects. Also, we aim to demonstrate how algorithmic machine learning approaches, qualitative methods, and data visualization techniques can complement each other to discern diverse reactions to kratom’s effects, thereby complementing traditional quantitative and qualitative methods. Methods: Social media data were analyzed using the latent Dirichlet allocation (LDA) algorithm, PyLDAVis, and t-distributed stochastic neighbor …

I’M Not Lovin’ It: Re-Thinking Fast Food Advertising, Brody Shea, Michael S. Sinha

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In 1971, the Federal Trade Commission (“FTC”) and the Food and Drug Administration (“FDA”) agreed to prevent injury and deception to the consumer in advertising, detailing their respective roles in a Memorandum of Understanding (“MOU”).¹ The MOU proscribes that the FTC regulates truth in advertising relating to foods, drugs, devices and cosmetics while the FDA controls labeling and the misbranding of foods, drugs, devices, and cosmetics shipped in interstate commerce.² The MOU has been amended and an addendum added since 1971, but the material provisions have remained consistent for over a half-century.³

Importantly, the FDA and the …

Borrelia Burgdorferi Plza Is A Cyclic-Di-Gmp Dependent Dna And Rna Binding Protein, Nerina Jusufovic, Andrew C. Krusenstjerna, Christina R. Savage, Timothy C. Saylor, Catherine A. Brissette, Wolfram R. Zückert, Paula Schlax, Md A. Motaleb, Brian Stevenson

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The PilZ domain-containing protein, PlzA, is the only known cyclic di-GMP binding protein encoded by all Lyme disease spirochetes. PlzA has been implicated in the regulation of many borrelial processes, but the effector mechanism of PlzA was not previously known. Here, we report that PlzA can bind DNA and RNA and that nucleic acid binding requires c-di-GMP, with the affinity of PlzA for nucleic acids increasing as concentrations of c-di-GMP were increased. A mutant PlzA that is incapable of binding c-di-GMP did not bind to any tested nucleic acids. We also determined that PlzA interacts predominantly with the major groove …

Unpatenting Product Hops, Michael S. Sinha

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On July 9, 2021, President Joseph R. Biden signed Executive Order 14036 (“Promoting Competition in the American Economy”), which directed the U.S. Food and Drug Administration (FDA) and the U.S. Patent and Trademark Office (USPTO) to collaborate on new approaches to increasing competition and lowering prices in the pharmaceutical marketplace. In response, the USPTO outlined several new initiatives, among them an intent to improve the robustness and reliability of issued patents.

A major impetus for the Executive Order was the pervasive nature of pharmaceutical product hopping, which occurs when manufacturers introduce new follow-on versions of lucrative pharmaceutical products to the …

Reproductive Rights And Medico-Legal Education Post-Dobbs: A Fireside Chat, Michael S. Sinha, Anna Krotinger, Maya A. Phan, Louise P. King

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The Supreme Court’s 2022 decision in Dobbs v. Jackson Women’s Health Organization was a pivotal moment that reshaped the landscape of abortion policy and delivery of abortion care in the United States. To create a space for critical reflection on the implications of Dobbs for the teaching and learning of abortion care in both medical and legal education, the authors engage in a dialogue highlighting the varied perspectives of professionals and professionals-in-training in both the medical and legal professions. As new attacks on reproductive autonomy continue at both state and federal levels, we foreshadow a tumultuous landscape for abortion policy …

Physician Decision Making Under Uncertainty In A Post-Dobbs America, Molly J. Walker Wilson, Michael S. Sinha

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Following the Supreme Court's decision in Dobbs v. Jackson Women's Health Organization and a series of restrictive state laws post-Dobbs, physicians in many states now face difficult choices between evidence-based practice and criminal penalties. Previously, when deciding whether to provide abortion care, concern for the health of the patient was paramount. Now, fear of criminal penalties drives decision-making for physicians practicing in many areas of the country, including our home state: Missouri. For certain life-threatening complications, termination of pregnancy is warranted, but since Dobbs, physicians have been delaying these potentially lifesaving procedures for fear of criminal repercussions. Behavioral research on …

Ai Renaissance: Pharmaceuticals And Diagnostic Medicine, Ty J. Feeney, Michael S. Sinha

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The explosive growth of Artificial Intelligence (AI) in the modern era has led to significant advancements in the world of medicine. In drug discovery, AI technology is used to classify proteins as drug targets or non-targets for specific diseases, more accurately interpret and describe pharmacology in a quantitative fashion, and predict protein structures based on only a protein sequence for input. AI methods are used in drug development to generate predictive models for drug screening purposes, refine and modify candidate structures of drugs to optimize compounds, and predict a drug’s physiochemical properties, bioactivity, and toxicity. For medical devices, the advancement …

Navigating Export Control Laws In Animal Research: Key Considerations, Rani Muthukrishnan

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No abstract provided.

The Teapot Dome Scandal: The Supreme Court's Precedent That Changed The Political Corruption Prosecution Because Of Social Pressure, Jesus R. Jimenez-Andrade

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No abstract provided.

Trauma As Cultural Capital: A Critical Feminist Theory Of Trauma Discourse, Lucy Britt, Wilson H. Hammett

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This essay theorizes a problem for feminism posed by a particular form of trauma discourse. Feminists have played an important role in developing cultural and clinical conceptions of trauma, but one result of the destigmatization of trauma has been that trauma discourse is sometimes used as a form of cultural capital to reinforce existing hierarchies. In a novel application of Pierre Bourdieu's theory of distinction, we show how, when instrumentalized as cultural capital, trauma discourse can be used to reinforce patriarchy and other systems of oppression. We trace a critical feminist history of the struggle to understand and treat trauma. …

Second-Tier Marriages, Jeremiah A. Ho

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This Essay interrogates the reasoning behind the retrenchment toward LGBTQ rights progress that has taken place since marriage equality. With marriage rights for same-sex couples now "on the books," the Supreme Court's treatment of same-sex couples in both Masterpiece Cakeshop, Ltd. v. Colorado Civil Rights Comm'n and 303 Creative LLC v. Elenis reveals the status quo's hesitancy to recognize same-sex relationships on equal footing. Retrenchment, however, only describes the moment itself; it alludes to but offers no comprehensive or satisfying theory that identifies the motives behind the moves. This Essay theorizes from within the context of the Supreme Court's LGBTQ …

Political Polarization And The Dynamics Between Actual Income And Perceived Income Inequality In The United States, 1987 To 2021, Cary Wu, Kriti Sharma, Edward Haddon, Francesco Duina

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The rich often perceive lower levels of inequality than the poor. In recent decades, however, notions regarding the equality or inequality of our society have progressively taken on a more political nature. Consequently, people’s perceptions of income inequality may be less associated with their actual income status and more with their political ideology. The authors visualize this “political turn” using data from the U.S. General Social Survey (1987–2021). The analysis shows that historically actual income and perceived inequality had an inverse relationship, independent of political alignment. Yet since 2000, this has changed: whereas Republicans show a deepening inverse correlation after …

Level Up! Priming Hobbyist Political Identity Using Survey Experiment, Pavel Bačovský

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Recent research suggests that a strong identity attachment to leisure activity affects the hobbyists' political preferences and behavior. This paper further evaluates the claim that hobbyists - in this case, gamers - react differently to political stimuli that directly involve their hobby of choice. Using original survey experiment data, this paper shows that gamers become more interested in foreign trade policy when presented in the context of video games. This finding indicates that even seemingly apolitical identities matter in framing political behavior. Aspects of hobbyist identities seep into political attitudes, even if preferences in the strictest meaning of the word …

Dark Side Of Genai: A Blackbox Analysis Of X, Ahmed El Noshokaty, Tareq Nasralah, Omar El-Gayar, Mohammad A. Al-Ramahi, Abdullah Wahbeh

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Recent advancements in generative artificial intelligence (GenAI) have raised many fears, risks, and concerns (Kim 2023; Okey et al. 2023). To shed light on the dark side of GenAI, we collected 55,916 posts from X (formerly Twitter). Based on the content of these posts, we manually labeled a sample set with the corresponding dark side, then identified a short, comprehensive list of GenAI dark sides. Using this list, we trained the ReadMe classifier, a supervised learning algorithm on Brandwatch (“Crimson Hexagon and Brandwatch” 2020), to classify the remaining posts. Further analysis, including emotion analysis and analysis of professions and interests …

A Comparative Analysis Of The Interpretability Of Lda And Llm For Topic Modeling: The Case Of Healthcare Apps, Omar El-Gayar, Mohammad A. Al-Ramahi, Abdullah Wahbeh, Tareq Nasralah, Ahmed El Noshokaty

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This study compares the interpretability of the topics resulting from three topic modeling techniques, namely, LDA, BERTopic, and RoBERTa. Using a case study of three healthcare apps (MyChart, Replika, and Teladoc), we collected 39,999, 52,255, and 27,462 reviews from each app, respectively. Topics were generated for each app using the three topic models and labels were assigned to the resulting topics. Comparative qualitative analysis showed that BERTopic, RoBERTa, and LDA have relatively similar performance in terms of the final list of resulting topics concerning human interpretability. The LDA topic model achieved the highest rate of assigning labels to topics, but …

Factors Affecting Users’ Satisfaction With Telehealth Apps: Analysis Of Users Reviews Using Bert, Abdullah Wahbeh, Tyler Howes, Omar El-Gayar, Raed Seetan, Mohammad A. Al-Ramahi, Ahmed Al-Omari

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Telehealth mobile apps and telehealth services are increasingly used by patients, particularly, post-COVID-19. This study examines factors related to users’ satisfaction with these apps and services by analyzing reviews from actual telehealth app users. A total of 53,209 reviews were collected from nine telehealth apps on the Google Play store. Using BERT embeddings, UMAP, and HDBSCAN, topics were generated and labeled to identify these factors. Results showed that telehealth app users expressed several factors related to satisfaction with telehealth apps, which could impact the acceptability and adoption of such apps. These include usability (ease of use), usefulness, convenience and efficiency, …

Indigenous Practice And Community-Led Climate Change Solutions: The Relevance Of Traditional Cosmic Knowledge Systems, Rani Muthukrishnan, Ranjan Datta

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This book centers Indigenous knowledge and practice in community-led climate change solutions.

This book will be one of the first academic books to use the consciousness framework to examine and explain humans' situatedness and role in maintaining ecosystems' health. Drawing on teachings from the Indigenous Adi-Shaiva community, the authors present up-to-date research on meanings and implications of South Asian traditional cosmic knowledge, which focuses on relationality and spirituality connected to climate change. This knowledge can create innovative climate change solutions in areas including land, water, traditional management, sustainability goals and expectations, and state development projects. Overall, this book provides an …

Are You Talking To Me? How Ideological And Gender Characteristics Moderate The Effect Of Legitimizing Rhetoric On Scotus Legitimacy, Ryan J. Williams

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Possessing neither purse nor sword, the unelected US Supreme Court relies on sustained public confidence in its institutional credibility to give force to its decisions. Previous research shows that Supreme Court justices are increasingly making public appearances to engage in a course of institutional maintenance to preserve its legitimacy. Amid a potential legitimacy crisis, justices seek to shore up the Court’s public support in these public appearances by emphasizing the apolitical nature of the Court and its decision making. The question for a growing body of literature is whether these attempts at institutional maintenance do, in fact, lead to higher …

Sustained Beneficial Infections: Priority Effects, Competition, And Specialization Drive Patterns Of Association In Intracellular Mutualisms, Malcolm Hill, Barry Lawson, John W. Cain, Nasheya Rahman, Shiv Toolsidass, Tongyu Wang, Sara Geraghty, Eberardo Raymundo, April Hill

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Intracellular symbioses provide a useful system for exploring evolutionary and ecological forces that shape mutualistic partnerships. Within- and among-host competitiveness driven by different strategies that symbionts adopt as they transfer materials to the host across a sub-cellular membrane might explain patterns of host:symbiont association observed in natural systems. We tested the hypothesis that different translocation strategies employed by symbionts affect their ability to occupy host habitats using two distinct modeling approaches. The first involved constructing a deterministic, Lotka-Volterra-type model with two symbiont species competing for access to a single host. The model recovered expected behaviors of co-occupancy/coinfection as well as …

The Relationship Between Balance Confidence And Center Of Pressure In Lower-Limb Prosthesis Users, Gary Guerra, John Smith, Eun-Jung Yoon

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Background: Agreement between the activities-specific balance confidence scale (ABC) and center of pressure (CoP) in prosthesis users is still very much unknown. The purpose of this study was to investigate the agreement between ABC and CoP in lower-limb prosthesis users. Methods: Twenty-one individuals with lower-limb prostheses were recruited. Participants were provided with the ABC scale and performed static balance tasks during eyes opened (EO) and eyes closed (EC) conditions whilst standing on a force platform. Pearson product moment coefficients between CoP displacements and ABC scores were performed. Participants were also stratified by those who had better (≥80 on ABC scale) …

Recognition Of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, And Optical Character Recognition (Ocr) Techniques, Khalid Nahar, Izzat Alsmadi, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Hasan Gharaibeh, Ali Saeed Almuflih, Fahad Alasim

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Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages, such as Arabic. To fill this gap, we propose a hybrid model that combines feature extraction with deep learning models and then uses machine learning (ML) and optical character recognition (OCR) methods and applies grid and random search optimization algorithms to obtain …

U2-Net: A Very-Deep Convolutional Neural Network For Detecting Distracted Drivers, Nawaf Alsrehin, Mohit Gupta, Izzat Alsmadi, Saif Addeen Alrababah

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In recent years, the number of deaths and injuries resulting from traffic accidents has been increasing dramatically all over the world due to distracted drivers. Thus, a key element in developing intelligent vehicles and safe roads is monitoring driver behaviors. In this paper, we modify and extend the U-net convolutional neural network so that it provides deep layers to represent image features and yields more precise classification results. It is the basis of a very deep convolution neural network, called U2-net, to detect distracted drivers. The U2-net model has two paths (contracting and expanding) in addition to a fully-connected dense …

The Slogans And Goals Of Antitrust Law, Herbert J. Hovenkamp

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This is a comparative examination of the slogans and goals most advocated for antitrust law today – namely, that antitrust should be concerned with “bigness,” that it should intervene when actions undermine the “competitive process,” or that it should be concerned about promoting some conception of welfare. “Bigness” as an antitrust concern targets firms based on absolute size rather than share of a market, as antitrust traditionally has done. The bigness approach entails that antitrust cannot be concerned about low prices, or the welfare of consumers and labor. Nondominant firms could not sustain very high prices or cause significant reductions …

Peer Leader Perspectives From A Pltl Implementation In A Hispanic-Serving Institution, Madhavan Narayanan, Kasey Powers, Dhananjaya Premawardena, Davida S. Smyth, Et Al.

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Peer-Led Team Learning (PLTL) is a pedagogical approach that has been shown to benefit all students, especially underrepresented minority students and peer leaders in Science, Technology, Engineering, and Mathematics (STEM) disciplines. In this work, we present results from our study of the impact of PLTL on our peer leaders from a controlled implementation in general biology, general chemistry, and statistics courses at a Hispanic-serving, minority-serving institution. More specifically, we have measured our PLTL program’s impact on our peer leaders' skill development, engagement with the subject material, and sense of belonging as peer leaders. Weekly peer leader reflections analyzed using the …

Microgravity Facilities For Cold Atom Experiments, Matthias Raudonis, Albert Roura, Matthias Meister, Christoph Lotz, Ludger Overmeyer, Sven Herrmann, Andreas Gierse, Claus Lämmerzahl, Nicholas P. Bigelow, Maike Lachmann, Baptist Piest, Naceur Gaaloul, Ernst M. Rasel, Christian Schubert, Waldemar Herr, Christian Deppner, Holger Ahlers, Wolfgang Ertmer, Jason R Williams, Nathan Lundblad, Lisa Wörner

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Microgravity platforms enable cold atom research beyond experiments in typical laboratories by removing restrictions due to the gravitational acceleration or compensation techniques. While research in space allows for undisturbed experimentation, technological readiness, availability and accessibility present challenges for experimental operation. In this work we focus on the main capabilities and unique features of ground-based microgravity facilities for cold atom research. A selection of current and future scientific opportunities and their high demands on the microgravity environment are presented, and some relevant ground-based facilities are discussed and compared. Specifically, we point out the applicable free fall times, repetition rates, stability and …

The Trouble With Time Served, Kimberly Ferzan

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Every jurisdiction in the United States gives criminal defendants “credit” against their sentence for the time they spend detained pretrial. In a world of mass incarceration and overcriminalization that disproportionately impacts people of color, this practice appears to be a welcome mechanism for mercy and justice. In fact, however, crediting detainees for time served is perverse. It harms the innocent. A defendant who is found not guilty, or whose case is dismissed, gets nothing. Crediting time served also allows the state to avoid internalizing the full costs of pretrial detention, thereby making overinclusive detention standards less expensive. Finally, crediting time …

Self-Supervised Learning Application On Covid-19 Chest X- Ray Image Classification Using Masked Autoencoder, Xin Xing, Gongbo Liang, Chris Wang, Nathan Jacobs, Ai-Ling Lin

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The COVID-19 pandemic has underscored the urgent need for rapid and accurate diagnosis facilitated by artificial intelligence (AI), particularly in computer-aided diagnosis using medical imag- ing. However, this context presents two notable challenges: high diagnostic accuracy demand and limited availability of medical data for training AI models. To address these issues, we proposed the implementation of a Masked AutoEncoder (MAE), an innovative self-supervised learning approach, for classifying 2D Chest X-ray images. Our approach involved performing imaging reconstruction using a Vision Transformer (ViT) model as the feature encoder, paired with a custom-defined decoder. Additionally, we fine-tuned the pretrained ViT encoder using …

Career Mobility For Black Professionals: Mentorship As An Underground Railroad, Duane A. Williams, Rahjaun Gordon, Pearl Stewart

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Career mobility for Black individuals may appear individualistic, ignoring the collectivistic endeavor involved to achieve success. This qualitative study explored participants’ mentorship relationships, analogous to the underground railroad system, as it relates to navigating their careers. Participants, who are Black professionals in various career fields, detailed how the support provided by their mentors allowed them to understand the nuances of career mobility while gaining lifelong relationships, resources, and networks necessary for continued and sustainable success. The theoretical frameworks for this study used Phenomenological Variant Ecological Systems Theory (PVEST) and Social Capital Theory. Analysis of 15 individual semi[1]structured interviews were highlighted …

Identification Of Unsuccessful Students In General Chemistry, G. Robert Shelton, Joseph M. Simpson, Diana Mason

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The Networking for Science Advancement (NSA) team collected data from multiple general chemistry courses at nine universities within a broad geographic setting in a majority-minority US state. Data include diagnostic scores on the Math-Up Skills Test (MUST), quantitative literacy/quantitative reasoning (QL/QR) quiz, along with student demographics, and overall course grades. From these data the team determined how automaticity skills in procedural arithmetic and quantitative literacy and reasoning can be used to predict success in lower-division chemistry courses. By expanding this dataset, we extended our investigations to discover what characterizes successful and unsuccessful students in general chemistry, first and second semesters …