bluuebunny/crossref_metadata_2025 huggingface dataset:
Opportunities to respond and behavior-specific praise in the juvenile justice setting : teacher professional development and coaching
Authors:   , Graves Katherine Ann
Published: September 2024

Students in the juvenile justice setting have unique behavioral needs as compared to those in general education environments. Thus, professional development on behavioral management practices is important for teachers in these settings. Further, one instance of professional development has been shown to influence teacher knowledge, but the use of coaching is more effective in influencing teacher skill acquisition. This study employed a single subject, multiple-baseline across participants design to examine the impact of professional development modules and coaching on teacher use of opportunities to respond and behavior-specific praise, on student problem behavior. Results from the study indicate that only using the professional development modules did not change teacher not student behavior; however, the addition of coaching lead to increased use of targeted skills. Throughout the intervention, student problem behavior did not change as a result of the change in teacher behavior. Following the intervention, the teacher participants rated the intervention as a whole, the professional development modules, and the coaching to be useful, sustainable, feasible, and acceptable. The present study addresses a significant gap in the literature on the professional development needs for teachers in juvenile justice settings. Implications and future research are discussed.
Academic library assessment success in demonstrating value to parent organizations
Authors:   , Horne-Popp Laura Marie
Published: September 2024

The practice of assessing academic libraries attempts to review library functions to improve as well as demonstrate value. However, library assessment has not been fully investigated from the practitioner perspective. This qualitative study focused on practitioners' perspectives of how library assessment assists the academic library utilizing a qualitative approach. The aim of this research was to determine what aspects of library assessment were successful from the perspective of librarians who coordinate assessment and library administrators who often make decisions and arguments utilizing assessment findings. Using a variety of analysis including a survey capturing assessment practices, interviews of assessment librarians and library administrators, evaluation of assessment documents, and capturing budget data, the study found all participants, regardless of position or classification of the institution, perceived quality improvement as the most valuable aspect of library assessment. Participants agreed focusing on students as the primary stakeholders and utilized library assessment to gather student feedback as well as demonstrate impact on students. Participants also discussed using library assessment information for data-driven decision-making, quality assurance practices such as accreditation, and raising the library profile through promotions that demonstrate value as well as illustrating the resources needed to provide necessary services that support library patrons and highlight the purposes of higher education to be a public good.
Meanings of the U.S. withdrawal from Afghanistan as framed and reified in the New York Times : discourse analysis and visual analysis
Authors:   , MacNeil Cory Wes
Published: September 2024

The high stakes of war stress-tests every practice, tenant, ethos, and ethical code of journalism to the breaking point, making war journalism (herein, writing and photographs) a rich ground for studying meaning-making through the social authority of journalism. Pairing framing theory with social construction of knowledge as theoretical lenses, this research performed discourse and visual analyses on an exhaustive collection of New York Times'--the newspaper that prides itself on publishing all the news [and meaning] that's fit to print--articles and photographs from the February 29, 2020, public announcement of the U.S. withdrawal from a two-decade war in Afghanistan to the August 31, 2021, close of the withdrawal. Examining 475 articles with 1,412 accompanying photographs, this research discovered 13 consistent voices contending for 10 reified meanings. This dissertation contributes to the literature on journalistic authority, war journalism, and war photojournalism through thorough examination of NYT narrative and visual construction of the withdrawal.
Diversifying the physician workforce : black medical students matriculate through holistic admissions
Authors:   , Simmons Andrea Marie Johnson
Published: September 2024

Attending medical school is a dream for many, and thousands of people apply each year. However, the mission to medical school is a dream deferred for some Black students. This qualitative study investigated the successful matriculation of Black students into medical school through holistic admissions, aiming to identify the factors contributing to their success. Although Critical Race Theory explains how some students encountered systemic, institutional, and personal challenges that hindered access, the anti-deficit achievement framework (ADAF, Harper S. R., 2012) guided the study to focus on success and achievements. Drawing upon S. R. Harper's ADAF and utilizing a critical narrative inquiry approach, including photovoice methodology, the research delved into the experiences of six Black medical students who navigated the admissions process successfully. Through two semi-structured interviews, the study explored holistic measures to assess the "whole" student and the markers of success: success-promoting experiences, adaptive attributes and skills, and resources that led to matriculation. The findings revealed that these students relied on personal motivation, supportive relationships, rigorous preparation, and developing critical attributes and skills to navigate holistic admissions and the various challenges related to systemic barriers such as the Medical College Admission Test (MCAT). The study emphasized the significance of understanding the intricacies of the rich descriptive experiences of Black medical students, particularly considering the recent shifts away from race-based admissions policies. By highlighting the holistic nature of successful candidates and advocating for a nuanced approach to admissions criteria, the research aims to inform policy and practice to foster greater diversity within the physician workforce.
Trauma-informed classroom check-up : feasibility and social acceptability with effects on educator efficacy, coping, stress and burnout
Authors:   , Weigand Tanya
Published: September 2024

The purpose of this feasibility project is to implement and evaluate the effect of a trauma-informed modification on an evidence-based classroom intervention model to promote effective trauma-informed classroom management and coping skills with potential reduction of educator stress and burnout. Trauma is the most-common psychological health condition with adverse childhood experiences strongly correlated to increased risk for negative outcomes (i.e. mental and physical health problems, substance abuse and criminal justice involvement). Despite a wealth of knowledge regarding trauma impact on youth, a lack of research exists on the impact of trauma on educators. Educator stress, secondary trauma, and compassion fatigue are significantly high, due in part to trauma exposure leading to difficult student behaviors along with personal trauma responses, leading to educator burnout. This feasibility study utilized a pre-posttest design to assess a pilot of a traumainformed adaptation of the Classroom Check-up. The Trauma-Informed Classroom Checkup (TI-CCU) uses an assessment-based feedback session targeting teacher behavior through intervention to improve trauma-informed knowledge, coping, self-efficacy, and basic work satisfaction promoting reduction of educator stress and burnout.
Hybrid quantum-classical machine learning for canonical fluid dynamics and heat transfer problems
Authors:   , Bazgir Adib
Published: September 2024

This thesis introduces the implementation of some hybrid frameworks for quantum and classical machine learning techniques associated with the fluid dynamics and heat transfer problems. Chapter 1 discusses an introduction concerning the high-performance computing, physics-based CFD simulations, classical machine learning, and quantum machine learning. In Chapter 2, the study further concentrates on the exploration of advanced physics-base computational methods emphasizing data generation to be considered as input into the following machine learning models. Chapter 2 delves into the numerical analysis of fluid dynamics and heat transfer problems such as airborne particle dispersion, deep-sea sponge, inverse heat conduction problem, and turbulent reacting flow. This chapter highlights the use of simulation to understand complex problems in precise settings, providing insights into the interaction between various fluids and the impact on heat transfer processes. Chapter 3 shifts the focus to the machine learning approaches into the behavior of hybrid fluids. This exploration reveals significant enhancements in analyzing the fluid dynamics and heat transfer problems due to the unique characteristics which the machine learning and quantum computing can offer to the research community. Together, these chapters (chapter 2 and chapter 3) present a comprehensive study that integrates computational fluid dynamics (CFD) simulations with machine learning research to advance the understanding of fluid behavior and heat transfer mechanisms, contributing to the development of more efficient and effective thermal management solutions. Finally, the thesis is concluded by Chapter 4 outlining the major findings along with this thesis.
The relationship between unplanned drinking and drinking context on alcohol-impaired driving cognitions and behavior in daily life
Authors:   , Darmour Charles
Published: September 2024

This study investigated the association between unplanned drinking, drinking context, and alcohol-impaired driving (AID) cognitions and behavior among young adults using ecological momentary assessment (EMA) over six weeks. Participants were recruited from a large Midwestern university and the surrounding community, with eligibility criteria including regular driving and alcohol consumption. The analyses focused on the impact of unplanned versus planned drinking episodes and on- versus off-premises drinking locations on perceptions of AID danger, willingness to drive, and actual AID behavior, while accounting for alcohol consumption using a novel breath alcohol concentration (BrAC) Bluetooth device. Results indicated that unplanned drinking episodes were associated with lower perceived danger of AID, increased willingness to drive after drinking, and higher odds of engaging in AID, compared to planned drinking episodes. Similarly, drinking in on-premises locations (e.g., bars, restaurants) was associated with higher odds of AID behavior compared to off-premises drinking (e.g., at home, friends' houses), but not related to riskier AID cognitions. These findings highlight the need for targeted interventions and policies to reduce unplanned drinking and address the risks associated with on-premises alcohol consumption. Focusing on these risk factors can enhance efforts to prevent AID and improve public health outcomes among young adults.
How the BTS fandom promotes transculturalism through social media
Authors:   , Hamai Campbell Mae
Published: September 2024

This paper attempts to examine an ethnographic study into cultural immersion via activity in a digital fandom of a foreign popular culture and how these fandoms are undeniable forces in the transmission of foreign cultures themselves through an autotheoretical lens. This will be explored through an account of the author's own experience of becoming a fan of the South Korean music act BTS which led to an osmosis-style education of South Korean practices and language. In doing so, this paper will contribute to the disciplines of the digital diaspora, fandom identity, and transculturalism and transnationalism. Transculturalism and transnationalism refer to the flow of cultural information, practices, and beliefs across national and cultural borders decided by geography and political rulings. These borders used to be difficult to cross, however, the invention of the internet and the revolution of international travel for both people and products has allowed for an explosion of transcultural information being exchanged at exponential rates and volumes (Guo). This explosion has contributed to "a reorientation of diaspora studies towards new configurations of participation and identification" (Candidatu and Ponzanesi, "Abstract"). I argue that these new configurations can include digital fandoms.
Validation of a simulated commercial plain bagel baking process to control salmonella and Shiga toxin producing Escherichia coli
Authors:   , Hunt Conor Logan
Published: September 2024

Flour is a minimally processed raw agricultural product with low water activity and is typically not conducive to bacterial growth. Despite this, pathogenic microorganisms such as Salmonella and STEC can withstand the drying process and persist in flour for weeks and even months in a desiccated state. Both Salmonella and STEC have been associated with several foodborne illness outbreaks linked to flour and its derivatives in the United States. The FDA Food Safety Modernization Act (FSMA) mandates validation of preventive controls, such as baking, to control potential foodborne pathogens and assure the safety of finished food products. To the best of our knowledge, there have been no prior baking studies on thermal inactivation of Salmonella and STEC in plain bagels. Therefore, studies were conducted to validate the effectiveness of plain bagels baking process ((450 [degrees] F) for 14 minutes) as an effective kill-step for controlling Salmonella and STEC in the event of pre-baking contamination. Additionally, water activity and pH in plain bagels during baking, and thermal inactivation kinetics (D- and z-values) of Salmonella and STEC in plain bagels dough were studied. The results clearly demonstrated that baking plain bagels at 450 [degrees] F for at least 14 minutes will result in a [greater than] 5 log reduction in Salmonella and STEC population thus providing an effective kill-step assuring the safety of the finished food products. The D- values of Salmonella in plain bagels at, 56, 59, and 62 [degrees] C were 24.5 [plus or minus] 1.5, 13.3 [plus or minus] 1.85, and 6.8 [plus or minus] 1.05 min with a z- value of 11.1 [plus or minus] 1.58 [degrees] C. The D- values of STEC in plain bagels at, 56, 59, and 62 degreesC were 26.3 [plus or minus] 1.55, 9.0 [plus or minus] 0.27, and 2.50 [plus or minus] 0.15 min with a z- value of 5.8 [plus or minus] 0.16 [degrees] C.
Variable selection procedures under collinearity (multicollinearity)
Authors:   , Khumalo Busiswa Tive
Published: September 2024

Variable selection is an important area of statistical modeling, which is still an active area of research. In this study, we investigated the performance of four variable selection procedures: backward elimination, Bayesian, least absolute shrinkage selection operator (lasso), and ridge selection operator under collinearity. Specifically, we focused on the variable selection accuracy, prediction accuracy, and their ability to mitigate the impact of collinearity on variable selection and predictive accuracy. What we found is that sample size, and the strength of the regression coefficient impacted the selection accuracy specifically in the standard linear regression simulation, where the simulation results showed that as the sample size decreased, the selection accuracy decreased specifically for methods such as backward elimination, Bayesian, and the lasso, while that of the ridge selection operator the variable selection accuracy increased. In the high dimensional simulation, the lasso outperformed the other variable selection methods, indicating its unique features to select sparse models even when the number of parameters exceeds the sample size. However, the estimates were extremely biased for all methods investigated in the high dimensional regression simulation. Though the computational times were not reported, the ridge selection operator was the slowest, especially for large sample sizes or number of predictors. This indicates its unfeasibility in the practical world where sample sizes or number of predictors are large since it is too computationally costly. In terms of prediction, overall, Bayesian g-prior variable selection and the lasso-fitted models performed better than those from the other variable selection methods. In the last section we discuss the limitations and provide recommendations on using these methods.
Comparison of four endotracheal tube cleaning protocols in anesthetized dogs
Authors:   , Marquis Charlotte Rose
Published: September 2024

The purpose of this dissertation is to review the evidence available for endotracheal tube (ETT) disinfection and compare the efficacy of four endotracheal tube cleaning protocols in a clinical population of anesthetized dogs. A ten-question survey designed to determine endotracheal tube reuse and cleaning practices was distributed via email to a sample of veterinary anesthesiologists. Four endotracheal tube cleaning protocols, selected based upon survey results, were chosen for use in this prospective clinical study. Dogs were intubated with sterile polyvinyl chloride (PVC) endotracheal tubes. At extubation, each endotracheal tube was cultured for bacterial growth, assigned to one of four cleaning protocols [water scrub (P1), detergent scrub (P2), detergent scrub and chlorhexidine gluconate (CHG) soak (P3), or detergent scrub and bleach soak (P4)], and cultured again after air-drying. Bacterial genera were identified using mass spectrometry and/or 16s rRNA sequencing. The proportions of endotracheal tubes exhibiting no post-cleaning growth were compared between protocols using Fisher's exact test with Bonferroni correction. Endotracheal tube cleaning methods used by respondents varied widely and no reported methods were evidence-based. Pairwise comparisons did not reveal statistically significant differences in elimination of post-cleaning bacterial culture growth between any of the tested protocols. At this time, further research is necessary to identify a safe, efficacious endotracheal tube cleaning protocol for use in small animal practice.
A cell atlas of swine immune system development
Authors:   , May Alyssa
Published: September 2024

Swine are an agricultural species of global economic importance. Additionally, pigs are increasingly used as biomedical models for a range of human diseases as they share many physiological, metabolic, and developmental similarities to humans. Diseases that involve the immune system, especially those caused by infectious diseases, can result in significant losses in swine production. Understanding the porcine immune system is crucial to efforts to control and prevent such diseases. It also promotes using pigs as a preclinical model to study human immunological illnesses. However, many aspects of the pig's immune system remain poorly understood. This thesis describes using single-cell RNA sequencing (scRNA-seq) to create a cell atlas of pig fetal hematopoiesis which was compared to published human scRNA-seq datasets. Cells isolated from fetal liver were collected at 45 days of gestation (DG), while cells from thymi and bone marrow were isolated at 48-, 60-, 75-, and 90- DG as well as 1 day of age (DOA) and 7-months of age (MOA) after birth. This data establishes a new reference map of immune cell differentiation across major immune organs and shows conserved features as well as species-specific differences in cell states and cell types compared with human hematopoiesis. Our results provide a resource to better understand the porcine immune system and immune-related diseases in pigs.
A study of alteration of preferences
Authors:   , Murphy Emily Elizabeth
Published: September 2024

Restricted and repetitive toy play is a common barrier reported by parents of children diagnosed with autism spectrum disorder. Individuals who engage in restricted and repetitive toy play tend to interact with a limited number of stimuli. This may limit opportunities for social interaction with peers through play, and potentially limit effectiveness of intervention due to a lack of items obtaining reinforcing value. Therefore, it is essential to evaluate ways to increase interaction with a variety of items. The purpose of the current study was a) to extend Hanley et al. 2003 research on the effects of paired reinforcement on interaction with a less preferred item and b) to assess if preference for less preferred items increased in a hierarchy of preferences, as a result of a pairing intervention. Initially, pre-conditioning multiple stimulus preference assessments were conducted to identify a hierarchy of preferences for seven items. In an attempt to increase interaction with less preferred items, a pairing intervention occurred in which a less preferred item was paired with a restricted interest item. A post-conditioning multiple stimulus preference assessment was conducted following the pairing intervention to determine if relative preference for less preferred items increased in a hierarchy of preferences. For participant one, average interaction with two of the three less preferred items increased, and two of the three less preferred items also increased in a hierarchy of preferences. Participant two displayed high levels of interaction with less preferred items during baseline, therefore intervention was not necessary. Participation in the study was discontinued for participant two due to a trend of high levels of interaction with all three less preferred items during baseline sessions.
Visualizing the impact of climate change at upper treeline across Rocky Mountain National Park, USA
Authors:   , Talbott-Swain Evan
Published: September 2024

Over the past 30 years, high-elevation forests of the Southern Rocky Mountain region (SRM) have been subject to heat-induced drought stress, or hotter drought, from sharply rising temperatures coupled with lower precipitation totals. Hotter drought across this region has caused widespread tree mortality from spruce beetle outbreaks and prevented successful seedling establishment within upper treeline ecotones. Recently, spruce beetle-induced mortality has also been documented across upper treeline environments where trees of all size classes have been affected, yet the spatial extent of this throughout the SRM remains unclear. This study aims to investigate whether upper treeline environments within Rocky Mountain National Park (RMNP) have been negatively impacted by hotter drought conditions, including spruce beetle-induced mortality. Repeat photography of photos taken in 1996 combined with remote sensing techniques is used to test three hypotheses: H1) Treeline advance will be widespread throughout RMNP, H2) Spruce beetle-induced mortality will be evident at upper treeline, and H3) Satellite imagery will show widespread decrease in Normalized Difference Vegetation Index (NDVI). Results from photo pairs show that treeline advance is not widespread throughout RMNP (33 percent, n=4), but spruce beetle-induced mortality at upper treeline is evident at a majority of repeat photo sites (75 percent, n=9) -- with these conditions present together in 25 percent (n=3) of the photo sites. Remote sensing results show that the majority of spruce beetle-induced mortality within RMNP and within the photo pairs occurred between 1999 and 2014, with little change occurring between 2014 and 2023. If the current trends of hotter drought continue, these findings suggest that upper treeline dynamics within RMNP will be impacted negatively from both climate and disturbance.
Mapping spatial disparity in news provision : a study of news deserts in rural Missouri
Authors:   , De Jesus Yves
Published: September 2024

[EMBARGOED UNTIL 05/01/2025] Despite extensive discussions on news deserts, a detailed examination of news provision within these areas remains limited. This study explores the scope of news provision and its spatial distribution in rural Missouri in the context of socio-economic factors. Our analysis of geo-tagged articles uncovers notable variations in news availability across rural cities, highlighting the intricate interplay between local demographics and the distribution of news provisions. Using geo-tagged articles as a lens, the study delves into the distribution patterns of news content across different bivariate classes, highlighting disparities in news provision based on areal characteristics. The analysis reveals spatial disparities in news coverage, influenced by median household income levels and diversity indices, with Jefferson City's unique socio-economic profile playing a significant role in shaping the distribution patterns. To measure the relationship between the bivariate classes and article count distribution, this study used Poisson regression analysis which provided statistically significant insights into the dynamics of news coverage distribution across bivariate classes. The analysis found that median household income generally correlates with increased news coverage, confirming existing literature. Additionally, the regression analysis highlighted the inverse relationship between diversity levels and news coverage within rural areas. Specifically, as diversity levels increase, there is a consistent decrease in the count of news articles, even when controlling for median household income. These results emphasize the substantial impact of increasing diversity on lower news coverage, highlighting an intricate interplay between socio-economic characteristics and media coverage. These findings demonstrate the importance of contextualizing the socio-economic dynamics of individual cities in interpreting the spatial distribution of news coverage, advocating for more inclusive and equitable news ecosystems within rural communities. By examining the spatial dynamics of news provision, it informs efforts to address gaps in media coverage and foster a more balanced media landscape in rural settings, offering valuable insights to the fields of local journalism, community dynamics, and media studies. This study contributes valuable insights to the fields of local journalism, community dynamics, and media studies, informing efforts to address gaps in media coverage and foster a more balanced media landscape in rural settings.
Discoidal fossils from the Ediacaran Wood Canyon formation, Nye County, NV, USA. Parasitic traces in bivalve, potamocorbula amurensis, from the Pearl River Delta, China
Authors:   , Edwards Emily Lauren Vincensa
Published: September 2024

[EMBARGOED UNTIL 05/01/2025] The late Ediacaran lower Wood Canyon Formation in Nye County, Nevada, has shown significant paleontological promise in recent years. Investigations in the Johnnie Range between the Amargosa Desert and Pahrump Valley have revealed a diverse assemblage of pyritized tubicolous fossils, with rare examples showing the preservation of bilaterian-grade throughguts, limited specimens of erniettomorphs, and abundant trace fossils approaching the Cambrian boundary. Here, we report both in-situ and float examples of discoidal structures from sandstones near the Stirling Quartzite-Wood Canyon boundary. These structures range in size from 3.5 to 47.5 mm in diameter and show the quintessential discoidal morphology of Aspidella, with visible concentric rings. Preserved in positive epirelief on the surfaces of desert-varnished coarse quartz sandstone beds, these specimens are generally found as isolated individuals--with the exception of multiple individuals found on smaller blocks of float. Similar discoidal structures have been reported from the region, including Nimbia from the Stirling Quartzite in Nye County, Nevada, and medusozoan strandings from the younger Zabriskie Quartzite in Death Valley, California. Like the other regional examples, the Johnnie discoidal fossils lack associated frond petalodia, which could argue against a holdfast interpretation like Aspidella, though its central boss may suggest otherwise. These discoidal fossils serve to bolster previous reports of the "Ediacara-type" preservation potential of soft-bodied organisms, like Ernietta, from this region.
The impact of cadmium and nickel on non-small cell lung cancer progression in vitro analysis of tumor progression
Authors:   , Otoboh Mary Omonyokan
Published: September 2024

[EMBARGOED UNTIL 05/01/2025] Lung cancer ranks among the primary contributors to cancer-related fatalities globally, affecting both men and women (Zhai et al., 2019). Lung cancer begins when healthy cells in the lungs undergo genetic mutations that disrupt their normal growth and death cycle (Fong et al., 2008). These mutated cells divide uncontrollably, forming tumors and disrupting lung function. In 2015, lung cancer diagnoses affected 221,200 individuals in the United States, and this disease claimed the lives of another 158,040 individuals (Townsend et al., 2017). Annually, approximately 230,000 individuals in the United States receive a diagnosis of lung cancer, leading to an estimated 135,000 deaths per year. The mortality rate linked to lung cancer now surpasses the combined fatalities from prostate, breast, brain, and colorectal cancer.
Female sex protects cerebral arteries from mitochondrial membrane potential depolarization and cell death induced by reactive oxygen species
Authors:   , Safa nan
Published: September 2024

[EMBARGOED UNTIL 05/01/2025] Stroke, Alzheimer's disease, and traumatic brain injury exacerbate the production of reactive oxygen species (ROS), leading to apoptosis in cerebral arteries. Notably, females exhibit greater resilience to vascular damage compared to males. Mitochondrial membrane potential ([delta][psi]m) depolarization is a pivotal event in apoptosis. However, under significant depolarization, ATP synthase can reverse direction, acting as a proton pump to mitigate [delta][psi]m depolarization. Additionally, alterations in the electron transport chain function may regulate [delta][psi]m. Furthermore, plasminogen activator inhibitor-1 (PAI-1), a serine protease inhibitor present in cerebral arteries, can promote cellular resilience, although its effects on mitochondrial function have not been defined. We hypothesize that during acute oxidative stress induced by exposure to H2O2, female protection of posterior cerebral arteries (PCAs) is facilitated by enhanced reverse ATP synthase activity, augmented mitochondrial electron transport function, and PAI-1 signaling. PCAs (80 [mu]m diameter) from male and female mice (age: 4-6 months) were isolated, cannulated, and pressurized to 90 cm H2O2 at 37 degreesC. Cell death was quantified with Hoechst 33342 (1 [mu]M, labels all nuclei) and propidium iodide (2 [mu]M, labels dead nuclei), and mitochondrial membrane potential ([delta][psi]m) at rest was evaluated by JC-1 and during depolarization with H2O2 with tetramethylrhodamine methyl ester (TMRM, 10 nM). H2O2 exposure (50 min) led to significantly (P<0.05) greater smooth muscle cell death in males compared to females (30 [plus or minus] 7.4 percent vs. [approx] 7 [plus or minus] 3 percent; n=8); there was a similar trend for endothelial cell death. The ATP synthase inhibitor oligomycin (2 [mu]M) greatly augmented apoptosis in PCAs from both males and females to [approx]80 percent and eliminated differences between sexes. Consistently, H2O2 evoked a more robust depolarization of [delta][psi]m in males vs. females and oligomycin enhanced [delta][psi]m depolarization to H2O2. Oxygen consumption rate (OCR) in females was significantly higher at baseline and when exposed to H2O2, while glycolysis was not altered by exposure to H2O2. In females, PAI-1 signaling contributes to resilience against acute oxidative stress damage, whereas males exhibit greater protection in the absence of PAI-1. We conclude that cerebral vessels from female mice possess greater resilience to H2O2 -induced apoptosis than males by limiting depolarization of [delta][psi]m and though sex differences in PAI-1 signaling.
Development of a mixed reality-based learning system with dynamic posture recognition for advancing ergonomics education
Authors:   , Yu Ching-Yun
Published: September 2024

[EMBARGOED UNTIL 05/01/2025] Proper lifting posture is one of the crucial topics in ergonomics education. Prolonged use of incorrect postures to carry heavy objects can lead to potential illnesses. The high rate of lumbar spine injuries among airport baggage handlers is an example of this. To enhance students' understanding, we designed a series of mixed reality modules enabling them to view the working process of airport baggage handlers and learn the biomechanical calculations related to the lifting task through Microsoft HoloLens 2. In the last module, students are required to perform the baggage handling movement with Xsens MVN Awinda motion capture sensors worn, and the system provides feedback based on what they performed. We recruited 20 undergraduate and graduate students to try out this learning system, including 10 males and 10 females. We evaluated this system from multiple aspects. In terms of system performance, there were no application errors or data loss during the experiments, which demonstrated the robustness of our system architecture and implementation. We obtained 39 recognition results with a recognition accuracy of 92.31 percent. We tested with different baseline movements on the recorded participants' motion data after the experiments but found that the accuracy was not improved. This suggests the limitations of our method in classifying similar movements with small differences. In terms of learning performance, the 20 participants watched lectures introducing proper lifting postures but 9 of them still chose to perform the baggage handling movement with a bad posture. This illustrates the limitations of the instructional effectiveness of listening to lectures and highlights the significance of hands-on learning. The participants' SUS scores demonstrate that our system usability is between okay and good. Since the participants' SCLS results indicate that our educational materials are helpful and their NASA TLX results indicate that the tasks we designed are easier to complete, we can improve the system usability by providing more interaction in the virtual environment or designing additional engaging learning activities. In conclusion, we developed a robust mixed reality-based learning system with dynamic posture recognition capabilities, which benefits ergonomics education. Our proposed framework is promising to be applied to more learning scenarios in which students follow specific instructions.
Environmental entrepreneurship : an external enablers perspective
Authors:   , Chen Yan
Published: September 2024

This dissertation focuses on explaining how and why entrepreneurs create new products, technologies, and markets to address environmental issues, and it consists of three studies on the topic of environmental entrepreneurship. The first study reviews the literature on environmental entrepreneurship to expose limitations and suggest directions for future research, and the second and third studies empirically address the limitations identified in the review. The review shows that recent studies have emphasized how various factors at different levels (e.g., individual, organizational-, and field- levels) can enable environmental entrepreneurship. Although extant research has provided new knowledge useful to scholars and managers, why and with what effects factors that are external to entrepreneurs influencing environmental entrepreneurship are less examined. Based on this review, in the first study, I suggest several directions for future research. In the second study, I address our limited understanding of why some conventional market incumbents enable environmental entrepreneurship, given that incumbents in conventional markets often respond negatively to the introduction of market alternatives. Building on the institutional logics perspective which suggests that incumbents in conventional markets vary in their flexibility to engage with new producers and thus enable those pioneers to enter nascent moral markets. In the third study, I focus on the vii demand side and examine how corporate buyers enable environmental entrepreneurship. Broader entrepreneurship research emphasizes the importance of market demand to entrepreneurial success, and studies on environmental entrepreneurship assume that institutional changes can lead to substantive demand changes. However, little research has explored how entrepreneurs interpret and respond to the opportunity signals sent by corporate buyers when they may or may not promise substantive demand change for ecofriendly products. This dissertation highlights the importance of overlooked external factor and their impact on environmental entrepreneurship.
Being and belonging in Victorian fiction, science, and medicine (1847-1897)
Authors:   , Fried Ariel
Published: September 2024

This dissertation examines the processes of individual subject formation and affective possibilities enacted by nonnormative, Othered, or otherwise "deviant" identity groups within the Victorian period. In chapters one and two, I argue that characteristics that seemed to define static identity categories were always subject to modularity and slippage, and that this rhetorical flexibility is sometimes reflected in the form and style of late-Victorian Gothic fictions. Chapter three then argues that a parallel blurring of distinctions can occur between medico-scientific and erotic genres, revealing how these disparate textual disciplines utilized similar structural and generic elements to achieve their rhetorical goals. While certain identity categories, constructions of subjectivity, and affective configurations became especially salient during this period, this dissertation argues that there were always other/Other ontological and affective possibilities being conceived and enacted. My reading and re-reading of Wuthering Heights in chapter four demonstrates the simultaneity of such possibilities. Triangulating this work in relation to cultural studies, history, queer studies, postcolonial studies, and critical race scholarship, this interdisciplinary dissertation thus argues that a multiplicity of viable ontologies populated mainstream and marginal literature alike during the Victorian period. Introducing a more multivocal view of these processes of identity construction offers a more nuanced understanding of the processes by which various subjectivities came to be and the contexts in which they could comfortably belong in the Victorian era.
Applications of deep learning in protein structure prediction : from complexes to intrinsically disordered proteins
Authors:   , Quadir Farhan
Published: September 2024

Proteins are essential biomolecules that play crucial roles in various biological processes within organisms. Their complex interactions and structures are fundamental to understanding cellular mechanisms and developing therapeutic strategies. However, traditional experimental methods like X-ray crystallography and NMR spectroscopy, despite their accuracy, are costly and time-consuming. This has prompted the exploration of computational models, particularly deep learning techniques, to predict protein structures, especially of complexes, more efficiently. This dissertation presents the development of DNCON2_Inter, DeepComplex, and Disformer. DNCON2_Inter predicts inter-chain contacts in homooligomers using deep convolutional neural networks, leveraging monomeric multiple sequence alignments (MSAs) and co-evolutionary features to enhance prediction accuracy. Using the predicted inter-chain contacts as distant restraints, quaternary structures can be produced. High precision of the inter-chain contacts leads to better quality models of the complexes. DeepComplex, a web server, extends this approach to predict inter-chain contacts and reconstruct quaternary structures of both homodimers and heterodimers. Finally, Disformer, was proposed in the prediction of intrinsically disordered proteins (IDP) which only gain structural and functional importance upon interaction with other molecules. Disformer employs a transformer-based dual graph approach combining Graph Attention Networks (GAT) and Graph Convolutional Neural Networks (GCN). It excels in predicting intrinsically disordered regions (IDRs) by leveraging both sequence-based and structure-based features for a comprehensive graph-based binary node classification. These contributions collectively enhance the predictive capabilities of protein structural analysis, providing new insights into protein interactions and disorder. This research not only advances our understanding of protein dynamics but also paves the way for future developments in the prediction and analysis of protein complexes and IDPs.
Tracing the threads of time : elucidating early evolutionary histories of arthropods and Ediacaran tubular fossils
Authors:   , Rosbach Stephanie A
Published: September 2024

In the extensive history of phylogenetic research, descriptions of morphological features have formed the backbone of our understanding of faunal relationships. Incorporating fossil data has proven crucial to this endeavor, offering a vital perspective on the relative evolution of diverse groups and their interconnected histories. However, as investigations extend further into the past, a sparse and inconsistent fossil record hinders understanding during the earliest periods of these evolutionary histories. This dissertation delves into the early evolutionary histories of arthropods and an enigmatic fossil assemblage from the terminal Ediacaran period, exploring the intricacies and challenges associated with unraveling the evolutionary stories of these two faunal groups. First, the description of a new arthropod, Papiliomaris kluessendorfae gen. et sp. nov., from the early Silurian, Waukesha Lagerstatte in the Brandon Bridge Formation, WI, provides valuable insights into this previously understudied temporal window for arthropod evolution. After which we move to examine the fossils of the terminal Ediacaran, which exist as an evolutionary preamble to the appearance of modern phyla during the Cambrian radiation. First, by describing a new cloudinomorph, Saarina corsettii sp. nov., from the southwestern US. Then by consolidating and reevaluating the current knowledge on late Ediacaran to early Cambrian tubular fossils from 170 journal articles in a comprehensive dataset on 99 tubular taxa from this time period. This dataset and subsequent statistical analysis serves as a call-to-arms for better standardization and rigorization of descriptive data collection for fossils in these early time periods.
Reliable, secure and energy-efficient AI hardware
Authors:   , Siddique Ayesha
Published: September 2024

The embedded AI hardware chips are being widely used in consumer devices and enterprise markets, such as high-end smartphones, tablets, smart speakers, wearables, autonomous vehicles, cameras, sensors, and other IoT (internet of things) devices. According to a recent report, the embedded AI hardware market is projected to grow from 920 million units in 2021 to 2,080 million units by 2026; it is expected to grow at a CAGR of 17.7 percent from 2021 to 2026. Unfortunately, these embedded AI devices are not only resource and power-constrained but, also vulnerable to reliability and security threats. To date, many energy-aware solutions such as approximate computing have been proposed to address the energy constraints of AI devices. Approximate computing-based deep learning algorithms relax the abstraction with near-perfect accuracy for energy efficiency in errorresilient applications. However, similar to traditional deep neural networks (DNNs), approximate deep neural networks (AxDNNs) and approximate spiking neural networks (AxSNNs) are vulnerable to many reliability threats, such as permanent and transient faults, and security threats, such as adversarial attacks. Considering that approximate computing is energy efficient technique but has an error-inducing nature, there is a pent-up need to exploit the vulnerabilities of AxDNNs against reliability and security threats. In this thesis, we aim to develop sustainable and dependable AI hardware that can analyze and mitigate reliability and security threats in energy-constrained AI hardware. We exploit emerging computing paradigms such as explainable artificial intelligence, neural architecture search, and moving target defense to guarantee reliability, security, and energy efficiency. My Ph.D. thesis is the first effort toward developing energy, reliability, and robustness-aware AI hardware for safety-critical applications.
Our journey on our own terms : the perceptions, experiences, and impact of U.S. black women studying abroad in Ghana
Authors:   , Smotherson Brittany
Published: September 2024

U.S. women of all races study abroad twice as much as men, yet literature did not begin examining women's gendered experiences until the 1990s. Race-based research seldom accounts for gender or ethnicity, with research focusing on "Black students" or "students of color." This Black feminist epistemology-informed critical ethnography examining the perceptions, experiences, and impact of seven U.S. Black women studying abroad for a semester at the University of Ghana contributes to these gaps by providing insight into what makes study abroad meaningful and systemically accessible for a "missing" population. By centering Black women's epistemology, this study critiques previous framings of Black women's experiences with study abroad as an act of activism within the ivory tower by the Black women in this study. It serves to improve intercultural engagement through study abroad program recruitment and implementation recommendations, and U.S. and Ghanaian higher education institutional relationship strengthening.
A Bayesian approach to discovery of latent dependency in point-referenced data
Authors:   , Wang Shuwan
Published: September 2024

In spatial statistics where data usually was observed as point-referenced, classical and parametric spatial models were assumed and used to describe real-world phenomena. This is generally due to the large number of spatial locations that the spatial models should cover. However, such classical methods usually rely strongly on unrealistic assumptions that real-world data do not follow. Due to this limitation, this dissertation focuses on developing statistics models that are more flexible and lead to a better understanding and explanation for the latent dependency in the real-world point-referenced data. This dissertation begins with a statistical model accounting for collective animal movement. The model highlights how to incorporate the ecological perspective into the hierarchical modeling structure, motivating the need of considering the underlying ecological structure to better understand the driving dynamics in the animal behaviors. Then, a statistical model is proposed to explain a real-world phenomenon, lightning strikes. Starting with an exploratory analysis, we found that the lightning strikes data do not follow classical assumptions in spatial models. Thus, a data-driven statistics approach is proposed, where the latent spatio-temporal dependency considered in the Log-Gaussian Cox process (LGCP) is not only non-stationary but also time-varying. The proposed method relaxes the standard assumption in spatial models (stationarity and isotropy) and thus is able to better account for the latent spatio-temporal dependency for the real-world data. Last, we propose using a novel neural-network method to overcome the computational burden in LGCP computations for posterior inference. The proposed neural-networkbased method provides faster and accurate parameter estimation as well as reliable uncertainty quantification for inference.