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Impact Of Natural Feed Additives And Monensin Sodium On Growth Performance In Feedlot Cattle, Thiago Lauro Maia Ribeiro

Electronic Theses and Dissertations

The objective of this dissertation was to investigate how phytogenic feed additives and a pulse feeding monensin sodium strategy would affect growth performance in the receiving and finishing feedlot phases. Three randomized complete block design feedlot experiments and one pooled analysis were conducted to determine the effects of the feed additives and management strategies used in newly weaned and finishing beef cattle. The objective of these experiments were 1) determine if a blend of capsicum oleoresin, clove essential oil, and garlic essential oil (CCG) influences cattle performance, sera metabolites or health outcomes during the feedlot receiving phase; 2) determine if …

In The Footsteps Of Moose: Using Non-Invasive Techniques To Identify Cause-Specific Calf Mortalities And Evaluate Moose (Alces Alces) Movements Pertaining To Mineral Lick Locations On Ancestral Lands Of The Grand Portage Ojibwe, Anna B. Weesies

Electronic Theses and Dissertations

Following a sharp moose (Alces alces; mooz, Anishinaabemowin, Ojibwe language) population decline in northeastern Minnesota during the early 2000s, the Grand Portage Band of Lake Superior Chippewa initiated a long-term moose collaring effort to assess survival and mortality causes. Moose are a culturally important species to the Band, with annual subsistence hunts held on the Reservation and adjacent 1854 Ceded Territory. Continued research guides culturally appropriate management decisions aimed at bolstering calf and adult survival, helping to preserve this moose in Minnesota today and for subsequent generations. Chapter 1 identifies cause-specific calf mortality rates in this multi-predator system using minimally …

Computation-Efficient Deep Learning Models For Computer Vision And Multimodal Vision-Language Tasks Via Network Pruning, Abir Mohammad Hadi

Electronic Theses and Dissertations

With the rapid evolution of deep neural networks over the past decade, the demand for efficient, generalizable, and task-adaptable models, especially in computer vision, has increased significantly. To address the computational and deployment challenges posed by overparameterized models, the research community has extensively explored model compression techniques such as pruning, quantization, and distillation. These approaches aim to enhance model efficiency without compromising performance, particularly when adapting to domain-specific tasks under limited resources. This dissertation investigates several underexplored yet critical aspects of task-aware deep learning model compression, spanning both convolutional and vision-language architectures. In the early part of this work, we …

Characterizing A Free-Roaming Cat Population To Predict Predation Of Threatened Species In An Island Ecosystem, Sarah Gheida

Electronic Theses and Dissertations

No abstract provided.

An Integrated Wetland Condition Index And Environmental Metric Framework For The Prairie Pothole Region, Mercedes L. Batalla

Electronic Theses and Dissertations

The USDA-NRCS Agricultural Conservation Easement Program (ACEP) assists landowners with protecting, restoring, and enhancing wetlands. Evaluating wetland conservation efforts is crucial for informing future management decisions. However, assessment frameworks vary across regions and among stakeholders. The Prairie Pothole Region is an ecologically unique landscape characterized by its abundance of wetlands that provide important ecosystem services. To evaluate wetlands enrolled in ACEP, I sampled forty-five semi-permanent wetlands in the Prairie Pothole Region from July – August 2023 and 2024. I selected and sampled twenty-six wetlands enrolled in ACEP. Nineteen additional wetlands not enrolled in ACEP were also sampled; these included nine …

The Formation And Degradation Of Carboxysomes During Heterocyst Development In Filamentous Cyanobacteria, Maxwell Anton Jakubiak

Electronic Theses and Dissertations

Photosynthetic carbon (CO2) fixation and solar-powered nitrogen (N2) fixation are foundational biochemical processes that introduce essential elements into the biosphere. While atmospheric dinitrogen gas (N2) is unusable to most organisms, diazotrophs utilize the nitrogenase enzyme to reduce N2 to ammonia. Because all known nitrogenases are highly susceptible to irreversible oxygen inactivation, N2 fixation is generally incompatible with oxygenic photosynthesis. However, several cyanobacteria are both photosynthetic and diazotrophic, balancing these opposing metabolisms by temporally or spatially separating the respective enzymes. Anabaena sp. PCC 7120 is a model multicellular cyanobacterium that grows in filaments of photosynthetic vegetative cells, which respond to nitrogen …

Leadership And Management In Action Program (L-Map) Supplement: Case Studies For Humanities And Social Sciences, Giovanna Bonadonna Ph.D., Kevin Kadowaki Ph.D., A. Patricia Mendoza Ph.D., Matthew Thompson Ph.D., Shirl Yang Ph.D.

Office of Postdoctoral Affairs

The Leadership and Management in Action Program (L-MAP) Workbook and Facilitator Guide are authored by Erin Heckler, Ph.D., Jessica A. Hutchins, Ph.D., Molly Grisham, M.A., and Elizabeth Luckman, Ph.D., M.B.A. The L-MAP Project was supported by a Burroughs Wellcome Fund (BWF) Career Guidance for Trainees grant to Washington University in St. Louis, 2019-2021 (co-principal investigators: Erin Heckler, Ph.D., and Jessica Hutchins, Ph.D.).

This Supplement does not (nor does it intend to) replace the L-MAP curriculum. The case studies in this document are designed to accompany the theory in the L-MAP curriculum applying it to discipline-specific situations in the humanities and …

Foster Care Students And Their Success In Academic Achievements In School, Kirsten Nassiff

Theses and Dissertations

This applied dissertation was designed to provide better training and resources for teachers working with students in foster care who have experienced multiple foster care placements, and to assist them in achieving academic success.

The researcher conducted semi-structured interviews with six educators and staff at an alternative school that has the highest number of students in foster care, located in this school district. Using Braun and Clarke’s six steps for Thematic Analysis, each transcript was coded with the assistance of MAXQDA, and themes were developed.

An analysis of the data revealed that educators and staff do not receive adequate communication …

The Experience Of The “Too Good To Go” Platform In Ireland And Its Implementation Potential In Mongolia., Jargal Erdenebaatar

Business ETD Collections

Food waste presents a considerable challenge to global environmental, economic, and social sustainability. This study investigates the viability of replicating the “Too Good To Go” (TGTG) platform in Mongolia, informed by the experiences of the TGTG platform in Ireland. Employing a mixed-methods approach, the research includes a secondary data analysis from Ireland, an online survey administered to 162 consumers in Ulaanbaatar, and semi-structured interviews with three entrepreneurs.

The findings suggest that the success of TGTG in Ireland can be attributed to several key factors: elevated consumer awareness, a supportive environment reinforced by government policies, and accessible technology. In contrast, the …

The Law Of Digital Resurrection, Victoria J. Haneman

Scholarly Works

The digital right to be dead has yet to be recognized as an important legal right. Artificial intelligence, augmented reality, and nanotechnology have progressed to the point that personal data can be used to resurrect the deceased in digital form with appearance, voice, emotion, and memory recreated to allow interaction with a digital app, chat bot, or avatar that may be indistinguishable from that with a living person. Users may now have a completely immersive experience simply by loading the personal data of the deceased into a neural network to create a chatbot that inherits features and idiosyncrasies of the …

Gambaran Kasus Gondongan Pada Sekolah Dasar Negeri 010 Makroman, Samarinda, Dwi Listiani, Ashri Budi Astuti, Jami'an Jami'an, Eko Prasetya Budi, Arif Sumarianto, Irfansyah Baharuddin Pakki

Jurnal Epidemiologi Kesehatan Indonesia

Mumps is an infectious disease caused by a viral infection, often attacking the salivary glands, especially the parotid glands. This disease is self-limiting and common in elementary school children. This study aims to describe the prevalence, symptoms, and impact of mumps in students of SD Negeri 010 Makroman, Samarinda, as well as evaluate risk factors and relevant prevention efforts. With a descriptive research design, data was obtained from a population of 307 students through secondary data from the Makroman Health Center and direct on-site investigations. An attack rate of 3.58% indicates a limited impact on at-risk populations, but it is …

Heterogeneous Clustering Of Multiomics Data For Breast Cancer Subgroup Classification And Detection, Joseph Pateras, Musaddiq Lodi, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

The rapid growth of diverse -omics datasets has made multiomics data integration crucial in cancer research. This study adapts the expectation–maximization routine for the joint latent variable modeling of multiomics patient profiles. By combining this approach with traditional biological feature selection methods, this study optimizes latent distribution, enabling efficient patient clustering from well-studied cancer types with reduced computational expense. The proposed optimization subroutines enhance survival analysis and improve runtime performance. This article presents a framework for distinguishing cancer subtypes and identifying potential biomarkers for breast cancer. Key insights into individual subtype expression and function were obtained through differentially expressed gene …

A Bibliographic And Topic Modeling Analysis Of The P-Adic Theory Literature Using Latent Dirichlet Allocation, Humberto Llinás, Ismael Gutiérrez, Anselmo Torresblanca, Javier De La Hoz, Brian Llinás

Computer Science Faculty Publications

P-adic analysis, introduced by Kurt Hensel in the early 20th century, has developed into a fundamental area of mathematical research with broad applications in number theory, algebraic geometry, and mathematical physics. This study aims to examine the thematic evolution and scholarly impact of p-adic research through a comprehensive topic modeling and bibliometric analysis. Using classical bibliometric techniques (e.g., performance analysis, co-authorship, and co-citation networks) combined with Latent Dirichlet Allocation (LDA), we analyzed 7388 peer-reviewed documents published between 1965 and 2024. The computational workflow was conducted using R (version 4.4.1) and VOSviewer (version 1.6.20), which enabled the identification of 20 distinct …

Deepssetracer 2.0: Improved Deep Learning Model Performance For Protein Secondary Structure Segmentation From Cryo-Em Maps, Bryan Hawickhorst, Thu Nguyen, Willy Wriggers, Jiangwen Sun, Jing He

Computer Science Faculty Publications

DeepSSETracer is a method for segmenting protein secondary structure from medium-resolution (5-10Å) cryogenic electron microscopy (cryo-EM) density maps. We conducted experiments and ablation studies to examine the effects of normalization methods, max-pooling, activation functions, and loss calculation region on DeepSSETracer. By combining multiple technical improvements, the performance of the new version, DeepSSETracer 2.0, was significantly enhanced compared to DeepSSETracer 1.1. On a set of 77 test cases, the weighted average per-voxel F1 score increased from 62.1% to 70.3% for helix detection, and from 47.8% to 62.5% for β-sheet detection. While each of the five modifications in the network enhanced the …

Benchmarking And Improving Foundation Model Dietary Estimates From Meal Images, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Accurate quantifying dietary contents, such as calories, proteins, carbohydrates, and fats, from an image of a meal plate is vital for managing diabetes. Recently, Large Multimodal Models (LMMs) have excelled in complex vision-language tasks due to their use of very large, highly diverse data. This study benchmarked the use of seven LMMs that include full and lightweight models of GPT, Gemini, and Llama for nutrition estimation based on Google's Nutrition5k dataset and our own phone-collected DonateAndLearn dataset. We analyzed the performance of LMMs and the RGB-D fusion model, in which the RGB-D model was specifically trained using Nutrition5k data. On …

Closing Racial And Ethnic Disparity Gaps In Pediatric Asthma Follow Up Care - A Quality Improvement Initiative, Ayodele Ayeko

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

Closing racial and ethnic disparity gaps in pediatric asthma follow up care - A quality improvement initiative

Ayodele Ayeko

Introduction/Background: Inadequate management of asthma significantly contributes to poor asthma control, poor quality of life (QOL), and high hospitalization rates among pediatric patients. The Global Initiative for Asthma (GINA) guidelines offer recommendations designed to enhance asthma control and improve the quality of life for those affected (2015), including recommendations for close follow up care. At WVU Medicine Children’s Hospital (WVUMCH), insufficient asthma control has been associated with lower clinic follow-up rates and an increase in hospitalization. Although educational initiatives …

An Edna Assessment Of The Diamond Darter (Crystallaria Cincotta) In Its Current And Historic Distribution Range, Cameron Moore Layne

Graduate Theses, Dissertations, and Problem Reports (ETD)

Environmental DNA (eDNA) can serve as a useful monitoring tool for cryptic and imperiled freshwater stream fishes. eDNA can fill knowledge gaps regarding species’ distribution, site abundance, and habitat usage. The last known stronghold of the Diamond Darter (Crystallaria cincotta) in the Elk River of West Virginia provides an excellent test case to examine the utility of this non-invasive method of surveying rare species. Diamond Darters are one of the most newly recognized freshwater fishes in North America and are among the most imperiled U.S. fishes, having been federally listed as endangered in 2013. The cryptic behavior and limitations of …

The Effect Of Sars-Cov-2 On Bacterial Diversity And Abundance In Community Wastewater, Joshua Lambert

Graduate Theses, Dissertations, and Problem Reports (ETD)

Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) enters human respiratory cells through binding of its spike (S) protein to the ACE-2 receptor, which is highly expressed in lung cells, but is also found in over 150 other cell types encompassing major organs including GI enterocytes. SARS-CoV-2 causes gut dysbiosis in infected individuals and patients with COVID-19 and also coincides with lower alpha diversity of the individual’s gut microbiome. Certain gut microbiome-associated genera are lower in abundance in COVID-19 patients including Lachnospira, Prevetolla, Roseburia, Bifidobacterium, and Faecalibacterium while genera such as Bacteroides, Enterococcus and Proteobacteria are increased during a SARS-CoV-2 …

Sleep, Endocannabinoid Signaling, And Cortical Processing In Mouse Models Of Autism Spectrum Disorder, Bryan Rodriguez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Sleep plays a crucial role in memory consolidation, neuronal plasticity, and cognitive function. Individuals with autism spectrum disorder (ASD) often experience sleep disturbances, which are positively correlated with symptom severity. However, on the surface, sleep architecture is remarkably normal under baseline conditions in many rodent models of ASD. The goals if this dissertation were to investigate whether regulation of sleep, biochemical signaling during sleep, and downstream consequences of sleep on behavior are altered in two mouse models of ASD. In Aim 1, we tested the hypothesis that sleep phenotypes emerge in ASD models under conditions of high sleep pressure. We …

Quantitative Assessment Of Knee Joint Stability Using Inertial Measurement Units In Patients With Acl Reconstruction Performing Single-Legged Hopping Tasks, Haley Hartman-Mongold

Graduate Theses, Dissertations, and Problem Reports (ETD)

Purpose: The purpose of this study was to examine proximal tibial IMU accelerations between the involved limb and uninvolved limbs of individuals who have undergone ACL reconstruction performing the single-leg hop test battery and to correlate these results to deficits in quadriceps strength and distance hopped. Methods: Thirty-four subjects (19 male, 15 female; age = 20.5 ± 6.7 years; mass = 76.4 ± 15.8 kg; height = 1.74 ± .08 cm) who have undergone unilateral ACL reconstruction were recruited for this study. An isokinetic dynamometer was used to assess the knee extension peak torque on the involved and uninvolved limbs. …

The Stochastic Occupation Kernel (Sock) Method For Learning Stochastic Differential Equations, M. L. Wells, Kamel Lahouel, Bruno Jedynak

Mathematics and Statistics Faculty Publications and Presentations

We present a novel kernel-based method for learning multivariate stochastic differential equations (SDEs). The method follows a two-step procedure: we first estimate the drift term function, then the (matrix-valued) diffusion function given the drift. Occupation kernels are integral functionals on a reproducing kernel Hilbert space (RKHS) that aggregate information over a trajectory. Our approach leverages vector-valued occupation kernels for estimating the drift component of the stochastic process. For diffusion estimation, we extend this framework by introducing operator-valued occupation kernels, enabling the estimation of an auxiliary matrix-valued function as a positive semi-definite operator, from which we readily derive the diffusion estimate. …

Mock: An Algorithm For Learning Nonparametric Differential Equations Via Multivariate Occupation Kernel Functions, Victoria A. Rielly, Kamel Lahouel, Ethan Lew, Nicholas Fisher, Vicky Geneva Haney, Michael Wells, Bruno M. Jedynak

Mathematics and Statistics Faculty Publications and Presentations

Learning a nonparametric system of ordinary differential equations from trajectories in a -dimensional state space requires learning functions of variables. Explicit formulations often scale quadratically in unless additional knowledge about system properties, such as sparsity and symmetries, is available. In this work, we propose a linear approach, the multivariate occupation kernel method (MOCK), using the implicit formulation provided by vector-valued reproducing kernel Hilbert spaces. The solution for the vector field relies on multivariate occupation kernel functions associated with the trajectories and scales linearly with the dimension of the state space. We validate through experiments on a variety of simulated and …

Optical Coherence Tomography Harmonization With Anatomy-Guided Latent Metric Schrödinger Bridges, Shuwen Wei, Blake E. Dewey, Samuel W. Remedios, Bruno Jedynak, Shimeng Wang, Peter Calabresi, Shiv Saidha, Aaron Carass, Multiple Additional Authors

Mathematics and Statistics Faculty Publications and Presentations

Medical image harmonization aims to reduce the differences in appearance caused by scanner hardware variations to allow for consistent and reliable comparisons across devices. Harmonization based on paired images from different devices has limited applicability in real-world clinical settings. On the other hand, unpaired harmonization typically does not guarantee anatomy consistency, which is problematic because anatomical information preservation is paramount. The Schrödinger bridge framework has achieved state-of-the-art style transfer performance with natural images by matching distributions of unpaired images, but this approach can also introduce anatomy changes when applied to medical images. We show that such changes occur because the …

Recent Changes In Discretionary Denials Of Drug Patent Challenges, S. Sean Tu, Arti K. Rai, Aaron S. Kesselheim

Faculty Scholarship

Recent policy shifts at the U.S. Patent and Trademark Office (USPTO) have sharply limited the use of two administrative pathways for patent reviews, inter partes review (IPR) and post-grant review (PGR). Congress created these administrative pathways to provide a faster and less costly way to challenge weak patents. Recently, the USPTO has expanded the use of “discretionary denials,” invoking a new “settled expectations” rationale that blocks IPR petitions for patents more than about six years old. From May to September 2025, 60% of 506 requests for discretionary denial were granted, triple historical levels, including one-third involving drug patents. These changes …

The Reliability Response To Patent Law’S Ai Challenges, Arti K. Rai

Faculty Scholarship

Pervasive AI use adds newfound importance to longstanding debates over patent timing and reliability. Patent claims on speculative ideas generated by AI, or even the infusion of speculative AI-generated ideas into the public domain, may defeat patent incentives for more careful research. Although challenges that AI use poses for patent validity requirements like human inventorship and nonobviousness have received more attention, reliability is equally important.

Indeed, as this Article argues, the issues are linked. If requirements for inventorship and nonobviousness were adjusted to emphasize reliability, a human role could be preserved, and AI use would not necessarily threaten patents. Currently, …

Multi-Risk Governance Of Solar Radiation Modification, Jonathan B. Wiener, Tyler Felgenhauer, Mark E. Borsuk

Faculty Scholarship

Solar radiation modification (SRM) presents important challenges to risk regulation and governance, arising from the array of multiple risks that SRM may influence. SRM would not simply reverse climate change, but could pose further ancillary impacts, depending on the method of SRM, such as stratospheric aerosol injection (SAI), marine cloud brightening (MCB), or a space-based planetary sunshade system (PSS). We identify multiple risks that SRM may influence, both biophysical and sociopolitical, to be compared to the multiple risks that may be affected by greenhouse gas (GHG) mitigation and climate adaptation. This multi-risk framework helps analysts and decision makers identify, evaluate, …

Understanding The Prevalence Of Γ-Hydroxybutyric Acid In Hair For Clinical And Forensic Applications, Collin J. Kustera

Graduate Theses, Dissertations, and Problem Reports (ETD)

Sexual assault affects over 400,000 Americans annually, including 13% of college students, yet only 2.5% of assailants face incarceration. This disparity stems from significant challenges in evidence collection, particularly in drug-facilitated crimes (DFCs). Victims often delay reporting due to fear, self-blame, or unawareness of the assault which is common in cases involving substances like γ-hydroxybutyric acid (GHB). Current forensic standards rely on blood and urine, which offer detection windows of just 48 and 120 hours, respectively. These short timeframes frequently fail to capture critical toxicological evidence, leaving investigators with only victim testimony, which the judicial system struggles to act upon …

Loss Of Endogenous Circadian Clock Function In Mice Alters Respiratory Cycle Timing In A Time Of Day- And Sex-Specific Manner, Aaron A. Jones, Deanna M. Arble

Biological Sciences Faculty Research and Publications

Resting breathing and ventilatory chemoreflexes are regulated in a 24-hr manner by the endogenous circadian clock. However, it is unclear how circadian biology influences different phases of the breath-to-breath respiratory cycle which are predominantly controlled by pontomedullary regions of the brainstem. Here, we performed whole-body plethysmography during quiet wakefulness in young adult male and female mice lacking the core clock gene Brain and Muscle Arnt-like 1 (BMAL1) to determine the extent to which the molecular clock affects respiratory cycle timing and ventilatory airflow mechanics. Breath waveform analysis revealed that male BMAL1 knockout (KO) mice exhibit time of day-specific differences in …

Long-Term Increases In Wing Length Occur Independently Of Changes In Climate And Climate-Driven Shifts In Body Size, Tiffany Dias, Nathan P. Lemoine, Scott W. Yanco, Marketa Zimova, Rachael A. Bay, Brian C. Weeks

Biological Sciences Faculty Research and Publications

Recent widespread reductions in body size across species have been linked to increasing temperatures; simultaneous increases in wing length relative to body size have been broadly observed but remain unexplained. Size and shape may change independently of one another, or these morphological shifts may be linked, with body size mediating or directly driving the degree to which shape changes. Using hierarchical Bayesian models and a morphological time series of 27 366 specimens from five North American migratory passerine bird species, we tested the roles that climate and body size have played in shifting wing length allometry over four decades. We …

Diabetes Potentiates The Emergence And Expansion Of Antibiotic Resistance, John C. Shook, Benjamin P. Darwitz, Kaleb J. Tyson, Amanda Z. Velez, Sophia K. Bridwell, Joshua B. Parsons, Sarah E. Rowe, Christopher Marshall, Brian P. Conlon, Lance R. Thurlow

Biological Sciences Faculty Research and Publications

Individuals with diabetes mellitus frequently develop severe skin and soft tissue infections (SSTIs) that are recalcitrant to antibiotic treatment. We examined how diabetes affects the emergence of antibiotic resistance in a Staphylococcus aureus SSTI. We determined that S. aureus evolves antibiotic resistance rapidly in diabetic mice, while resistance did not occur in nondiabetic mice over the course of infection. Diabetes-associated immune cell dysfunction plays a minor role in the emergence of resistance, while hyperglycemia plays a dominant role facilitating the expansion and takeover of resistant mutants in diabetic infections. Furthermore, vancomycin intermediate resistant isolates display a pronounced fitness defect in …