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Articles 14041 - 14070 of 291657

Full-Text Articles in Physical Sciences and Mathematics

Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-Based Benchmark, Han Zhang, Zixiang Meng, Meng Luo, Hong Han, Lizi Liao, Erik Cambria, Hao Fei May 2025

Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-Based Benchmark, Han Zhang, Zixiang Meng, Meng Luo, Hong Han, Lizi Liao, Erik Cambria, Hao Fei

Research Collection School Of Computing and Information Systems

Empathetic Response Generation (ERG) is one of the key tasks of the affective computing area, which aims to produce emotionally nuanced and compassionate responses to user's queries. However, existing ERG research is predominantly confined to the singleton text modality, limiting its effectiveness since human emotions are inherently conveyed through multiple modalities. To combat this, we introduce an avatar-based Multimodal ERG (MERG) task, entailing rich text, speech, and facial vision information. We first present a large-scale high-quality benchmark dataset, AvaMERG, which extends traditional text ERG by incorporating authentic human speech audio and dynamic talking-face avatar videos, encompassing a diverse range of …

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On Learning Informative Trajectory Embeddings For Imitation, Classification And Regression, Zichang Ge, Changyu Chen, Arunesh Sinha, Pradeep Varakantham May 2025

On Learning Informative Trajectory Embeddings For Imitation, Classification And Regression, Zichang Ge, Changyu Chen, Arunesh Sinha, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

In real-world sequential decision making tasks like autonomousdriving, robotics, and healthcare, learning from observed state-action trajectories is critical for tasks like imitation, classification,and clustering. For example, self-driving cars must replicate humandriving behaviors, while robots and healthcare systems benefitfrom modeling decision sequences, whether or not they come fromexpert data. Existing trajectory encoding methods often focus onspecific tasks or rely on reward signals, limiting their ability togeneralize across domains and tasks.Inspired by the success of embedding models like CLIP andBERT in static domains, we propose a novel method for embeddingstate-action trajectories into a latent space that captures the skillsand competencies in the …

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Eduqate: Generating Adaptive Curricula Through Rmabs In Education Settings, Sidney Tio, Dexun Li, Pradeep Varakantham May 2025

Eduqate: Generating Adaptive Curricula Through Rmabs In Education Settings, Sidney Tio, Dexun Li, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

There has been significant interest in the development of personalized and adaptive educational tools that cater to a student's individual learning progress. A crucial aspect in developing such tools is in exploring how mastery can be achieved across a diverse yet related range of content in an efficient manner. While Reinforcement Learning and Multi-armed Bandits have shown promise in educational settings, existing works often assume the independence of learning content, neglecting the prevalent interdependencies between such content. In response, we introduce Education Network Restless Multi-armed Bandits (EdNetRMABs), utilizing a network to represent the relationships between interdependent arms. Subsequently, we propose …

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Shipnavisim: Data-Driven Simulation For Real-World Maritime Navigation, Quang Anh Pham, Janaka Chathuranga Brahmanage, Akshat Kumar May 2025

Shipnavisim: Data-Driven Simulation For Real-World Maritime Navigation, Quang Anh Pham, Janaka Chathuranga Brahmanage, Akshat Kumar

Research Collection School Of Computing and Information Systems

Maritime traffic management in busy ports faces growing challenges due to increased vessel traffic and complex waterway interactions. Strategies such as e-navigation by the International Maritime Organization aim to enhance navigation safety through traffic digitization. Maritime traffic simulation is essential for these systems, offering a virtual environment to model, analyze, and optimize traffic flows. Unlike road traffic, there are few simulators for maritime traffic, and they often lack realism and multi-ship interactions. In this paper, we (a) present ShipNaviSim, a data-driven maritime traffic simulator that utilizes a large-scale dataset over 2 years and electronic navigation charts to model vessel movements …

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Hierarchical Frameworks For Scaling-Up Multi-Agent Coordination, Minghong Geng May 2025

Hierarchical Frameworks For Scaling-Up Multi-Agent Coordination, Minghong Geng

Research Collection School Of Computing and Information Systems

Multi-agent reinforcement learning has emerged as a powerful framework for developing collaborative behaviors in autonomous systems. However, existing MARL methods often struggle with scalability in terms of both the number of agents and decision-making horizons. My research focuses on developing hierarchicalapproaches to scale up MARL systems through two complementary directions: structural scaling by increasing the number of coordinated agents and temporal scaling by extending planning horizons. My initial work introduced HiSOMA, a hierarchical framework integrating self-organizing neural networks with MARL forlong-horizon planning, and MOSMAC, a benchmark for evaluating MARL methods on multi-objective MARL scenarios. Building on these foundations, my recent …

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Seaexam And Seabench: Benchmarking Llms With Local Multilingual Questions In Southeast Asia, Chaoqun Liu, Wenxuan Zhang, Jiahao Ying, Mahani Aljunied, Anh Tuan Luu, Lidong Bing May 2025

Seaexam And Seabench: Benchmarking Llms With Local Multilingual Questions In Southeast Asia, Chaoqun Liu, Wenxuan Zhang, Jiahao Ying, Mahani Aljunied, Anh Tuan Luu, Lidong Bing

Research Collection School Of Computing and Information Systems

This study introduces two novel benchmarks, SeaExam and SeaBench, designed to evalu ate the capabilities of Large Language Models (LLMs) in Southeast Asian (SEA) application scenarios. Unlike existing multilingual datasets primarily derived from English translations, these benchmarks are constructed based on real world scenarios from SEA regions. SeaExam draws from regional educational exams to form a comprehensive dataset that encompasses sub jects such as local history and literature. In contrast, SeaBench is crafted around multi turn, open-ended tasks that reflect daily inter actions within SEA communities. Our evalua tions demonstrate that SeaExam and SeaBench more effectively discern LLM performance on …

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Rotation-Adaptive Point Cloud Domain Generalization Via Intricate Orientation Learning, Bangzhen Liu, Chenxi Zheng, Xuemiao Xu, Cheng Xu, Huaidong Zhang, Shengfeng He May 2025

Rotation-Adaptive Point Cloud Domain Generalization Via Intricate Orientation Learning, Bangzhen Liu, Chenxi Zheng, Xuemiao Xu, Cheng Xu, Huaidong Zhang, Shengfeng He

Research Collection School Of Computing and Information Systems

The vulnerability of 3D point cloud analysis to unpredictable rotations poses an open yet challenging problem: orientation-aware 3D domain generalization. Cross-domain robustness and adaptability of 3D representations are crucial but not easily achieved through rotation augmentation. Motivated by the inherent advantages of intricate orientations in enhancing generalizability, we propose an innovative rotation-adaptive domain generalization framework for 3D point cloud analysis. Our approach aims to alleviate orientational shifts by leveraging intricate samples in an iterative learning process. Specifically, we identify the most challenging rotation for each point cloud and construct an intricate orientation set by optimizing intricate orientations. Subsequently, we employ …

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Few-Shot Learning On Graphs: From Meta-Learning To Llm-Empowered Pre-Training And Beyond, Yuan Fang, Yuxia Wu, Xingtong Yu, Shirui Pan May 2025

Few-Shot Learning On Graphs: From Meta-Learning To Llm-Empowered Pre-Training And Beyond, Yuan Fang, Yuxia Wu, Xingtong Yu, Shirui Pan

Research Collection School Of Computing and Information Systems

Graph representation learning has become central to many graph-based tasks, driving advancements in various domains such as web search, recommendation systems, and social network analysis. Traditionally, these methods rely on end-to-end supervised learning paradigms that require abundant labeled data, which can be costly and difficult to obtain. To address this limitation, few-shot learning on graphs has emerged as a promising approach, allowing models to generalize with minimal supervision and overcome data scarcity in real-world applications. This tutorial offers an in-depth exploration of recent advancements in few-shot learning for graphs, providing a comparative analysis of state-of-the-art methods and identifying future research …

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“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono May 2025

“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono

Research Collection School Of Computing and Information Systems

Dark environment challenges low-vision (LV) individuals to engage in running by following sighted guide—a Caller-style guided running—due to insufficient illumination, because it prevents them from using their residual vision to follow the guide and be aware about their environment. We design, develop, and evaluate RunSight, an augmented reality (AR)-based assistive tool to support LV individuals to run at night. RunSight combines see-through HMD and image processing to enhance one’s visual awareness of the surrounding environment (e.g., potential hazard) and visualize the guide’s position with AR-based visualization. To demonstrate RunSight’s efficacy, we conducted a user study with 8 LV runners. The …

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Worldcuisines: A Massive-Scale Benchmark For Multilingual And Multicultural Visual Question Answering On Global Cuisines, Genta Indra Winata, Et. Al May 2025

Worldcuisines: A Massive-Scale Benchmark For Multilingual And Multicultural Visual Question Answering On Global Cuisines, Genta Indra Winata, Et. Al

Research Collection School Of Computing and Information Systems

Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts. To evaluate their understanding of such knowledge, we introduce WorldCuisines, a massive-scale benchmark for multilingual and multicultural, visually grounded language understanding. This benchmark includes a visual question answering (VQA) dataset with text-image pairs across 30 languages and dialects, spanning 9 language families and featuring over 1 million data points, making it the largest multicultural VQA benchmark to date. It includes tasks for identifying dish names and their origins. We provide evaluation datasets in two sizes (12k and 60k instances) alongside …

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Enriching Automatic Test Case Generation By Extracting Relevant Test Inputs From Bug Reports, Wendkuuni C. Ouedraogo, Laura Plein, Kader Kabore, Andrew Habib, Jacques Klein, David Lo, Tegawende F. Bissyande May 2025

Enriching Automatic Test Case Generation By Extracting Relevant Test Inputs From Bug Reports, Wendkuuni C. Ouedraogo, Laura Plein, Kader Kabore, Andrew Habib, Jacques Klein, David Lo, Tegawende F. Bissyande

Research Collection School Of Computing and Information Systems

The quality of software is closely tied to the effectiveness of the tests it undergoes. Manual test writing, though crucial for bug detection, is time-consuming, which has driven significant research into automated test case generation. However, current methods often struggle to generate relevant inputs, limiting the effectiveness of the tests produced. To address this, we introduce BRMiner, a novel approach that leverages Large Language Models (LLMs) in combination with traditional techniques to extract relevant inputs from bug reports, thereby enhancing automated test generation tools. In this study, we evaluate BRMiner using the Defects4J benchmark and test generation tools such as …

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Relation Prediction In Knowledge Graphs: A Self-Organizing Neural Network Approach, Budhitama Subagdja, Shanthoshigaa D, Ah-Hwee Tan May 2025

Relation Prediction In Knowledge Graphs: A Self-Organizing Neural Network Approach, Budhitama Subagdja, Shanthoshigaa D, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Knowledge graphs (KGs) in specialized domains frequently suffer from incomplete information. While current relation prediction methods for KG completion typically rely on neural network-based representation learning, we present KG2ART---a novel self-organizing neural network that employs a fundamentally different approach. Instead of learning distributed representations, KG2ART encodes relation triples of knowledge graphs explicitly and performs parallel inference over the graph structure through bidirectional interactions between bottom-up activations and top-down pattern matching. Our comprehensive evaluation across five diverse KGs (Nations, UMLS, Kinship, CoDEx-M, and a jet engine technical KG) demonstrates that KG2ART consistently outperforms state-of-the-art baselines (TuckER, ComplEX, RESCAL, ConvE, CompGCN) in …

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Disambiguart: A Neural-Based Inference Model For Knowledge Graph Disambiguation, Budhitama Subagdja, D. Shanthoshigaa, Ah-Hwee Tan May 2025

Disambiguart: A Neural-Based Inference Model For Knowledge Graph Disambiguation, Budhitama Subagdja, D. Shanthoshigaa, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

One main challenge in constructing a knowledge graph (KG) is to deal with ambiguity. Specifically, an entity in the graph can be assigned with multiple meanings while two or more entities considered to have different meanings may actually be the same. Assigning an entity with the correct meaning may involve re-evaluation of its relevant contexts. This costly operation typically involves searching for other similar entities within the KG such that the context can be determined. In this paper, a new model called DisambiguART is proposed leveraging multi-channel matching and inference in a self-organizing neural network for sense disambiguation in knowledge …

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Creating Talking Points For Client Advisers At Banks To Promote Sustainable Investing, Wewe Zi Yi, Pradeep Varakantham, Alan Megargel May 2025

Creating Talking Points For Client Advisers At Banks To Promote Sustainable Investing, Wewe Zi Yi, Pradeep Varakantham, Alan Megargel

Research Collection School Of Computing and Information Systems

Environmental, social and governance (ESG) factors have become key nonfinancial factors for investors to evaluate companies with respect to understanding material risks and growth opportunities. While not mandatory, companies are providing ESG reports that outline progress in different ESG metrics (six broad metrics and 15 specific ones). Client advisers (CAs) read these reports to identify key metrics of interest to investors. Given the number of companies and investment products, however, it is not feasible for CAs to read all the reports, which can sometimes run into tens or hundreds of pages). The authors have developed multiple frameworks building on leading …

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Prompting An Embodied Ai Agent: How Embodiment And Multimodal Signaling Affects Prompting Behaviour, Tianyi Zhang, Colin Au Yeung, Emily Aurelia, Yuki Onishi, Neil Chulpongsatorn, Jiannan Li, Anthony Tang May 2025

Prompting An Embodied Ai Agent: How Embodiment And Multimodal Signaling Affects Prompting Behaviour, Tianyi Zhang, Colin Au Yeung, Emily Aurelia, Yuki Onishi, Neil Chulpongsatorn, Jiannan Li, Anthony Tang

Research Collection School Of Computing and Information Systems

Current voice agents wait for a user to complete their verbal instruction before responding; yet, this is misaligned with how humans engage in everyday conversational interaction, where interlocutors use multimodal signaling (e.g. nodding, grunting, or looking at referred to objects) to ensure conversational grounding. We designed an embodied VR agent that exhibits multimodal signaling behaviors in response to situated prompts, by turning its head, or by visually highlighting objects being discussed or referred to. We explore how people prompt this agent to design and manipulate the objects in a VR scene. Through a Wizard of Oz study, we found that …

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Integrating Path Selection For Symbolic Execution And Variable Selection For Constraint Solving, Shunkai Zhu, Jun Sun, Jingyi Wang, Zhenbang Chen, Peng Cheng May 2025

Integrating Path Selection For Symbolic Execution And Variable Selection For Constraint Solving, Shunkai Zhu, Jun Sun, Jingyi Wang, Zhenbang Chen, Peng Cheng

Research Collection School Of Computing and Information Systems

Symbolic execution is a powerful technique that can accurately synthesize program inputs for program testing through constraint solving. Applying symbolic execution effectively means that we must solve two searching problems efficiently. One is to search through the many program paths and the other is, given a particular path condition, to search through the numerous variable assignments to identify one satisfying solution. With few exceptions, existing symbolic execution engines treat constraint solvers as black boxes. As a result, the two searches are completely separated, which results in much redundancy (i.e., the same variable assignments may be tried for solving many program …

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Scenario-Driven And Context-Aware Automated Accessibility Testing For Android Apps, Yuxin Zhang, Sen Chen, Xiaofei Xie, Zibo Liu, Lingling Fan May 2025

Scenario-Driven And Context-Aware Automated Accessibility Testing For Android Apps, Yuxin Zhang, Sen Chen, Xiaofei Xie, Zibo Liu, Lingling Fan

Research Collection School Of Computing and Information Systems

Mobile accessibility is increasingly important nowadays as it enables people with disabilities to use mobile applications to perform daily tasks. Ensuring mobile accessibility not only benefits those with disabilities but also enhances the user experience for all users, making applications more intuitive and user-friendly. Although numerous tools are available for testing and detecting accessibility issues in Android applications, a large number of false negatives and false positives persist due to limitations in the existing approaches, i.e., low coverage of UI scenarios and lack of consideration of runtime context. To address these problems, in this paper, we propose a scenario-driven exploration …

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The Food Truck: A Multi-Product Newsvendor With Trans-Shipment Cost, Samuel Ajibola May 2025

The Food Truck: A Multi-Product Newsvendor With Trans-Shipment Cost, Samuel Ajibola

Electronic Theses and Dissertations

The Newsvendor Problem is a key model in supply chain management that focuses on determining the optimal order quantity to minimize costs under uncertain demand. This thesis introduces the Food Truck Problem, an extension of the Newsvendor model that incorporates nonlinear transshipment costs for inventory transportation. In this context, a Food Truck must determine the optimal stock levels for multiple products while minimizing costs related to stock shortages, excess inventory, and transportation. Unlike traditional Newsvendor models, our approach explicitly considers a quadratic transshipment cost, which necessitates the use of Lagrangian duality and Karush-Kuhn-Tucker (KKT) conditions for analysis. Moreover, we apply …

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On The Challenges Posed By Non-Machian Solutions To Relationalism In General Relativity, Zachary Matthew Zito May 2025

On The Challenges Posed By Non-Machian Solutions To Relationalism In General Relativity, Zachary Matthew Zito

Undergraduate Honors Capstone Projects

The relationship between Mach’s Principle and solutions to Einstein’s field equations is examined, with special attention to Friedmann-Lematre-Robertson-Walker (FLRW) cosmology. Mach’s Principle is outlined, and the extent to which general relativity fulfills Machs vision is assessed. It is argued that several important solutions to Einsteins equations, particularly the FLRW cosmological models, embody key Machian features. In order to elucidate the FLRW cosmological model, the associated energy-momentum tensor for a perfect fluid under the assumptions of large-scale homogeneity and isotropy is derived and used to obtain the Friedmann equations that govern cosmic expansion. It is shown that FLRW cosmology can be …

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Reevaluating The Drumian Carbon Isotope Excursion (Dice) In Western-Central Utah, Michelle M. Norman May 2025

Reevaluating The Drumian Carbon Isotope Excursion (Dice) In Western-Central Utah, Michelle M. Norman

Undergraduate Honors Capstone Projects

The Drumian Stage of the Cambrian Period is defined by the First Appearance Datum (FAD) of the cosmopolitan trilobite Ptychagnostus atavus in 504.5 Ma strata deposited on the slope and shelf of the Laurentia margin. The Drumian Global Stratotype Section and Point (GSSP), showing the best preserved example of P. atavus compared to global outcrops, is defined in the Drum Mountains of west-central Utah. Due to the inconsistent nature of fossil preservation, researchers have sought secondary proxies to identify Drumian-aged strata in the absence of age-diagnostic fauna. One key proxy is the Drumian Carbon Isotope Excursion (DICE), an ~-2.5‰ carbon …

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To Bee Or Not To Bee: Investigating Pesticide Behavior Inside And Outside Of Semi-Field Cages, Mallory Bingham May 2025

To Bee Or Not To Bee: Investigating Pesticide Behavior Inside And Outside Of Semi-Field Cages, Mallory Bingham

Undergraduate Honors Capstone Projects

Bees play an important role in ecosystems and food production through pollination. One such bee, the alfalfa leaf cutting bee (ALCB) is a very efficient pollinator and is essential in alfalfa seed production. However, bees face increasing harm, most notably due to the deleterious effect of pesticides used in agriculture, and much research is dedicated to investigating the extent of effects that pesticides have on different bee populations. One common tool used to study the effects of pesticide exposure on bees is semi-field cages. These cages have some key advantages, such as restricting bee foraging to plots sprayed with pesticides …

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Data Science For Engineers, Heidi Moulton May 2025

Data Science For Engineers, Heidi Moulton

Undergraduate Honors Capstone Projects

Undergraduate research is a core pillar of Utah State University’s College of Engineering. Many students become involved with research during their Junior and Senior years and begin to generate various forms of data. Most students, however, have received little formal education on how to process data, and there are currently no readily available resources within the College of Engineering. As a Mechanical Engineering and Data Science double major, I found the data processing techniques I learned in my Data Science courses invaluable as an undergraduate researcher, and now as a Mechanical Engineer at Apogee Instruments, I frequently draw upon these …

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Investigation Into The Effectiveness Of G-C3n4 For The Degradation Of Indigo Dye In Aqueous Solution Via Electrocatalysis, Rolando R. Barron Jr May 2025

Investigation Into The Effectiveness Of G-C3n4 For The Degradation Of Indigo Dye In Aqueous Solution Via Electrocatalysis, Rolando R. Barron Jr

Theses and Dissertations

Indigo dye (IUPAC 2-(3-hydroxy-1H-indol-2-yl)indol-3-one) is one of the most used dyes in the textile industry worldwide with more than 40,000 tons produced each year. It can elicit adverse physiological responses in humans including vomiting, diarrhea, and other gastrointestinal conditions, and it is toxic in large amounts. There is also evidence to suggest that indigo is a teratogen and genotoxic in aquatic life. Environmentally, the enormous amount of indigo used in the textile industry has caused rivers and waterways to run blue as well as severely impacting aquatic and plant ecosystems. The chemicals used in its synthesis are also …

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Fairness And Robustness In Decentralized Federated Learning, Kaichuang Zhang May 2025

Fairness And Robustness In Decentralized Federated Learning, Kaichuang Zhang

Theses and Dissertations

Federated Learning (FL) has emerged as a privacy-preserving paradigm that allows multiple clients to collaboratively train a machine learning model without sharing raw data. However, traditional FL relies on a central server for model aggregation, which introduces a single point of failure and makes the system vulnerable to server-side attacks or breakdowns. To address these limitations, Decentralized Federated Learning (DFL) has been proposed, eliminating the need for a central server and enhancing system resilience. Despite these advantages, DFL faces critical challenges related to fairness and robustness, especially under non-i.i.d. data distributions and adversarial conditions. In this thesis, we propose a …

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Climate Change And The Field Of Farm Labor In The Lower Rio Grande Valley, Texas, Cody Richard Mortell May 2025

Climate Change And The Field Of Farm Labor In The Lower Rio Grande Valley, Texas, Cody Richard Mortell

Theses and Dissertations

Farm workers in the United States are often vulnerable to adverse impacts of climate change, particularly extreme heat. This study explores farm workers’ climate change perceptions (CCP) as a mediating force in climate adaptation. Using latent class analysis, in-person survey data (n=404) from Lower Rio Grande Valley, TX (2024) and NOAA data were analyzed. Results were interpreted using Bourdieu’s field analysis framework and his notions of capital and symbolic power. Findings include: a social hierarchy with three latent classes of workers based on economic, cultural, social, and symbolic capital, which statistically significantly affected CCP. Workers in higher structural positions were …

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Comparison And Evaluation Of Overlay And Leveling Binder In Traffic Circle Construction, Pratik Neupane May 2025

Comparison And Evaluation Of Overlay And Leveling Binder In Traffic Circle Construction, Pratik Neupane

Graduate Theses and Dissertations (2019 - present)

Traffic circles play a vital role in managing traffic flow and ensuring safety, yet their unique traffic conditions make them prone to early cracking and deformation. This study evaluated the performance of overlay and leveling binder asphalt mixtures for a reconstructed traffic circle at the University of South Alabama, using plant-mixed laboratory-compacted (PMLC) specimens. Volumetric analyses were performed to determine maximum specific gravity (Gmm), bulk specific gravity (Gmb), and air voids content. Laboratory tests were conducted on both the overlay and leveling binder layers using indirect tensile cracking test (IDEAL-CT) and indirect tensile rutting test (IDEAL-RT) to assess cracking tolerance …

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A Survey Of Master's Qualifying Exam Practices And Content In Real Analysis, Zachary M. Coverstone May 2025

A Survey Of Master's Qualifying Exam Practices And Content In Real Analysis, Zachary M. Coverstone

All Graduate Theses and Dissertations, Fall 2023 to Present

Graduate programs in mathematics are intended to develop experts in mathematics. As part of a graduate program, many students are expected to engage in a qualifying examination that can serve myriad purposes. This dissertation investigates real analysis qualifying examinations at the master's level through a nation-wide survey of institutions in the Association of Public and Land-Grant Universities (APLU). This study reveals the practices in administration of real analysis qualifying exams, institutions reported offering traditional, pencil-and-paper exams and generally asked students to prepare individually using previously administered exams. The survey results show that approximately two in three APLU institutions offering master's …

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Cranial Ontogeny Of The Extinct Dwarf Tapir Tapirus Polkensis; With Comparison To That Of The Extant Tapirus Bairdii (Tapiridae, Perissodactyla), Johannah Orendorff May 2025

Cranial Ontogeny Of The Extinct Dwarf Tapir Tapirus Polkensis; With Comparison To That Of The Extant Tapirus Bairdii (Tapiridae, Perissodactyla), Johannah Orendorff

Electronic Theses and Dissertations

Tapirus polkensis is the smallest known species of tapir to ever live, and the largest deposit of their fossils is currently located at the GFS in Gray, TN. Phylogenetics suggest that the extant T. bairdii may be the sister taxon to T. polkensis, although they differ greatly in their morphology. Variation exists among adult T. polkensis specimens, with patterns not present in T. bairdii. For this study, as series of 2D GMAs, with TPSs, were rendered on 10 skulls of T. polkensis and 48 skulls of T. bairdii, across both species’ ontogenetic series. Analyses confirmed that growth …

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New Mathematical Approaches To Ultra-Cold Atoms, Joanna Ruhl May 2025

New Mathematical Approaches To Ultra-Cold Atoms, Joanna Ruhl

Graduate Doctoral Dissertations

This dissertation addresses three main themes: cold atoms, integrability, and number theory. In this dissertation we present novel approaches to four models, each of which touches on at least two of the three themes. At the intersection of cold atoms and integrability, we present a Lagrange bracket formalism that allows for exact computation of initial quantum fluctuations of soliton breathers which previously could only be estimated numerically, and the advance in software tools developed in Python to facilitate studies of two-dimensional disc breathers. At the intersection of integrability and number theory, we present a propagator for the Newman-Moore, or triangular …

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Effects Of Environmentally Relevant Concentrations Of Roundup On Oxidative-Nitrative Stress, Cellular Apoptosis, Prooxidant-Antioxidant Homeostasis, Renin And Cyp1a Expressions In Goldfish: Molecular Mechanisms Underlying Kidney Damage During Roundup Exposure, Md Imran Noor, Md Saydur Rahman May 2025

Effects Of Environmentally Relevant Concentrations Of Roundup On Oxidative-Nitrative Stress, Cellular Apoptosis, Prooxidant-Antioxidant Homeostasis, Renin And Cyp1a Expressions In Goldfish: Molecular Mechanisms Underlying Kidney Damage During Roundup Exposure, Md Imran Noor, Md Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Roundup is one of the most widely used glyphosate-based harmful herbicides in the United States as well as globally, which poses a severe risk for terrestrial and aquatic organisms. In order to identify the detrimental effects of Roundup exposure in aquatic organisms, we investigated the environmentally relevant concentrations of Roundup exposure (low dose: 0.5 μg/L and high dose: 5.0 μg/L for 2 weeks) on renin expression, oxidative-nitrative stress biomarkers (e.g., 2,4-dinitrophenol, DNP; and 3-nitrotyrosine protein, NTP), prooxidant-antioxidant enzymes expressions (e.g., superoxide dismutase, SOD; and catalase, CAT), cellular apoptosis, and cytochrome P450 1A (CYP1A) mRNA levels in the kidneys of goldfish …

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