Digital Commons Network^™

Pair Creation, Backreaction, And Resummation In Strong Fields, Patrick Copinger, James P. Edwards, Anton Ilderton, Karthik Rajeev

School of Engineering, Computing and Mathematics

We revisit particle creation in strong fields, and backreaction on those fields, from an amplitudes perspective. We describe the strong field by an initial coherent state of photons which we explicitly evolve in time, thus going beyond the background-field approximation, and then consider observables which quantify the effects of backreaction. We present expressions for the waveform, vacuum persistence probability, and number of produced photons at next-to-leading order, all of which are impacted by backreaction, along with the number and statistics of produced pairs. We find that converting between in-out (amplitude) and in-in (expectation value) expressions requires explicit resummation of an …

Evaluating The Ghg Emissions, Land Use, And Water Use Associated With Contemporary Dietary Patterns In The Republic Of Ireland, Daniel Burke, Paul Hynds, Anushree Priyadarshini

Articles

Dietary patterns are intrinsically linked to greenhouse (GHG) emissions, land use, and water use via food production systems. Analysing and comparing contemporary dietary patterns and their environmental impact is critical to identifying which should be promoted to enhance global sustainability. A cross-sectional survey of adult consumption patterns was conducted across Ireland with a representative sample size of 957 respondents. Subsequently, a farm-to-fork life cycle assessment (LCA) was employed via OpenLCA 2.0.4 to assess three primary environmental impacts (global warming, land use, and water use) across the population. Thirteen distinct dietary patterns were analysed: total population, rural, urban, self-reported (omnivore, flexitarian, …

Exploring Key Factors Influencing Depressive Symptoms Among Middle-Aged And Elderly Adult Population: A Machine Learning-Based Method, Ngoc Doan Thu Tran, Yi Zhen Tan, Sapphire Lin, Fang Zhao, Yee Sien Ng, Dong Ma, Jeonggil Ko, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Objective: This paper aims to investigate the key factors, including demographics, socioeconomics, physical wellbeing, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using machine learning techniques. By identifying the most important predictors of depressive symptoms through the analysis, the findings can have important implications for early depression detection and intervention. Participants: For our cross-sectional study, we recruited a total of 976 volunteers, with a specific focus on individuals aged 50 and above. Each participant was requested to provide their demographic, socioeconomic information and undergo several physical health tests. Additionally, they were asked …

A Causality-Aware Paradigm For Evaluating Creativity Of Multimodal Large Language Models, Zhongzhan Huang, Shanshan Zhong, Pan Zhou, Shanghua Gao, Marink Zitnik, Liang Lin

Research Collection School Of Computing and Information Systems

Recently, numerous benchmarks have been developed to evaluate the logical reasoning abilities of large language models (LLMs). However, assessing the equally important creative capabilities of LLMs is challenging due to the subjective, diverse, and data-scarce nature of creativity, especially in multimodal scenarios. In this paper, we consider the comprehensive pipeline for evaluating the creativity of multimodal LLMs, with a focus on suitable evaluation platforms and methodologies. First, we find the Oogiri game—a creativity-driven task requiring humor, associative thinking, and the ability to produce unexpected responses to text, images, or both. This game aligns well with the input-output structure of modern …

Towards Resource-Efficient Reactive And Proactive Auto-Scaling For Microservice Architectures, Hussain Ahmad, Christoph Treude, Markus Wagner, Claudia Szabo

Research Collection School Of Computing and Information Systems

Microservice architectures have become increasingly popular in both academia and industry, providing enhanced agility, elasticity, and maintainability in software development and deployment. To simplify scaling operations in microservice architectures, container orchestration platforms such as Kubernetes feature Horizontal Pod Auto-scalers (HPAs) designed to adjust the resources of microservices to accommodate fluctuating workloads. However, existing HPAs are not suitable for resource-constrained environments, as they make scaling decisions based on the individual resource capacities of microservices, leading to service unavailability, resource mismanagement, and financial losses. Furthermore, the inherent delay in initializing and terminating microservice pods hinders HPAs from timely responding to workload fluctuations, …

Seven Hci Grand Challenges Revisited: Five-Year Progress, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Vincent G Duffy, Qin Gao, Waldemar Karwowski, Fiona Nah, Stavroula Ntoa, Pei-Luen Patrick Rau, Keng Siau, Jia Zhou

Research Collection School Of Computing and Information Systems

Motivated by the rapid technological advancements achieved in the last five years, and the pervasiveness of Artificial Intelligence, the paper investigates the evolving role of Human-Computer Interaction and revisits the seven grand challenges outlined in 2019: human-technology symbiosis, human-environment interactions, ethics, privacy and security, well-being, health and eudaimonia, accessibility and universal access, learning and creativity, and social organization and democracy. Through literature analysis, the paper reevaluates the status of each challenge and highlights emerging requirements. Key findings reveal the widespread impact of Artificial Intelligence across all domains and emphasize the need for improved AI transparency, alignment with human values, and …

Hotpatching On The Fly: Mitigating Drone Incidents Arising From Incorrect Configuration, Ruidong Han, Juanru Li, Zhuo Ma, David Lo, Arash Shaghaghi, Jianfeng Ma, Siqi Ma

Research Collection School Of Computing and Information Systems

Manufacturers offer adjustable control parameters for flight control systems to accommodate diverse environments and missions. To ensure flight safety, they also develop established boundaries, i.e., range specifications for parameter values. However, even when the configuration parameters fall within the prescribed manufacturer range, they could still lead to instability or even severe incidents like crashes, which are referred to as Range Specification Bugs. Prior research has suggested shrinking the range of parameter values to protect drones from the adverse effects of such bugs. However, narrowing the range of parameters may only reduce the probability of errors and could potentially limit the …

Helicity Modulus And Chiral Symmetry Breaking For Boundary Conditions With Finite Twist, Gaurav Khairnar, Thomas Vojta

Physics Faculty Research & Creative Works

We study the response of a two-dimensional classical XY model to a finite (noninfinitesimal) twist of the boundary conditions. We use Monte Carlo simulations to evaluate the free energy difference between periodic and twisted-periodic boundary conditions and find deviations from the expected quadratic dependence on the twist angle. Consequently, the helicity modulus (spin stiffness) shows a nontrivial dependence on the twist angle. We show that the deviation from the expected behavior arises because of the mixing of states with opposite chirality which leads to an additional entropy contribution in the quasi-long-range ordered phase. We give an improved prescription for the …

Microplastic Accumulation In Soils: Unlocking The Mechanism And Biodegradation Pathway, Minh-Ky Nguyen, Md. Refat Jahan Rakib, Myung Hwangbo, Jongsun Kim

School of Earth, Environmental, & Marine Sciences Faculty Publications

Plastic pollution has become a pressing environmental issue, with significant quantities of microplastics (MPs) contaminating terrestrial ecosystems. In agro-environments and soils, the abundance of MPs has been reported to range from 3.7 to 40,800 items per kilogram. Once MPs enter the soil, their accumulation can have several detrimental effects on the soil environment and ecosystems. This review summarizes current research on the biodegradation of MP-contaminated soils. The primary mechanism of MP biodegradation involves enzymatic oxidation and hydrolysis, leading to the formation of functional groups. The interaction between microorganisms and polymers involves various processes, including colonization, biofilm formation, and biodegradation. Microorganisms …

Application Of Convolutional Neural Network For Seismic Event Classification: Impact Of Dataset Quality, Distribution, And Human-In-The-Loop Feedback, Yanwei Zhang, Stephen S. Gao, Xiaoyi Fan, Shaohui Zhou, Junhao Qu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Convolutional neural networks (CNNs) have gained popularity in geophysical research due to their exceptional performance in various areas. However, achieving reliable results with CNNs typically requires a significant amount of high-quality data for training. In this study, we develop a CNN to classify natural earthquakes, mine collapses, and explosions using seismic waveforms from 287 stations in Shandong Province, China. The dataset comprises 1035 earthquakes, 159 mine collapses, and 586 explosions. To address the impact of unreliable measurements, we employ cross validation to screen, manually correct, or discard measurements with inconsistent labels assigned by human experts and CNN. By refining the …

Analytical Method For Solving Systems Of Fractional Initial Value Problems Using The Modified Atangana-Baleanu Derivative, Lana Mohammad Aref

Theses

This thesis presents an analytical method to solve systems of fractional initial value problems using the Modified Atangana-Baleanu Fractional Derivative. The proposed approach leverages an improved operational matrix method, incorporating an iterative, direct computation technique to simplify the solution process and reduce computational costs. Foundational concepts in fractional calculus and block pulse functions are introduced, followed by the derivation of operational matrices tailored for fractional systems. Theoretical analysis establishes the existence and uniqueness of solutions, along with uniform convergence and error estimates. Practical examples and applications are presented that demonstrate the efficiency, accuracy, and versatility of the method in solving …

Impact Of A Kinesthetic Learning Model On Architecture, Engineering, And Construction (Aec) Knowledge In African American Middle School Girls, Mercy F. Fash, Andrea A.N Ofori-Boadu

Journal of Research Initiatives

This study examines the impact of a femalized Architecture, Engineering, and Construction Kinesthetic Learning Model (fAEC-KLM) intervention on the AEC knowledge of African American middle school girls. Fourteen (14) middle school girls completed both pre- and post-surveys and tests that assessed their knowledge of AEC concepts, including roles and responsibilities, gender and racial diversity, and salary benefits. Paired-sample t-tests were utilized to evaluate statistically significant differences in knowledge before and after fAEC-KLM intervention. Results showed notable improvements in students' knowledge of AEC salary and benefits, as well as the underrepresentation of females, particularly African American females, and AEC roles and …

Scrutinizer: Towards Secure Forensics On Compromised Trustzone, Yiming Zhang, Fengwei Zhang, Xiapu Luo, Rui Hou, Xuhua Ding, Zhenkai Liang, Shoumeng Yan, Tao We, Zhengyu He

Research Collection School Of Computing and Information Systems

The number of vulnerabilities exploited in Arm TrustZone systems has been increasing recently. The absence of digital forensics tools prevents platform owners from incident response or periodic security scans. However, the area of secure forensics for compromised TrustZone remains unexplored and presents unresolved challenges. Traditional out-of-TrustZone forensics are inherently hindered by TrustZone protection, rendering them infeasible. In-TrustZone approaches are susceptible to attacks from privileged adversaries, undermining their security. To fill these gaps, we introduce SCRUTINIZER, the first secure forensics solution for compromised TrustZone systems. SCRUTINIZER utilizes the highest privilege domain of the recent Arm Confidential Computing Architecture (CCA), called the …

Toward A Critical Pedagogy Of Assessment Integrating Social Studies Education: The Proposed Socio-Critical Assessment Integration Framework (Scaif), Caroline O. Alordiah, Regina Arisi

Journal of Research Initiatives

The Socio-Critical Assessment Integration Framework (SCAIF) and its consequences for social studies education are examined in this study. The results emphasize the advantages of developing inclusive learning environments, encouraging comprehensive evaluation procedures, encouraging applicability to the real world, and giving students agency by allowing participation in the evaluation process actively. Teachers can promote social justice, question prevailing narratives, and foster critical discourse in the classroom using a critical pedagogy lens. Student learning outcomes are improved by authentic assessment activities that reflect real-world problems and demand that students use their knowledge in meaningful ways. Inclusive learning settings respect student diversity, encourage …

Iowa Waste Reduction Center Newsletter, February 2025, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Diane Albertson Memorial Scholarship
--- Introducing new IWRC Advisory Committee Members
--- Launching Compost Training Program in Rural Midwestern Communities
--- 2024 MSEI Reminder
--- Resilient Iowa Communities
--- Industry news

K–12 Educators’ Use Of Technology And Experiences With Technostress: A Case Study, Greg Blair Pittman

Electronic Theses and Dissertations

Abstract

This dissertation explored the increased use of technology in K–12 classrooms, which is causing educators to experience technostress. The purpose of the qualitative, descriptive, single case study was to explore the experiences of K–12 teachers with technology and technostress—techno-insecurity, techno-invasion, techno-complexity, techno-uncertainty, and techno-overload—in a West Texas private school district. The researcher conducted one-to-one interviews with seven K-12 educators and two senior leadership team members. In addition, open-ended online questionnaires were available for K–12 educators and senior leadership team members. Thematic analysis was used to locate and communicate the findings. The principal research question was: How do K–12 classroom …

Human-Ai Synergy In Survey Development: Implications From Large Language Models In Business And Research, Ping Fan Ke, Ka Chung Ng

Research Collection School Of Computing and Information Systems

This study examines the novel integration of Large Language Models (LLMs) into the survey development process in business and research through the development and evaluation of the Behavioral Research ASSistant (BRASS) Bot. We first analyzed the traditional scale development process to identify tasks suitable for LLM integration, including both human-in-the-loop and automated LLM data collection methods. Following this analysis, we developed the details of BRASS Bot, incorporating design principles of falsifiability and reproducibility. We then conducted a comprehensive evaluation of the BRASS Bot across a diverse set of LLMs, including GPT, Claude, Gemini, and Llama, to assess its usability, validity, …

The Role Of Surprisal In Issue Trackers, James Caddy, Christoph Treude, Markus Wagner, Earl T. Barr

Research Collection School Of Computing and Information Systems

Context: Software development creates and relies on a large volume of information, yet the volume of this information can make it challenging for developers to maintain an overview of all goings-on that a team and external actors contribute to a project. We posit that unexpected or “surprising” events could serve as important signposts amidst this information overload. These unexpected events may indicate underlying anomalies or emergent situations that require immediate attention. To explore this premise, our study leverages the concept of ‘surprisal’ from information theory to identify and quantify these unusual occurrences from the issues and pull requests of popular …

Wf-Ppg: A Wrist-Finger Dual-Channel Dataset For Studying The Impact Of Contact Pressure On Ppg Morphology, Matthew Yiwen Ho, Hung Manh Pham, Aaqib Saeed, Dong Ma

Research Collection School Of Computing and Information Systems

Photoplethysmography (PPG) is a simple optical technique widely used in wearable devices for continuous cardiac health monitoring. However, the quality of PPG signals, particularly their morphology, is influenced by the contact pressure between the skin and the sensor. This variability in signal quality complicates complex tasks that rely on high-quality signals, such as blood pressure and heart rate variability estimation, making them less reliable or even impossible. To address this issue, we present a novel dataset (termed WF-PPG) comprising PPG signals from the wrist measured under varying contact pressures, along with high-quality PPG signals from the fingertip captured simultaneously. Data …

Density Boosts Everything: A One-Stop Strategy For Improving Performance, Robustness, And Sustainability Of Malware Detectors, Jianwen Tian, Wei Kong, Debin Gao, Tong Wang, Taotao Gu, Kefan Qiu, Zhi Wang, Xiaohui Kuang

Research Collection School Of Computing and Information Systems

In the contemporary landscape of cybersecurity, AI-driven detectors have emerged as pivotal in the realm of malware detection. However, existing AI-driven detectors encounter a myriad of challenges, including poisoning attacks, evasion attacks, and concept drift, which stem from the inherent characteristics of AI methodologies. While numerous solutions have been proposed to address these issues, they often concentrate on isolated problems, neglecting the broader implications for other facets of malware detection. This paper diverges from the conventional approach by not targeting a singular issue but instead identifying one of the fundamental causes of these challenges, sparsity. Sparsity refers to a scenario …

Learning An Interpretable Stylized Subspace For 3d-Aware Animatable Artforms, Chenxi Zheng, Bangzhen Liu, Xuemiao Xu, Huaidong Zhang, Shengfeng He

Research Collection School Of Computing and Information Systems

Throughout history, static paintings have captivated viewers within display frames, yet the possibility of making these masterpieces vividly interactive remains intriguing. This research paper introduces 3DArtmator, a novel approach that aims to represent artforms in a highly interpretable stylized space, enabling 3D-aware animatable reconstruction and editing. Our rationale is to transfer the interpretability and 3D controllability of the latent space in a 3D-aware GAN to a stylized sub-space of a customized GAN, revitalizing the original artforms. To this end, the proposed two-stage optimization framework of 3DArtmator begins with discovering an anchor in the original latent space that accurately mimics the …

Negotiating With Gpt-4: Digital Doormat Or Skilful Counterpart?, Dorcas Quek Anderson

Research Collection Yong Pung How School Of Law

Large language models (LLMs) such as GPT-4 have been creatively harnessed in the conflict resolution arena as dialogue agents interacting with humans within negotiations, due to their capacity for in-context learning and giving human-like responses. In light of the burgeoning use of LLMs in conflict resolution training, a pilot study was conducted to ascertain the desirability of using dialogue agents built on GPT-4 in conducting simulations for students learning negotiation skills. This article discusses insights gained from the study on the reliability of LLM agents in following prompts for negotiation simulations; notable negotiation behaviour of the LLM agent; the degree …

The Dissertation Research Proposal Process: A Systematic Approach, Dianala M. Bernard

Journal of Research Initiatives

A dissertation research proposal is more than just a document that represents the foundation of a doctoral candidate's research journey. It is essential to communicate the study's intent to be undertaken and to gain approval from an academic committee. The present analysis provides a systematic approach to writing a dissertation proposal, offering insights and strategies that align with contemporary research practices. From framing the research with an introduction and formulating research questions to outlining the methodology, this guide highlights the key components contributing to a successful proposal. Emphasizing clarity, originality, and scholarly rigor, this guide also draws from current academic …

Draft Final Bpsou Insufficiently Reclaimed Sites Josephine Shaft (Ir-37) Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Revised Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 158 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Towards Characterizing And Quantifying Interpretability Of Knowledge Graph Embedding Models, Narayanan Asuri Krishnan

Theses

Knowledge graphs are structured representations of real-world information, where entities are connected by edges with labels known as predicates. These graphs contain logical patterns, known as inference patterns, such as symmetry, transitivity and composition, to name a few. To leverage the information contained within a knowledge graph, embedding methods have been developed to encode entities and predicates as numerical vectors in a multi-dimensional space. These embeddings aim to capture the semantic and structural information of the graph, including the inference patterns. However, the sub-symbolic nature of these embeddings present significant challenges in terms of interpretability. Additionally, each embedding model utilizes …

Prospective Observational Study Of Fkrp-Related Limb-Girdle Muscular Dystrophy R9: A Grasp Consortium Study, Lindsay N Alfano, Stephanie Hunn, Conrad C Weihl, Et Al.

2020-Current year OA Pubs

OBJECTIVE: Limb-girdle muscular dystrophy R9 (LGMDR9, formerly known as LGMD2I), caused by variants in the fukutin-related protein (FKRP) gene leads to progressive muscle weakness of the shoulder and pelvic limb-girdles and loss of motor function over time. Clinical management and future trial design are improved by determining which standardized clinical outcome assessments (COA) of function are most appropriate to capture disease presentation and progression, informing endpoint selection and enrollment criteria. The purpose of our study was to evaluate the cross-sectional validity and reliability of clinical outcome assessments in patients with FKRP-related LGMDR9 participating in the Genetic Resolution and Assessments Solving …

A Statistical Framework For Multi-Trait Rare Variant Analysis In Large-Scale Whole-Genome Sequencing Studies, Xihao Li, Han Chen, Margaret Sunitha Selvaraj, Eric Van Buren, Hufeng Zhou, Yuxuan Wang, Ryan Sun, Zachary R Mccaw, Zhi Yu, Min-Zhi Jiang, Daniel Dicorpo, Sheila M Gaynor, Rounak Dey, Donna K Arnett, Emelia J Benjamin, Joshua C Bis, John Blangero, Eric Boerwinkle, Donald W Bowden, Jennifer A Brody, Brian E Cade, April P Carson, Jenna C Carlson, Nathalie Chami, Yii-Der Ida Chen, Joanne E Curran, Paul S De Vries, Myriam Fornage, Nora Franceschini, Barry I Freedman, Charles Gu, Nancy L Heard-Costa, Jiang He, Lifang Hou, Yi-Jen Hung, Marguerite R Irvin, Robert C Kaplan, Sharon L R Kardia, Tanika N Kelly, Iain Konigsberg, Charles Kooperberg, Brian G Kral, Changwei Li, Yun Li, Honghuang Lin, Ching-Ti Liu, Ruth J F Loos, Michael C Mahaney, Lisa W Martin, Rasika A Mathias, Braxton D Mitchell, May E Montasser, Alanna C Morrison, Take Naseri, Kari E North, Nicholette D Palmer, Patricia A Peyser, Bruce M Psaty, Susan Redline, Alexander P Reiner, Stephen S Rich, Colleen M Sitlani, Jennifer A Smith, Kent D Taylor, Hemant K Tiwari, Ramachandran S Vasan, Satupa'itea Viali, Zhe Wang, Jennifer Wessel, Lisa R Yanek, Bing Yu, Nhlbi Trans-Omics For Precision Medicine (Topmed) Consortium, Josée Dupuis, James B Meigs, Paul L Auer, Laura M Raffield, Alisa K Manning, Kenneth M Rice, Jerome I Rotter, Gina M Peloso, Pradeep Natarajan, Zilin Li, Zhonghua Liu, Xihong Lin

Faculty, Staff and Student Publications

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally scalable analytical pipeline for functionally informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple …

Testosterone Modulation Of Muscle Transcriptomic Profile During Lifestyle Therapy In Older Men With Obesity And Hypogonadism, Viola Viola, Tagari Samanta, Maria Liza Duremdes Nava, Alessandra Celli, Reina Armamento-Villareal, Ngoc Ho Lam Nguyen, Georgia Colleluori, Yoann Barnouin, Nicola Napoli, Clifford Qualls, Benny Abraham Kaipparettu, Dennis T Villareal

Faculty, Staff and Students Publications

Background: Testosterone replacement therapy (TRT) added to lifestyle therapy can mitigate weight-loss-induced reduction of muscle mass and bone mineral density (BMD) in older men with obesity and hypogonadism.

Objective: To investigate the molecular mechanisms underlying the attenuation of muscle and BMD loss in response to TRT during intensive lifestyle intervention in this high-risk older population.

Methods: Among 83 older (≥ 65 years) men with obesity (BMI ≥ 30 kg/m2) and hypogonadism (early AM testosterone persistently < 300 ng/dL) associated with frailty (Modified Physical Performance Test score ≤ 31) randomized into 26-week lifestyle therapy plus testosterone (LT+TRT) or placebo (LT+Pbo) in the LITROS trial, 38 underwent serial muscle biopsies for the muscle transcriptomics substudy.

Results: Despite similar ~10% weight loss, lean body mass and thigh muscle volume decreased less in LT+TRT than LT+Pbo (-2% vs. -4%, respectively; p = …

Forearm Versus Upper Arm Location Of Arteriovenous Access Used At Hemodialysis Initiation: Temporal Trends And Racial Disparities, Melandrea L Worsley, Jingbo Niu, Kevin F Erickson, Neal R Barshes, Wolfgang C Winkelmayer, L Parker Gregg

Faculty, Staff and Students Publications

Rationale & objective: Race and ethnicity differences exist in the type of arteriovenous access (AVA, including fistulas and grafts) used at hemodialysis (HD) initiation. The preferred anatomic location for the creation of an initial HD AVA is typically in the forearm We evaluated race and ethnicity differences in the use of an AVA in the forearm location at HD initiation.

Study design: Retrospective cohort study.

Setting & participants: Using records from DaVita Kidney Care linked to the US Renal Data System (USRDS), we evaluated patients aged≥16 years who initiated in-center HD with an AVA between 2006 and 2019.

Predictor: Race …