Physical Sciences and Mathematics Commons^™

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 …

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, …

Controlling Structural Phases Of Sn Through Lattice Engineering, Chandima Kasun Edirisinghe, Anjali Rathore, Taegeon Lee, Daekwon Lee, An Hsi Chen, Garrett Baucom, Eitan Hershkovitz, Anuradha Wijesinghe, Pradip Adhikari, Sinchul Yeom, Hong Seok Lee, Hyung Kook Choi, Hyunsoo Kim, Mina Yoon

Physics Faculty Research & Creative Works

Topology and superconductivity, two distinct phenomena, offer unique insight into quantum properties and their applications in quantum technologies, spintronics, and sustainable energy technologies. Tin (Sn) plays a pivotal role here as an element because of its two structural phases, α-Sn exhibiting topological characteristics and β-Sn showing superconductivity. Here, we demonstrate precise control of these phases in Sn thin films using molecular beam epitaxy with systematically varied lattice parameters of the buffer layer. The Sn films exhibit either β-Sn or α-Sn phases as the buffer layer's lattice constant varies from 6.10Å to 6.48Å, spanning the range from GaSb (like InAs) to …

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 …

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

Spatiotemporal Trends In Anopheles Funestus Breeding Habitats, Grace R. Aduvukha, Elfatih M. Abdel-Rahman, Bester Tawona Mudereri, Onisimo Mutanga, John Odindi, Henri E.Z. Tonnang

All Peer-Reviewed Publications

Effective identification and control of malaria vector larval breeding habitats are crucial for the management and eradication of malaria. Despite its importance, the last decade has seen a decline in data availability and intervention efforts due to reduced attention and prioritization. This study addresses the geographic data scarcity concerning Anopheles funestus larval breeding habitats in a malaria-prone region of western Kenya. Employing a two-step methodological approach, we integrated multi-criteria decision analysis (MCDA) and rule-based fuzzy logic analysis to evaluate the spatiotemporal similarity or divergence of these habitats. The analysis spanned a five-year interval, 2008, 2013, and 2018 with 2013 serving …

Data And Digitalization In Energy Efficiency Policy Design: The Case Of Singapore, Ishani Mukherjee, Diandrea Ho

Research Collection School of Social Sciences

Overarching and broad policy goals for enhancing energy efficiency have existed globally over the last 50 years as a response to rising energy demands, heightening costs, and construction levels of residential and commercial buildings, and the associated rises in greenhouse gas emissions from energy use (Levine et al., 2007; World Bank, 2010). Buildings, in particular, have been widely recognized as offering the greatest potential for reducing energy use and related greenhouse gas emissions, followed by reduced energy consumption in manufacturing, appliances, electronic goods, and end-users of electricity (Levine, 2007; IEA, 2010). And while significant technological strides have been made globally …

Taming Biological Complexity Through The Use Of Symmetries, Luis A. Álvarez-García

Dissertations, Theses, and Capstone Projects

The study of biological systems is, inherently, the study of very complex systems. This is essentially due to the fact that they are made up of numerous, often very complicated, interactions between an extensive number of components. Often necessitating an abundance of quantitative parameters and details for a precise description. The human brain for ex- ample, consisting of ∼ 80 billion neurons with ∼ 800 to 100 trillion connections between them, each of them depending on a large set of parameters. Even simpler examples such as bacterial organisms, such as E. coli and B. subtilis, which we focus on …

Development Of Soil Survey Methods For Urban Areas, Kohinoor Begum

Dissertations, Theses, and Capstone Projects

Urban soils are the foundation of urban ecosystems and play a vital role in long-term urban sustainability and resiliency. Accurate soil surveys of urban areas should be done at higher resolution since extensive human activities often result in urban soil being highly disturbed and spatially variable. Besides heterogeneity, one of the unique and challenging aspects of urban soil is the nature and properties of its organic carbon with a significant percentage of black carbon (a particulate product of incomplete combustion), which is less biologically active. Thus, in order to determine the ability of a soil to support biological activity and …

Quantified Lives: Data, Bias, And The Cost Of Categorization, Colin F. Geraghty

Dissertations, Theses, and Capstone Projects

This project critically examines how statistical methods and data visualization have historically been used to categorize, rank, and control human populations. By exploring the works of key figures like Francis Galton, Karl Pearson, and R.A. Fisher, it traces the evolution of categorization frameworks from their eugenic roots to modern applications in artificial intelligence and global metrics like the World Happiness Report. Through interactive visualizations and historical analysis, the project invites users to question the legitimacy of these frameworks and reflect on their impact on society. At its core, this work emphasizes the need to move beyond rigid classification systems, challenging …

Solvation Thermodynamic Mapping Approaches For Computer-Aided Drug Discovery, Vjay Molino

Dissertations, Theses, and Capstone Projects

The drug discovery process is inherently long and costly, prompting the development and integration of computational tools to mitigate these challenges. One of area explored in computer-aided drug discovery is to understand the role of solvation in protein-drug binding and to develop computational tools and methods that can be integrated in the drug discovery process. Grid Inhomogeneous Solvation Theory (GIST) is a tool that provides a framework for mapping solvation thermodynamiproperties of water molecules on the protein surface.This thesis explores the use of GIST in generating pharmacophore models and elucidates the role of solvation in protein structural fluctuations.

One of …

Visualizing The Rise Of American Women's Soccer, Hoi Wah Tang

Dissertations, Theses, and Capstone Projects

The rise of American women’s soccer is a compelling narrative of determination, talent, and triumph on the global stage. From the inaugural FIFA Women’s World Cup in 1991 to the ongoing dominance of the U.S. Women’s National Team (USWNT), this journey encapsulates not only athletic excellence but also the broader struggles for equality, representation, and respect in sports.

This project aims to bring this story to life by presenting a rich tapestry of data visualizations, timelines, and multimedia elements that showcase key moments, players, and milestones. Through engaging graphics and interactive features, users will explore how the sport evolved, the …

The Role Of Confined Hydration And Water Reorganization In Molecular Binding, Joe Z. Wu

Dissertations, Theses, and Capstone Projects

An important factor in guiding the development of drug discovery efforts is the comprehensive assessment of a ligand or drug’s ability to bind its receptor. The metric used to measure this interaction strength is by calculating the binding free energy (BFE). To achieve this accurately, we combine two concepts: (1) Grid Inhomogeneous Solvation Theory (GIST) returns the local water thermodynamic and structural contributions to free energy; and the (2) Alchemical Transfer Method (ATM) obtains the absolute (ABFE) and relative binding free energy (RBFE) estimates between ligand pairs. In this work, we employ Alchemical Water-Transfer to tether bridging water(s) during the …

Silver-Alloyed Cigs Thin-Film Solar Cells On Flexible Stainless-Steel Substrate, Zhi Huang

Dissertations, Theses, and Capstone Projects

Our dissertation demonstrates the optimization of ACIGS (Ag-Cu-In-Ga-Se) thin-film solar cells, achieving an efficiency of 20.4% through the combined effects of silver incorporation and alkali metal post-deposition treatment (PDT). The incorporation of 2.8% Ag into the CIGS lattice enhanced crystal quality, reduced disorder, and widened the bandgap by 0.103 eV, as evidenced by a significant reduction in Urbach energy. These improvements resulted in stronger light absorption, increased carrier generation, and enhanced photovoltaic parameters, including a short-circuit current density Jsc of 35.31 mA/cm², an open-circuit voltage Voc of 0.74 V, and a fill factor (FF) of 75.8%. PDT using rubidium fluoride …

Why Are Fairness Concerns So Important? Lessons From A Last-Mile Transportation System, Yiwei Chen, Hai Wang

Research Collection School Of Computing and Information Systems

The Last-Mile Problem refers to the provision of travel service for passengers from the nearest public transportation node to the final destination. The Last-Mile Transportation System (LMTS), which has recently emerged, provides on-demand last-mile transportation service for passengers. We consider an LMTS that consists of two types of passengers, regular-type passengers and special-type passengers (e.g., seniors, disabled people). The valuation of the last-mile service for special-type passengers is statistically higher than the one for regular-type passengers. Passengers incur disutility from waiting for the last-mile service. In this paper, we explore two fairness constraints on special-type passengers: (1) the fare for …

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 …

Towards The Next Generation Of Geospatial Artificial Intelligence, Gengchen Mai, Yiqun Xie, Xiaowei Jia, Ni Lao, Jinmeng Rao, Qing Zhu, Zeping Liu, Yao-Yi Chiang, Jiao, Junfeng

Research Collection College of Integrative Studies

Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote …

Gamification For Air Quality Education: A Systematic Literature Review, Abdollah Baghaei Daemei, Ruggiero Lovreglio, Zhenan Feng, Daniel Paes, Clayton Miller

Research Collection College of Integrative Studies

Air quality is crucial to our health and well-being, as poor air quality can lead to serious health problems such as asthma, allergies, and other respiratory conditions. Educating people about air quality is key to improving awareness and taking action to reduce its negative effects. Gamification offers a creative and engaging way to deliver educational content by incorporating game elements into the learning experience. However, despite its potential, there has been no review of how gamification has been used for air quality education. Thus, this review aims to fill that gap by systematically examining how gamification is applied to air …

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, …

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, …

Human‑Ai And Human‑Robot Collaboration In The Age Of Generative Ai, Agentic Ai, And Artificial General Intelligence: Opportunities And Challenges, Keng Siau

Research Collection School Of Computing and Information Systems

The advancement of Artificial Intelligence (AI) has been exponential, especially in the past few years. Most, if not all, of the AI systems we encounter and are exposed to at this point are Artificial Narrow Intelligence (ANI). ANI specializes in one area and solves problems in one area. Generative AI (GenAI) and Agentic AI (i.e., independent AI agent), at the current stage of development, are regarded as ANI. The race is currently on to develop Artificial General Intelligence (AGI). AGI refers to AI systems as smart as humans across a wide range of cognitive tasks. Recently, OpenAI’s o3 system received …

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 …

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 …

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 …

Quantum-Inspired Framework For Big Data Analytics: Evaluating The Impact Of Movie Trailers And Its Financial Returns, Jaiteg Singh, Kamalpreet Singh Bhangu, Farman Ali, Ahmad Ali Alzubi, Babar Shah

All Works

In the context of the growing influence of businesses and marketers on social media platforms, understanding the impact of emotionally charged content on consumer behavior has become increasingly crucial. This study proposes a novel framework, leveraging quantum computing principles, to assess the emotional impact of movie trailers. The framework incorporates big data analytics and utilizes Quantum Walk andQuantum Time Series models to investigate the relationship between a movie trailer's emotional intensity and its financial performance. Unlike sequential problem-solving approach of traditional computing models, Quantum superposition allows exploring multiple options at once. An analysis of 141 movie trailers released after January …

Consequences Of Oxidative Dna Damage: Base-Pair Dissociation, Singlet Oxygenation And Dna-Protein Crosslinking, May Myat Moe

Dissertations, Theses, and Capstone Projects

8-Oxo-2′-deoxyguanosine (OG) is a common DNA lesion resulting from oxidatively generated damage and pairs with complementary cytidine (C) in Watson Crick base-pairing within duplex DNA. The WC-OG·C lesion, if not recognized or repaired, not only leads to G⋅C→T⋅A transversion mutations (through Hoogsteen (HG) base pairing of OG⋅A), but also renders the base pair being more vlunerable to ionizing radiation and singlet oxygen (1O2) damage. Leveraging on our previous accomplishments on the study of gas-phase reactions of 1O2 with 2′-deoxyguanosine radical cations, my research thesis expanded to the investigation of reaction dynamics of 9-methyl-8-oxoguanine (9MOG) radical cations. The experiments of following …

Novel Alchemical Methodologies For Modeling Molecular Binding, Solmaz Azimi

Dissertations, Theses, and Capstone Projects

Molecular recognition is fundamental to all biological and biochemical processes. Understanding the interactions between molecules is the foundation for drug discovery and development, for understanding biological processes, and for the design of biosensors and nanomaterials. There is tremendous interest in the development of computer models to predict molecular association equilibria. In structure-based drug discovery enterprises, predicting the strength and selectivity of a small molecule to a biological target can advance target identification, aid ligand design, and accelerate high-throughput screening of drug compounds. This work focuses on free energy models, a class of computational methodologies grounded on the fundamental physical and …

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, Ryan Sun, 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 …

The Role Of Secondary And Tertiary Structure In The Cap-Independent Translation Of Fgf-9 And Hif-1-Alpha, Amanda Michelle Whittaker

Dissertations, Theses, and Capstone Projects

Under normoxic conditions, eukaryotes initiate translation of RNA through eIF4E recognition of the 5’ cap. However, under cellular stress, eukaryotic translation must be initiated through a 4E-independent, or “cap-independent” mechanism, involving eukaryotic initiation factor 4G (eIF4G) binding directly to the 5’ untranslated regions (5’ UTR) of the RNA. eIF4G binding then recruits the ribosome to the transcript. While this mechanism is useful for translation of apoptotic transcripts and transcripts involved in cell survival, cap-independent translation is also utilized by oncogenic RNA for tumorigenesis. Previous work by our lab and others has categorized this recruitment and initiation mechanism as either internal-ribosome-entry-site …