Digital Commons Network^™

The Future Of Fashion: A Systematic Literature Review On Consumer Willingness To Pay For Green Apparel, Emma Clark

Graduate Theses and Dissertations

In recent years, consumers have become highly aware of the environmental impact of their purchases, specifically of apparel products. Accordingly, apparel brands have increasingly focused on enhancing the sustainability of their product offerings to attract environmentally conscious consumers and elevate their brand image (Dangelico et al., 2022). Furthermore, most sustainably produced products are priced higher for consumers compared to standard alternatives (Elmanadily & El-Deeb, 2022). Research has shown that consumers can accept higher prices for products that do less harm to the environment (Gomes et al., 2023), but it has yet to be determined in which cases this is consistently …

Oculomics: Current Concepts And Evidence, Zhuoting Zhu, Yueye Wang, Ziyi Qi, Wenyi Hu, Xiayin Zhang, Siegfried K Wagner, Yujie Wang, An Ran Ran, Joshua Ong, Ethan Waisberg, Mouayad Masalkhi, Alex Suh, Yih Chung Tham, Carol Y Cheung, Xiaohong Yang, Honghua Yu, Zongyuan Ge, Wei Wang, Bin Sheng, Yun Liu, Andrew G Lee, Alastair K Denniston, Peter Van Wijngaarden, Pearse A Keane, Ching-Yu Cheng, Mingguang He, Tien Yin Wong

Faculty, Staff and Student Publications

The eye provides novel insights into general health, as well as pathogenesis and development of systemic diseases. In the past decade, growing evidence has demonstrated that the eye's structure and function mirror multiple systemic health conditions, especially in cardiovascular diseases, neurodegenerative disorders, and kidney impairments. This has given rise to the field of oculomics-the application of ophthalmic biomarkers to understand mechanisms, detect and predict disease. The development of this field has been accelerated by three major advances: 1) the availability and widespread clinical adoption of high-resolution and non-invasive ophthalmic imaging ("hardware"); 2) the availability of large studies to interrogate associations …

The Role Of Ai In Enhancing Teamwork, Resilience And Decision-Making: Review Of Recent Developments, Satyadhar Joshi

Harrisburg University Other Works

This paper explores the transformative impact of artificial intelligence (AI) on organizational teamwork, decision-making, and resilience. This paper furthur reviews recent literature on the integration of Artificial Intelligence (AI) in various organizational functions, focusing on its impact on innovation management, leadership paradigms, and organizational resilience. We provide groundwork required to enhance frameworks that can integrate cognitive scaffolding with antifragile team dynamics, employing behavioral economics and neurocognitive principles. We introduce methodologies for enhancing team resilience through adaptive AI systems, cross-training interventions, and pre-mortem simulation techniques. The framework addresses key challenges in confirmation bias mitigation, cultural dimension alignment, and vigilance decrement prevention. …

Considerations And Techniques For Producing Urban Tree Canopy Maps Using Freely Available And Accessible Methods, Hugh Reed Ellerman

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Urban forests are valued as green infrastructure for the variety of benefits they provide across ecological, social, public health, and economic domains. To understand the distribution of trees, maps are required. Many methods of mapping tree cover use expensive and data-intensive datasets such as hyperspectral and LiDAR imagery, making these methods inaccessible to municipal forest managers. Variations in the modelling approaches of existing, freely available methods are not addressed in sufficient enough detail to understand the trade-offs implicit in these variations. Further, characteristics of urban tree canopy mapping (high spatial resolution imagery, heterogeneous urban environments, the importance of the tree …

Harnessing Edna Metabarcoding To Monitor Species Diversity In Restoration Sites: Insights From Laikipia, Kenya, Cornelius Okello, Nina Wambiji, Susana W. Kihia, Nehemiah Ongeso, Samuel Mwakisha Mwamburi, Anthony Wandera, Marie Estelle Demory, Margaret Awuor Owuor

All Peer-Reviewed Publications

Restoration of degraded arid and semi-arid lands (ASALs) dryland ecosystems gained traction globally with the enactment of the Bonn Challenge and UN Decade of Restoration. This has been domesticated in Kenya's context by The Forest and Landscape Restoration Implementation Plan (FOLAREP). However, effectively monitoring restored ecosystems is crucial but challenging because of data gaps and technical hurdles, highlighting the need for innovative approaches to assess and restore biodiversity. This study aimed to pilot soil environmental DNA (eDNA) metabarcoding to detect species compositions rapidly, evaluate population structures and abundances, and characterize taxonomic groups. The results from this study serve as a …

Biophysical Studies Of Nucleic Acid - Small Molecule Recognition, Andrea Conner

All Dissertations

The presented work is a collection of studies performed to examine small molecule recognition of nucleic acids. Recognition of nucleic acids was examined using two types of small molecules: aminoglycosides and Hoechst dyes. Chapter One focuses on established experimental techniques (i.e. absorbance, isothermal titration calorimetry, flow cytometry, cell microscopy, etc.) in small molecule recognition of nucleic acids. The emphasis of studies in the group has been on two focus areas. (i) Thermodynamic characterization of mixed A-form and B-form DNA or RNA conformation with aminoglycosides, particularly neomycin-class. (ii) Characterization of new Hoechst-morpholine (HT-MO) derivatives’ interactions with nucleic acids.

Focus area (i) …

Exploring The Pedagogical Impact Of Software Development Live Streams: Informal Learning Opportunities For Software And Game Developers, Ella Kokinda

All Dissertations

Live streaming is an increasingly popular medium for throwing back the curtain on software development where streamers and viewers share their knowledge and experiences. Popular platforms like Twitch and YouTube enable developers to stream live coding sessions where people around the world can engage in real-time collaboration, feedback, knowledge sharing, and skill development. This work investigates the pedagogical implications and learning opportunities present in software and game development live streaming while focusing on the role of streaming as a learning environment and collaborative community. We begin by exploring summer camps as an informal learning opportunity for STEM education, highlighting the …

Synthesis Of Nanoparticles In Silicate Matrix And Stimuli Responsive Nanocomposite Polymer Films, Dimuthu Edirisinghe

All Dissertations

Interactions between aqueous metal ions and soluble silicates lead to the formation of insoluble metal silicate complexes that form nanoparticles via condensation polymerization. Metal silicates function as nanoreactors, effectively condensing metal ions into nano-sized particles that can undergo further chemical transformations. Core-shell nanostructures present an intriguing strategy for integrating materials with different properties. The silicate shell around the silver nanoparticles can be successfully infused with other metal ions, enabling subsequent reactions to tailor their properties. Silver nanoparticles exhibit strong interactions with light, surpassing other chromophores, including noble metal nanoparticles, due to their highly efficient surface plasmonic resonance. The unique optical …

Strengthening The Bonds Between Us: An Empirical Investigation Of Morale In Human-Ai Teams And The Socially Supportive Ai Teammates Who Empower It, Rohit Mallick

All Dissertations

This dissertation investigates how artificial intelligence (AI) can be designed to improve the collective emotion within a team. A team's collective emotion, or morale, describes how motivated, optimistic, and enthusiastic the group is in accomplishing its goals. We conducted four studies that compared different social support strategies that AI teammates can provide to the team. Study 1A found that AI teammates who communicate with emotions can better motivate human team members and promote awareness of team dynamics and environmental changes. Study 1B found that human teammates become more motivated and happier when their AI teammates express joy and are close …

Thermal Performance Drifts Between The Egg Parasitoid Telenomus Remus And The Fall Armyworm May Threaten The Efficacy Of Biological Control Under Climate Change, Macdonald Mubayiwa, Honest Machekano, Brighton M. Mvumi, Winnifred A. Opio, Bame Segaiso, Frank Chidawanyika, Casper Nyamukondiwa

All Peer-Reviewed Publications

The fall armyworm, Spodoptera frugiperda J.E. Smith, is a significant global agricultural pest known for its rapid invasion and devastating impact on crops. While pesticides may be effective for controlling the pest in the short-term, they cause several socioeconomic and ecological costs that highlight the need for more sustainable management strategies. Telenomus remus (Nixon) is a promising egg parasitoid for its biological control. For the parasitoid to provide effective ecosystem services, it should be able to survive and coexist within the same ecological niches as its host. However, there is limited information regarding the potential responses of T. remus to …

Behind The Screen: Understanding The Human Firewall In Cybersecurity, Arun Venkitanarayanan

Emergency Preparedness, Homeland Security, and Cybersecurity

No abstract provided.

Correcting Sampling Bias With Privacy-Preserving Synthetic Data: Inference Stability Under The Da-Mi Framework, Hannah Jiang

Arts & Sciences Graduate Student Theses and Dissertations

With the rapid advancement into the Data Age, synthetic data has emerged as a promising avenue for sharing scientific information while protecting the original data. While existing research has primarily focused on generating synthetic data to accurately replicate the characteristics of observed data, we explore the potential of synthetic data to adjust for unrepresentative sampling. This study explores how sampling bias—specifically unbalanced subsets—impacts statistical inference, and whether synthetic data can help correct such bias. Using a Data Augmentation–Multiple Imputation (DA–MI) framework, we generate synthetic datasets from biased samples and evaluate parameter recovery under different correction strategies. Simulations under a Missing …

Microplastics In Coastal And Marine Environments: A Critical Issue Of Plastic Pollution On Marine Organisms, Seafood Contaminations, And Human Health Implications, Rebecca Muñiz, Md. Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Plastic has quickly become one of the world's most prevalent environmental pollutants. Population growth has only amplified the demand, resulting in 430 million tons of plastic produced annually, with 11 million tons ending up in our oceans. Without intentional intervention, plastic waste in the oceans is expected to triple, posing severe risks for the aquatic ecosystems, animals, and humans dependent on these waters. As plastic accumulates in oceans and other water environments, the non-biodegradable particles break down into micro- and nano-plastics, invading coastal and marine organisms and causing considerable physiological and morphological damage. This is especially concerning for the millions …

Assessing Perceived Safety Of Non Motorized Travel With Virtual Reality, Vahid Balali, Sahand Fathi

Mineta Transportation Institute

Cycling is increasingly advocated as a healthier and more sustainable mode of transportation, as reflected in both scholarly literature and policy initiatives. Nonetheless, the escalation in bicyclist crash fatalities underscores deficiencies in extant roadway designs that inadequately safeguard these vulnerable users. A persistent challenge in the examination of bicyclist safety, behavior, and comfort is the paucity of comprehensive cycling data. To enhance understanding of cyclists' behavioral and physiological responses safely and efficiently, this investigation utilizes a bicycle simulator within an immersive virtual environment (IVE). Off-the-shelf sensors are employed to evaluate cyclists' performance metrics (speed and lane position) and physiological responses …

Mathematics-Ai Based Phylogenetic Analysis Of Influenza Virus Mutation Data, Emilee Walden

Mathematical Sciences Undergraduate Honors Theses

The influenza virus is one of the most common viral infections each year and can mutate rapidly. Viral mutations pose significant threats to public health by increasing infectivity and strengthening vaccine resistance. To track these evolving patterns, agencies like the CDC annually evaluate thousands of virus strains to understand viral mutagenesis and evolution in depth. Therefore, a computational method for analyzing high-dimensional, noisy virus data could aid in the rapid identification of antigens essential for an effective influenza vaccine for the upcoming season. Through the integration of genomic analysis, clustering, and dimensionality reduction methods, this study specifically aims to develop …

2024 Annual Operations And Maintenance Report, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

“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 …

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 …

Achieving Fairness In Zoning Laws With Machine Learning, William Schimitsch

College Honors Program

Zoning is a powerful regulatory tool that determines how municipalities use and develop land. The goal of zoning is to classify land use (e.g., residential, commercial, industrial) to maximize compatibility among neighboring parcels. Local zoning decisions, however, are made by small-sized boards, often through an opaque process, which raises concerns about bias and fairness. In the United States, zoning has historically prioritized single-family housing and thus created economic barriers that limit access to certain communities. Given the task of classifying land use and the wealth of geographical, demographic, and infrastructural data describing each parcel, the problem of bias in zoning …

Guest Editorial: When Multimedia Meets Food: Multimedia Computing For Food Data Analysis And Applications, Weiqing Min, Shuqiang Jiang, Petia Radeva, Vladimir Pavlovic, Chong-Wah Ngo, Kiyoharu Aizawa, Wanqing Li

Research Collection School Of Computing and Information Systems

Food is central in our life for its fundamental role in our survival, health, mood and culture. The deployment of various networks (e.g., IoT and mobile networks), devices (e.g., hyperspectral imaging devices, electronic nose/tongue), databases (e.g., nutrition tables and food compositional databases), recipe-sharing websites (e.g., Yummly and Meishijie) and social media (e.g., Twitter and Weibo) has generated unprecedented volumes of multi-modal food data. Such multi-source multi-modal food data provides new perspectives to analyze and understand food consumption via multimedia computing. Riding on the wave of AI, food-oriented multimedia computing integrates AI, multimedia technology and food science to enable a wide …

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 …

Iot In Sustainability And Iot In The Ai And Metaverse Age, Yuzhou Qian, Keng Siau

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is a modern technology that has gained large popularity and is still developing. Connecting heterogeneous devices, such as phones, vehicles, and household appliances, IoT has brought convenience to our lives. Further, IoT plays a significant role in enhancing environmental sustainability. It provides timely data about different devices and enables users and managers to directly control the objects. IoT can optimize the existing energy systems and promote the usage of renewable technologies. In this paper, we discuss how IoT supports green initiatives (i.e., how it is applied in different sectors), how it can be "green" itself …

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 …

More Concerns About Atmospheric Methane Removal Efforts, Joshua Luczak

Research Collection College of Integrative Studies

The National Oceanic and Atmospheric Administration reported record-high global atmospheric carbon dioxide levels (419.3 ppm) in 2023, alongside atmospheric methane levels (1922.6 ppb) now over 160% above pre-industrial levels. The World Meteorological Organization predicts 2024 could surpass 2023 as the warmest year on record, with more frequent and severe extreme weather events. Meeting the Paris Climate goal of limiting global warming to well below 2°C—or ideally 1.5°C—above pre-industrial levels is becoming increasingly difficult. To address these challenges, efforts are expanding beyond reducing greenhouse gas emissions. While carbon dioxide removal (CDR) technologies have been the focus, attention is now turning to …

The Efficacy Of Incorporating Artificial Intelligence (Ai) Chatbots In Brief Gratitude And Self-Affirmation Interventions: Evidence From Two Exploratory Experiments, Jing Wen Hung, Andree Hartanto, Adalia Y.H. Goh, Zoey K.Y. Eun, K. T. A. Sandeeshwara Kasturiratna, Zhi Xuan Lee, Nadyanna M. Majeed

Research Collection School of Social Sciences

Numerous studies have demonstrated that positive psychology interventions, including brief interventions, can significantly improve well-being outcomes. These findings are particularly important given that many of these interventions are brief and self-administered, making them both accessible and scalable for large populations. However, the efficacy of positive psychology interventions is often constrained by small effect sizes. In light of advancements in generative Artificial Intelligence (AI), this study explored whether integrating AI chatbots into positive psychology interventions could enhance their efficacy compared to traditional self-administered approaches. Study 1 examined the efficacy of a gratitude intervention delivered through Snapchat's My AI, while Study 2 …

Augsso: Secure Threshold Single-Sign-On Authentication With Popular Password Collection, Changsong Jiang, Chunxiang Xu, Guomin Yang

Research Collection School Of Computing and Information Systems

Single-sign-on authentication is widely deployed in mobile systems, which allows an identity server to authenticate a mobile user and issue her/him with a token, such that the user can access diverse mobile services. To address the single-point-offailure problem, threshold single-sign-on authentication (PbTA) is a feasible solution, where multiple identity servers perform user authentication and token issuance in a threshold way. However, existing PbTA schemes confront critical drawbacks. Specifically, these schemes are vulnerable to perpetual secret leakage attacks (PSLA): an adversary perpetually compromises secrets of identity servers (e.g., secret key shares or credentials) to break security. Besides, they fail to achieve …

Mosmac: A Multi-Agent Reinforcement Learning Benchmark On Sequential Multi-Objective Tasks, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Recent advancements in multi-agent reinforcement learning (MARL) have demonstrated success on various cooperative multi-agent tasks. However, current benchmarks often fall short of representing realistic scenarios that demand agents to execute sequential tasks over long temporal horizons while balancing multiple objectives. To address this limitation, we introduce multi-objective SMAC (MOSMAC), a comprehensive MARL benchmark designed to evaluate MARL methods on tasks involving multiple objectives, sequential subtask assignments, and varying temporal horizons. MOSMAC requires agents to tackle a series of interconnected subtasks in StarCraft II while simultaneously optimizing for multiple objectives, including combat, safety, and navigation. Through rigorous evaluation of nine state-of-the-art …

Photochemical Transformations Of Crude Oil In Marine Environments: Temporal And Thermal Dynamics Of Oxygenated Photoproducts And Genotoxic Effects, Mohamed Elsheref

LSU New Orleans Theses and Dissertations

This dissertation investigates the photochemical transformation of different crude oil types in marine environments, focusing on the time and temperature dependency of the formation of oxygenated photoproducts and their potential genotoxic effects. Using electrospray ionization tandem mass spectrometry (ESI-MS/MS), we examined the time and temperature dependence of aldehyde and ketone oxocarboxylic acid photoproduct generation from crude oil-seawater systems under simulated solar irradiation. The study revealed a near-linear increase in photoproduct concentration over an 18-hour irradiation period, with production rates ranging from 0.6 to 69 µmol/hm² of oil surface. Temperature effects on photoproduct formation were complex, but generally showed increased total …

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 …

Unraveling The Causal Influences Of Drought And Crop Production On Groundwater Levels Across The Contiguous United States, Nitin K. Singh, Sheila M. Saia, Ruchi Bhattacharya, Hoori Ajami, David M. Borrok

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Groundwater depletion in agricultural-dominated regions is attributed to climate and irrigation withdrawals that support crop production. However, despite decades of effort, knowledge gaps remain in understanding the relative influence of drought and crop production on groundwater levels at the continental scale. Here, utilizing empirical observations, we simultaneously track how long-term trajectories of groundwater levels, crop production of seven crops, and drought have evolved over time, and then integrate these observations with a causality-based attribution framework to unravel the relative impact of drought and crop production on groundwater levels across the contiguous United States (CONUS). We find a dominant pattern of …