Digital Commons Network^™

Integrating Environmental Impact Assessment Into International Shipping Governance : A Bbnj-Pssa Synergy Framework, Thi Thuy Linh Pham

World Maritime University Dissertations

No abstract provided.

Butte Priority Soils Operable Unit Clark Tailings Consolidated Waste Management Area Site Investigation Quality Assurance Project Plan (Qapp) Revision 0, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

From Personas To Talks: Revisiting The Impact Of Personas On Llm-Synthesized Emotional Support Conversations, Shenghan Wu, Yimo Zhu, Wynne Hsu, Mong-Li Lee, Yang Deng

Research Collection School Of Computing and Information Systems

The rapid advancement of Large Language Models (LLMs) has revolutionized the generation of emotional support conversations (ESC), offering scalable solutions with reduced costs and enhanced data privacy. This paper explores the role of personas in the creation of ESC by LLMs. Our research utilizes established psychological frameworks to measure and infuse persona traits into LLMs, which then generate dialogues in the emotional support scenario. We conduct extensive evaluations to understand the stability of persona traits in dialogues, examining shifts in traits post-generation and their impact on dialogue quality and strategy distribution. Experimental results reveal several notable findings: 1) LLMs can …

Chain Of Strategy Optimization Makes Large Language Models Better Emotional Supporter, Weixiang Zhao, Xingyu Sui, Xinyang Han, Yang Deng, Yulin Hu, Jiahe Guo, Libo Qin, Qianyun Du, Shijin Wang, Yanyan Zhao, Bing Qin, Ting Liu

Research Collection School Of Computing and Information Systems

The growing emotional stress in modern society has increased the demand for Emotional Support Conversations (ESC). While Large Language Models (LLMs) show promise for ESC, they face two key challenges: (1) low strategy selection accuracy, and (2) preference bias, limiting their adaptability to users’ emotional needs. Existing supervised fine-tuning (SFT) struggles to address these issues, as it rigidly trains models on single gold-standard responses without modeling nuanced strategy trade-offs. To overcome these limitations, we propose a novel two-stage framework that optimizes strategy selection preferences at each dialogue turn. We first leverage Monte Carlo Tree Search to construct ESC-Pro, a high-quality …

Context-Aware Hierarchical Taxonomy Generation For Scientific Papers Via Llm-Guided Multi-Aspect Clustering, Kun Zhu, Lizi Liao, Yuxuan Gu, Lei Huang, Xiaocheng Feng, Bing Qin

Research Collection School Of Computing and Information Systems

The rapid growth of scientific literature demands efficient methods to organize and synthesize research findings. Existing taxonomy construction methods, leveraging unsupervised clustering or direct prompting of large language models (LLMs), often lack coherence and granularity. We propose a novel context-aware hierarchical taxonomy generation framework that integrates LLM-guided multi-aspect encoding with dynamic clustering. Our method leverages LLMs to identify key aspects of each paper (e.g., methodology, dataset, evaluation) and generates aspect-specific paper summaries, which are then encoded and clustered along each aspect to form a coherent hierarchy. In addition, we introduce a new evaluation benchmark of 156 expert-crafted taxonomies encompassing 11.6k …

Temporal And Heterogeneous Graph Neural Network For Remaining Useful Life Prediction, Zhihao Wen, Yuan Fang, Pengcheng Wei, Fayao Liu, Zhenghua Chen, Min Wu

Research Collection School Of Computing and Information Systems

Predicting remaining useful life (RUL) plays a crucial role in the prognostics and health management of industrial systems that involve a variety of interrelated sensors. Given a constant stream of time-series sensory data from such systems, deep learning (DL) models have risen to prominence at identifying complex, nonlinear temporal dependencies in these data. In addition to the temporal dependencies of individual sensors, spatial dependencies emerge as important correlations among these sensors, which can be naturally modeled by a temporal graph that describes time-varying spatial relationships. However, the majority of existing studies have relied on capturing discrete snapshots of this temporal …

Global Cooling Watch 2025, Omar Abdelaziz, Ray Gluckman, Ian Hamilton, Radhika Khosla, Lily Riahi

Research Collection College of Integrative Studies

The second edition of UNEP’s Global Cooling Watch Report takes a deep dive into one of the decade’s most urgent challenges: surging heat, soaring cooling demand, and stark inequalities in access. Produced by the UNEP-led Cool Coalition, the report provides a comprehensive assessment of the rapidly growing global demand for cooling and the need for climate-friendly solutions to the issue. The 2025 report builds on the first Global Cooling Watch (2023), which established the Sustainable Cooling Pathway framework. The new edition deepens analysis of intensifying extreme heat and its effect on cooling demand, improved assessment of passive cooling, and coverage …

Ai Companions And The Lessons Of Family Law, Clare Huntington

Faculty Scholarship

Virtual friends and lovers powered by artificial intelligence are rapidly moving to the center of our emotional and social lives. Millions of people turn to AI companions every day for conversation, romance, sexual intimacy, therapy, and education. AI companionship holds promise, potentially reducing loneliness, supporting people without access to mental health treatment, helping students learn, and offering a judgment-free space for sensitive conversations. But AI companionship also raises significant concerns. The technology's addictiveness may exacerbate loneliness and can undermine human relationships. Therapy bots may prove more harmful than helpful. AI companions can be emotionally abusive. And their access to the …

Attorneys And Ai: How Lawyers Use Artificial Intelligence And Analyze Its Impacts, Matthew I. Hall, Christian Turner, Eddie A. Gomez Schieber, Nathaniel Kite, Ari Schlesinger

Scholarly Works

AI systems are testing lawyers' professional ethics obligations of competence, confidentiality, and candor. In the legal profession, the widespread availability of AI systems presents opportunities, like improving the review of documents during the discovery stage of a lawsuit, and challenges, illustrated by the handful of high-profile incidents where lawyers submitted legal briefs in court citing and describing fictitious cases based on AI-generated output. We conducted interviews with 44 legal professionals in the U.S. to understand how attorneys are making sense of AI technology and the impacts these technologies are having on their profession, legal ethics, and legal institutions. We describe …

Ecophysiological Benefits Of Industrial Organic Wastes On Alfalfa Yield And Stress Mitigation In Saline Soils, Shugao Fan, Zhuanzhuan Ma, Jiawei Wu, Tianhui Yang, Jincheng Hao, Shumei Chen, Xutong Hu, Ying Zhao

School of Mathematical & Statistical Sciences Faculty Publications

Rising soil salinity and water scarcity demand sustainable solutions to maintain crop productivity. This study evaluated four agro-industrial organic amendments—fish emulsion, neem cake, coffee grounds, and seaweed extract on alfalfa (Medicago sativa) under combined salinity and drought stress, assessing their effects on soil respiration, plant physiology, and yield. Soil CO₂ efflux varied significantly among treatments: coffee grounds induced the highest microbial activity (6.2 μmol m⁻² s⁻¹), suggesting rapid decomposition, while neem cake exhibited stable emissions (3.8 μmol m⁻² s⁻¹), indicating slower organic matter turnover. Fish emulsion showed intermediate dynamics, peaking at 4.8 μmol m⁻² s⁻¹ by week 4, …

Image Captioning Through The Lens Of The Gricean Maxims: Generating Meaningful And Relevant Image Descriptions, Annika Lindh

Doctoral

Image captioning models enable us to automatically generate natural language image descriptions for previously unseen images. It combines the two fields of computer vision and natural language generation, allowing models to interpret the con tent of an image and communicate that knowledge through natural language text.

Research into image captioning has the potential benefit of reducing the gap in digital information availability between fully sighted individuals and those who are visually impaired. However, automatically generated captions often fail to provide the required level of detail and specificity to achieve this goal. Furthermore, current standard evaluation methods are insufficient at measuring …

Carbon–Neutral Granular Filtration For Sustainable And Safe Rainwater Harvesting In Urban Malaysia, Mohammad Nur-E-Alam, Md Helal Uddin, Saurav Dixit, Boon Kar Yap, Mohammad Tariqul Islam, Nowshad Amin

Research outputs 2022 to 2026

This work aims to design a granular filter-based carbon–neutral rainwater treatment system. Granular filters are capable of cleaning rainwater while leaving a carbon–neutral trace to promote environmentally friendly rainwater collection techniques by examining the filtration performance and impact on the environment. The elimination of pollutants and impurities from collected rainwater through granular filters highlights the significance of meeting water quality requirements. The system uses three filters (F1, F2, and F3) for the treatment process where palm (oil) fruit shell-activated carbon, coconut shell-activated carbon, coarse sand, and fine sand are used as raw materials. The physicochemical quality of rainwater (harvested at …

Deep Reinforcement Learning For Solving The Stochastic E-Waste Collection Problem, Dang Viet Anh Nguyen, Aldy Gunawan, Mustafa Misir, Kwan Hui Lim, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

With the growing influence of the internet and information technology, Electrical and Electronic Equipment (EEE) has become a gateway to technological innovations. However, discarded devices, also called e-waste, pose a significant threat to the environment and human health if not properly treated, disposed of, or recycled. In this study, we extend a novel model for the e-waste collection in an urban context: the Heterogeneous VRP with Multiple Time Windows and Stochastic Travel Times (HVRP-MTWSTT). We propose a solution method that employs deep reinforcement learning to guide local search heuristics (DRL-LSH). The contributions of this paper are as follows: (1) HVRP-MTWSTT …

Instructors’ Strategies In Creating And Implementing Constructivist Llm-Based Learning Activities, Emily Aurelia, Shun Yi Yeo, Michelle Lui, Effie Lai-Chong Law, Anthony Tang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly being integrated into educational settings, enabling more adoption of constructivist teaching and learning approaches in classrooms. This paper explores the strategies instructors are currently using to incorporate LLMs into learning activities that align with constructivist principles, which emphasize that learners actively construct their own knowledge. Through interviews with nine instructors who have designed eleven distinct LLM-based activities and using reflexive thematic analysis, this study identifies various types of learning activities with respect to four different aspects of the constructivist learning theory. The strategies employed and challenges faced to foster constructivist student-LLM interaction were also …

Bioaccumulation Pattern Of Per- And Polyfluoroalkyl Substances (Pfas) In Fish Tissues From Two Freshwater Systems, Margaret D. Taiwo, Husam Kafeenah, David D. Duvernell, Michael O. Eze

Biological Sciences Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFAS) are known for their persistence, ubiquity, bioaccumulation in different matrices of the environment and their detrimental effect on human health. In this study, we used EPA 1633 to examine the prevalence of ten PFAS compounds in two freshwater systems and investigated their bioaccumulation pattern across different tissues of grass carp fish (Ctenopharyngodon idella), common carp (Cyprinus carpio), and flathead catfish (Pylodictis olivaris). Among the PFAS compounds analyzed, PFBS exhibited the highest concentration in the freshwater sample, exceeding the U.S. EPA regulatory limit of 4 ng/L for drinking water. The total PFAS concentrations in the muscle, …

Enhancing The Acceptability Of Decision-Making System Using Xai Case: Crime Profiling System, Mohamed Saeed Al Shamsi

Theses

In the current world, we need to place more emphasis on how easily interpretable, accurate, and acceptable data analysis results are, given that essential operations in law enforcement, among other sectors, are backed up by the use of complex computing systems. Crime profiling systems that use crime data for profiling encounter major problems because they depend on algorithm-based methods. These methods can be ambiguous and inaccurate, leading to low public acceptability. The study investigates major problems with Complex Crime profiling systems (CPS) because their unexplained algorithms result in system performance issues and public scepticism. XAI provides a solution to handle …

Enhanced Privacy Preserving Healthcare Data Management With Federated Learning Using Homomorphic Encryption, Omar Abdulla Ali

Theses

Federated Learning (FL) is a decentralized approach of machine learning on multiple clients jointly training models without sharing their raw data, which drastically improves privacy and enhance protection against security breach. This is particularly critical in the healthcare sector, where hospitals and medical institutions are often unable to exchange patient records due to strict privacy regulations and data-management policies. However, there is still a risk of privacy breach when clients send their model updates to the central server, because if a model update is intercepted or analyzed by a malicious entity, it could be used to recover sensitive data using …

The Simulation Of Hyperspectral Observations By The Upcoming Spacecraft "Arab Satellite 813", With The Radiative Transfer Model Sciatran, Sara Maher Alhasan

Theses

The Arab Satellite 813, which is scheduled to be launched in 2025/2026 by the UAE Space Agency, is set to increase earth observation and monitor the climate across the middle East and North Africa (MENA) region. This study uses the SCIATRAN radiative transfer model which was originally developed for the Envisat mission to simulate the hyperspectral observation specifically tailored for the satellite's payload. Using calibrations that were used by the previous research in their SCIATRAN V4.6 study and adjusting parameters like the Leaf Area Index (LAI), a simulation which agreed robustly with the benchmarks set by the previous research was …

A Century Of Sediment Metal Contamination Of Mar Menor, Europe's Largest Saltwater Lagoon, Irene Alorda-Montiel, Valentí Rodellas, Ariane Arias-Ortiz, Albert Palanques, Andrea G. Bravo, Júlia Rodriguez-Puig, Aaron Alorda-Kleinglass, Carlos Green-Ruiz, Marc Diego-Feliu, Pere Masqué, Javier Gilabert, Jordi Garcia-Orellana

Research outputs 2022 to 2026

Coastal enclosed ecosystems, such as lagoons, are vulnerable to anthropogenic impacts because they favor the accumulation of contaminants from the surrounding watersheds, particularly in their sediments. Europe's largest saltwater lagoon, the Mar Menor (SE, Iberian Peninsula), is a highly impacted ecosystem and the first in the continent to be granted personhood rights. Based on a high-resolution spatial and temporal dataset, we present the historical reconstruction of metal contamination in this ecosystem during the last century. Our results highlight that sediment metal contamination has been mainly driven by the development of the mining industry in the nearby Sierra Minera de Cartagena-La …

How Fair Workweek Laws Affect Labor Markets: A New York City Case Study, Joseph Pickens, Aaron Sojourner

Employment Research Newsletter

No abstract provided.

Establishing A Framework Of Best Management Practices For Sustainable Water Quality: Integration Of Technology And Remote Sensing, Mason L. Marcantel

LSU Master's Theses

Water quality security is a complex management issue that is constantly challenged by factors of seasonal variability in climate change, urban population growth, and agricultural intensification. These factors warrant the need for innovative technological adaptations to management practices that integrate remote monitoring, predictive modeling, and sustainable resource utilization. This study establishes a framework for sustainable water quality practices through the integration of remote sensing technology for urban wastewater treatment and agricultural irrigation systems. This dual-site research study explores seasonal water quality dynamics and technological interventions to create a more proactive approach to water quality security.

In the first study, water …

Re: 3rd Quarter 2025 – Interim Site-Wide Surface Water Monitoring Data Report Silver Bow Creek Butte Area Npl Site, Butte Priority Soils Operable Unit Consent Decree-Civil Action No. Cv 89-039-Bu-She, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Causal Predictive Modeling Of Survival Of Lung And Bronchus Cancer Patients Diagnosed During 2010–2011 In Texas, Zeinab Mohamed, Sidketa Fofana, Everardo Cobos, Manish K. Tripathi, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

Background: Lung and Bronchus cancer is the most fatal type of cancer in the United States. According to the American Cancer Society, there were more than 127,000 deaths from lung cancer in 2023. Lung cancer care cost 23.8 billion dollars in 2020. In Texas, only 22.8% of lung cancer patients survived 5 years or more past diagnosis based on 2012-2018 data.

Aim: This study evaluates the survival length of lung and bronchus cancer patients in Texas using advanced statistical and machine learning methods applied to an 11-year cohort study from Surveillance, Epidemiology, and End Results Program. It also quantifies the …

Persepsi Mahasiswa Ilmu Perpustakaan Terhadap Penggunaan Perangkat Ai Llm Dalam Pencarian Informasi, Danisya Laila Zahra, Muhamad Prabu Wibowo

Jurnal Ilmu Informasi, Perpustakaan, dan Kearsipan

The increasing use of generative artificial intelligence (AI) among university students is driving changes in the way they seek and manage information, including in academic contexts. ChatGPT and DeepSeek AI are two AI platforms based on Large Language Models (LLMs) that are increasingly utilized as tools to support information seeking processes. This study aims to analyze the preferences of students from the Library and Information Science Program, Faculty of Humanities, Universitas Indonesia (FIB UI), in using these two platforms. The research employs a case study method with a qualitative approach, involving in-depth interviews with ten students. This study explores their …

Mosquito Classification And Explainability From Image Data Via Deep Learning Techniques, Farhat Binte Azam

USF Tampa Graduate Theses and Dissertations

According to the World Health Organization (WHO), mosquitoes are the deadliest animals on Earth, responsible for more human deaths annually than any other species. Mosquito-borne illnesses continue to pose severe risks to global health. In 2015 alone, there were an estimated 214 million malaria cases worldwide. Similarly, a 2016 report from the Centers for Disease Control and Prevention (CDC) revealed that Puerto Rico’s Department of Health received over 62,500 suspected cases of Zika, with 29,345 confirmed positive cases. In 2019, Southeast Asia experienced its worst dengue outbreak in recorded history. Of the approximately 4,500 mosquito species distributed across 34 genera, …

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Fourth Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Revised Draft Final Annual Operations And Maintenance (O&M) Report: Butte Treatment Lagoon (Btl) System – 2023, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Rewilding The Built Environment: Navigating Economic, Political, And Social Barriers To Urban Ecological Restoration, Carly E. Smith

PANDION: The Osprey Journal of Research and Ideas

Urban rewilding offers a nature-based approach to restoring ecological processes in cities while advancing climate resilience, biodiversity, and public well-being. Unlike conventional green infrastructure, rewilding allows ecosystems to develop with minimal intervention, emphasizing succession, complexity, and long-term adaptability. This paper examines the political, economic, and social factors that frame how rewilding is understood and implemented in urban planning. Governmental frameworks often prioritize order, predictability, and short-term results, making it difficult to accommodate the uncertainty and ecological complexity that rewilding requires. Economic models struggle to capture its long-term value, frequently overlooking ecosystem services or reconciling competing land uses. Social perceptions of …

Italian Mathematics Prison Teachers’ Perspective On The Teaching/Learning Of Mathematics In Prison School, Andrea Maffia, Luca Decembrotto, Chiara Giberti, Federica Mennuni, Gabriella Pocalana, Silvia Regola, Agnese Telloni

Journal of Prison Education Research

Teaching in the prison context is characterized by a high complexity level; it is a multifaced activity influenced by several factors depending on the specific context. We present a preliminary but overall picture of schooling in Italian prisons by considering teachers’ reflections regarding their experiences in teaching mathematics in correctional facilities. To address the gap in the current literature on this issue, we conducted a SWOT analysis on the reflection provided by a group of nine Italian mathematics teachers who teach in different prisons and with different experiences and backgrounds. Their reflection allowed us to identify and describe six theory-driven …

Reliable Detection Of Sf6breakdown Byproducts Using 2d Non-Hexagonal Carbon Allotrope Nanosheets, Pedro Elias Priori Spalenza, Fábio Arthur Leão De Souza, Debora C.M. Rodrigues, Rodrigo G. Amorim, Cesar E.P. Villegas, Wanderlã L. Scopel, Ravindra Pandey

Michigan Tech Publications

Sulfur hexafluoride (SF6), widely used as an insulating gas in the power industry, decomposes during long-term operation into byproducts such as H2S, SO2, SO2F2, and SOF2. Reliable detection of these compounds is essential, since their type and concentration provide diagnostic signatures of faults in gas-insulated switchgear. We employ density functional theory combined with nonequilibrium Green’s function calculations to evaluate pristine two-dimensional carbon allotropes with nonhexagonal rings, namely Graphene+, T-graphene, and Biphenylene, as potential field-effect nanosensors. To characterize the surfaces’ atomic structures, we simulated scanning tunneling microscopy images for filled states. Each surface exhibits a distinct brightness pattern that allows its …