Physical Sciences and Mathematics Commons^™

Variation In Food Web Reliance On Green And Brown Energy Pathways Across Ecosystem Gradients, James W. Sturges, W. Ryan James, Ryan J. Rezek, Rolando O. Santos, Mack White, Gina A. Badlowski, Shakira Trabelsi, Jordan Massie, Justin S. Lesser, Joel C. Trexler, James Nelson, Jennifer S. Rehage

Marine Science

Aquatic food webs typically include highly coupled fast, ‘green’ energy pathways driven by algae or phytoplankton and slower, ‘brown’ energy channels driven by detritus and terrestrial plants. Quantifying how much energy biological communities obtain from each of these pathways is essential, particularly across multiple interconnected food webs over large areas, because energy dynamics are known to influence ecosystem structure and function. Despite their importance, few studies track variance in energy channel contributions to food webs across interconnected habitats during distinct hydrologic seasons. In this study, we used tri-isotope Bayesian mixing models to quantify seasonal contributions of energy pathways to consumers …

A Runtime-Adaptive Transformer Neural Network Accelerator On Fpgas, Ehsan Kabir, Jason D. Bakos, David Andrews, Miaoqing Huang

Electrical Engineering and Computer Science Faculty Publications and Presentations

Transformer neural networks (TNN) excel in natural language processing (NLP), machine translation, and computer vision (CV) without relying on recurrent or convolutional layers. However, they have high computational and memory demands, particularly on resource constrained devices like FPGAs. Moreover, transformer models vary in processing time across applications, requiring custom models with specific parameters. Designing custom accelerators for each model is complex and time-intensive. Some custom accelerators exist with no runtime adaptability, and they often rely on sparse matrices to reduce latency. However, hardware designs become more challenging due to the need for application-specific sparsity patterns. This paper introduces ADAPTOR, a …

Hybrid Server–Ai Architecture For Persistent Generative Game Worlds: Achieving Scalable, Consistent, And Low-Latency Interactive Environments, Jay Ratican, James Hutson

Faculty Scholarship

Generative artificial intelligence has demonstrated remarkable capabilities in real-time content creation for interactive entertainment, yet current implementations struggle with the persistence, consistency, and scalability demanded by modern multiplayer and long-form gaming environments. This paper presents a hybrid server–AI architecture that fuses the deterministic reliability of authoritative multiplayer server frameworks with the creative flexibility of state-aware generative systems. The proposed three-tier design consists of (1) a deterministic server backend leveraging technologies such as Unity Netcode for GameObjects, Unreal Engine 5’s dedicated servers, and Amazon GameLift to maintain authoritative and persistent world state; (2) a state-aware generative layer responsible for producing real-time …

The Case For Ai Authorship In Copyright Law, Cheng Lim Saw, Duncan Lim

Research Collection Yong Pung How School Of Law

Today, with generative AI, literary and artistic works can be created almost effortlessly. There is at present intense debate as to whether works generated by AI – broadly categorised as “AI-assisted” and “AI-generated” works – ought to attract copyright protection. AI-assisted works are those that involve some degree of human intervention. Where AI-generated works are concerned, however, such works are created autonomously by the AI itself with minimal (de minimis) input from an identifiable human being. Presently, it is generally accepted that AI-generated works do not attract copyright protection for want of a human author. This article examines whether it …

Leveraging Molecular Mechanisms Of Desorption To Enhance Pfas Bioavailability In Contaminated Soils, Husam Kafeenah, Margaret D. Taiwo, Patrica Ivy Agorsor, Michael O. Eze

Chemistry Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFAS) are known for their strong binding properties to soil matrices owing to their amphiphilic properties. While most studies focus on the search for novel PFAS bio degraders, our knowledge of sustainable biomolecules that could drive PFAS desorption and make them more bioavailable is limited. This study investigated the effectiveness of rhamnolipids and organic acids in desorbing PFAS compounds from contaminated soil. Rhamnolipids (25 mg/L) significantly enhanced the release of PFAS compounds from soil, achieving up to 90 % desorption. Acetic acid provided 60–90 % desorption efficiency for most of the PFAS studied, except for PFDA …

Defending Code Language Models Against Backdoor Attacks With Deceptive Cross-Entropy Loss, Guang Yang, Yu Zhou, Xiangyu Zhang, Xiang Chen, Terry Yue Zhuo, David Lo, Taolue Chen

Research Collection School Of Computing and Information Systems

Code Language Models (CLMs), particularly those leveraging deep learning, have achieved significant success in code intelligence domain. However, the issue of security, particularly backdoor attacks, is often overlooked in this process. The previous research has focused on designing backdoor attacks for CLMs, but effective defenses have not been adequately addressed. In particular, existing defense methods from natural language processing, when directly applied to CLMs, are not effective enough and lack generality, working well in some models and scenarios but failing in others, thus fall short in consistently mitigating backdoor attacks. To bridge this gap, we first confirm the phenomenon of …

Supporting Data – Urban Stream, Cardinal Court, Isu, Normal, November 9, 2023 To May 1, 2025, Eric Wade Peterson, Ava Miller

Faculty Publications - Geography, Geology, and the Environment

Between November 9, 2023 to May 1, 2025, water samples were collected upstream and downstream along a segment of a stream adjacent to Cardinal Court on the Illinois State University campus. At each location, samples were collected at the surface. In-situ measurements of Dissolved Oxygen, Specific Conductance, and Temperature were recorded with a YSI 85. Anion samples were analyzed using a Ion Chromatograph for fluoride (F^-), chloride (Cl^-), nitrate as nitrogen (NO3-N), phosphate (PO₄^3-), and sulfate (SO₄^2-). The available dataset provides the recorded field parameters and the analyzed ion concentrations.

Hold Paramount The Health, Safety, And Welfare Of The Public And The Planet, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Flips In Two-Dimensional Hypertriangulations, Herbert Edelsbrunner, Alexey Garber, Mohadese Ghafari, Teresa Heiss, Morteza Saghafian

School of Mathematical & Statistical Sciences Faculty Publications

We study flips in hypertriangulations of planar points sets. Here a level-k hypertriangulation of n points in the plane is a subdivision induced by the projection of a k-hypersimplex, which is the convex hull of the barycenters of the (k−1)-dimensional faces of the standard (n−1)-simplex. In particular, we introduce four types of flips and prove that the level-2 hypertriangulations are connected by these flips.

Demographic And Other Correlates Of Non-Prescription Drug Use Among College Students During The Covid-19 Pandemic, Subi Gandhi, Sidketa Fofana, Md Rafiul Islam, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

Background and objectives: Substance use among college students in the U.S. remains a pressing concern and may have intensified during the COVID-19 pandemic due to increased stress, uncertainty, and academic disruptions. This study investigates the relationship between non-prescription drug use and various demographic, mental health, and behavioral factors among college students during the pandemic's early stages.

Methods: Data were collected through online and in-person surveys in the summer semester of 2021. Behavioral health was assessed using validated instruments: the Patient Health Questionnaire-9 (PHQ-9) for depression and the Drug Abuse Screening Test-20 (DAST-20) for substance use. Demographic and behavioral variables were …

Final 2022 Unreclaimed Sites Sampling: Ur-06 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2022 Unreclaimed Sites Sampling: Ur-28 Site Evaluation Summary Reportfinal 2022 Unreclaimed Sites Sampling: Ur-28 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2022 Unreclaimed Sites Sampling: Ur-13 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 32 – Corra 2 Dump Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 30 – Atlantic-1 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 38 – Sister Dump Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Derivation Of An Updated Brief Multivariable Prediction Model To Detect Panic-Related Anxiety In Emergency Department Patients With Cardiopulmonary Complaints, Sharon C. Sung, Felicia J. L. Ang, Arul Earnest, Leslie E. C. Lim, Shreshtha Jolly, Gilaine Rui Ng, A. John Rush, Marcus E. H. Ong

Research Collection School of Social Sciences

Background Patients with panic related-anxiety (i.e., panic attacks or panic disorder) frequently present to emergency departments (EDs) with cardiopulmonary complaints but are often undiagnosed, which can lead to recurrent visits and prolonged distress. This study aimed to derive a new symptom-based multivariable diagnostic prediction model to detect panic-related anxiety in ED patients with cardiopulmonary symptoms.Methods We conducted a single-blind prospective derivation study over 15 months in the ED of a major tertiary hospital in Singapore. Patients presenting with symptoms of palpitations, chest pain, dizziness, or difficulty breathing were assessed using the Structured Clinical Interview for DSM Disorders (SCID) to diagnose …

Cyber Science Education Meets Healthcare Technology, Angela Spencer

Journal of Cybersecurity Education, Research and Practice

The research investigates how cyber science education combines with healthcare technology during the digital age to resolve a fundamental research gap in these two advancing areas. A combined approach utilizing extensive surveys and detailed interviews evaluates the functionality of learning platforms as well as cybersecurity measures and potential uses of emerging virtual reality (VR) and augmented reality (AR) tools to improve both educational and clinical environments. The research document describes its methodologies thoroughly while. The research documents multiple quantitative and qualitative results before performing its analysis, which leads to strategy development for digit. The researchers worked to find ways that …

New Asymptotics Applied To Functional Coefficient Regression And Climate Sensitivity Analysis, Qiying Wang, Peter C. B. Phillips, Ying Wang

Research Collection School Of Economics

A general asymptotic theory is established for sample cross moments of nonstationary time series, allowing for long-range dependence and local unit roots. The theory provides a substantial extension of earlier results on nonparametric regression that include near-cointegrated nonparametric regression as well as spurious nonparametric regression. Many new models are covered by the limit theory, among which are functional coefficient regressions in which both regressors and the functional covariate are nonstationary. Simulations show finite sample performance matching well with the asymptotic theory and having broad relevance to applications, while revealing how dual nonstationarity in regressors and covariates raises sensitivity to bandwidth …

One-Step Purification Of A Bioactive Pak1-Derived Peptide, Djamali Muhoza, Emily P. Esquivel, Stacy R. Hunter, Pateince S. Okoto, Thallapuranam K.S. Kumar, Paul D. Adams

Chemistry & Biochemistry Faculty Publications and Presentations

The serine/threonine kinase PAK1 serves as a mediator of cytoskeletal reorganization and cancer-related signaling downstream of the small GTPases. Due to the challenges in purifying PAK1 complexes, a 46-residue peptide from PAK1, is widely used to study PAK1-Cdc42 signaling. Traditionally, this purification involved multi-step chromatography of recombinant GST-PBD46 complexes, yielding approximately 1 mg per 1.5 L culture. In this study, a 30 min heat treatment step after thrombin cleavage was used to precipitate GST while leaving pure PBD46 in solution. This step eliminated the need for further affinity and size-exclusion chromatography steps. This improved protocol produces proteins with a 6.5-fold …

How Consistent Friendlike Conversation With Ai Companions Influences Our Attitudes And Perceptions Toward Ai: An Exploratory Experiment, Qi Hui Jerlyn Ho, Meilan Hu, Adalia Yin Hui Goh, Emma Jane Pragasam, Andree Hartanto

Research Collection School of Social Sciences

Despite skepticism and distrust in artificial intelligence (AI), it is increasingly integrated into daily life, with its potential benefits drawing interest. Yet little is known about the attitudinal and psychological effects of human–AI interactions, and whether consistent interactions with AI chatbots can change users’ attitudes and perceptions. Our within-subjects experiment (N = 52) investigated how five days of socially oriented, friendlike interactions with an AI chatbot, versus a journaling control, influenced changes in attitudes and perceptions of AI. Participants’ attitudes towards AI, trust, perceived empathy, anthropomorphism, animacy, likeability, perceived intelligence and safety, dependency, and exploratory well-being indicators were recorded. Results …

Least Squares As Random Walks: The General Case Of Arbitrary Spacing, Daniel Kestner, Alexander Kostinski

Michigan Tech Publications

Recently, we introduced the notion of a random walk based on a discrete sequence of data samples ( data walk ) and discovered a surprising link between ordinary least squares (OLS) fits to evenly sampled data and random walks. Here we generalize earlier results by showing that the slope of a linear fit to data which annuls the net area under a residual data walk equals that found by OLS for irregularly spaced data sequence. We also discover a deep connection with the orthogonality principle of estimation theory, leading to interpretation of suitably defined scalar products of data vectors as …

Air Mass Trajectories Related To Dust Storms On Mars And A Comparison Study With Spacecraft Images, Mohammad Abdulla Ahli

Theses

The Martian weather system, climate, and surface evolution are strongly influenced by dust storms, which interact with the atmospheric circulation and the planet’s surface features. In this study, selected Martian dust storms are examined using data provided by the Emirates Mars Mission (EMM) and the Mars Climate Database (MCD) to track the movement of air masses and improve understanding of how these storms develop and move across the Martian atmosphere.

The Emirates Mars Mission (EMM), together with the Mars Climate Database (MCD), provides the data needed to track the movement of air masses at different altitudes and times of the …

Removed: When Taxi Drivers Meet Dynamic Pricing: A Lesson From Singapore's Justgrab Program, Shih-Fen Cheng, Wen-Tai Hsu, Jing Li

Research Collection School Of Economics

This paper studies how dynamic pricing influences taxi drivers’ behaviors using a unique event, the inception of the JustGrab program in Singapore in 2017, which introduces dynamic pricing to some, but not all, taxi drivers. This is the first time in history that traditional taxi drivers have access to dynamic pricing. Using data covering the universe of taxi trips before and after the inception of JustGrab, we find that there is spatial reallocation that directs more taxi drivers to the previously less-served areas, that there is also a temporal reallocation that directs more taxi drivers to rush hours, as well …

Final 2022 Unreclaimed Sites Sampling: Ur-20 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

G-Trac: Graph-Textual Representations Alignment For Cold-Start Recommendations, Li Yang Chang, Yuan Fang, Ming Feng Tsai, Chuan Ju Wang

Research Collection School Of Computing and Information Systems

The cold-start problem remains a significant challenge in recommendation systems, particularly for new users or unseen items with little to no historical data. Existing methods, including graph neural networks, often struggle in such scenarios. Inspired by the success of transformer models in natural language processing, we propose G-TRAC (Graph-Textual Representations Alignment for Cold-start Recommendations), a novel approach that integrates transformer-based textual modeling with graph neural networks. By effectively leveraging both textual and structural information, G-TRAC addresses cold-start challenges more effectively. Extensive experiments demonstrate its ability to enhance recommendation quality and generalize well across diverse scenarios.

Computational Characterization Of A Recently Identified Disinfection Byproduct In Drinking Water: The Chloronitramide Anion And Its Monohydrate Complex, Thufail M. Ismail, Max R. Tucker, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

The chloronitramide anion (ClNNO₂⁻) was recently identified as disinfection byproduct in drinking water, and various quantum chemistry methods (CCSD(T), MP2, B3LYP, ωB97XD, and M06-2X) are employed in this study to characterize this negatively charged species and its monohydrate complex. Both vertical and adiabatic quantities indicate the excess electron is bound by 3–4 eV. Four ClNNO₂⁻ monohydrate minima were identified, each exhibiting double ionic hydrogen bonding. The computed ClNNO₂⁻⋯H₂O interaction approaches 15 kcal/mol, and it induces pronounced vibrational frequency shifts in both fragments. Natural bond orbital analysis shows a redistribution of …

Electric Dipole Forbidden, Quadrupole Allowed Transitions In The Pure Rotational Spectrum Of Cyclopropylchloromethyldifluorosilane, Alexander R. Davies, Abanob G. Hanna, Alma Lutas, Gamil A. Guirgis, S. A. Cooke, Garry S. Grubbs

Chemistry Faculty Research & Creative Works

In a recent publication, some electric dipole forbidden, quadrupole allowed ΔJ = +2 and x-type transitions were observed in the chirped-pulse Fourier transform microwave spectrum of two conformations of cyclopropylchloromethyldifluorosilane. Many of these transitions arise from a handful of mixed states and mechanisms are proposed through which these transitions become weakly allowed. Observations of electric dipole forbidden, quadrupole allowed transitions in rotational spectra are unusual for molecules which contain a chlorine nucleus owing to the small quadrupole moment of ³⁵Cl and ³⁷Cl; thus, we believe we are the first to observe x-type transitions arising from perturbations caused by …

Atmospheric Circulation Reconstructions Over The Earth (Acre) 2025: Climate Data Recovery, Fiona Williamson

Research Collection College of Integrative Studies

On 15-16 September 2025, Singapore Management University hosted the annual Atmospheric Circulation Reconstructions over the Earth (ACRE, www.met-acre.net/) workshop, ’ACRE 2025: Climate Data Recovery’, chaired by Fiona Williamson, Rob Allan and Praveen Teleti. The 2-day event took place at the College of Integrative Studies and saw around 30 participants from multi-disciplinary backgrounds all working in meteorological data rescue (DaRe, www.community.wmo.int/en/data-rescue-projects-and-initiatives-dare) sharing their latest work and discoveries. Speakers were a mix of climate scientists and historians, archivists and historical climatologists from across the globe. ACRE has been operating for 18 years under Professor Rob Allan, formerly of the UK Meteorological Office …

Hybrid Data-Driven Cement-Stabilized Soil Design: An Integration Of Machine Learning, Multi-Objective Optimization, And Life Cycle Assessment, Chikezie Chimere Onyekwena, Yunli Li, Ikenna J. Okeke, Ubani Obinna Uzodimma, Monday Uchenna Okoronkwo, Wenping Wu

Chemical and Biochemical Engineering Faculty Research & Creative Works

Soil stabilization is crucial in geotechnical engineering, yet conventional methods are often time-consuming, resource-intensive, and environmentally unsustainable. Despite growing interest in Machine Learning (ML) and optimization tools for mix design, few studies integrate these methods with decision-making techniques and environmental assessment to support practical implementation. This study proposes a hybrid data-driven framework for predicting strength, optimizing mix compositions, and evaluating environmental impacts via life cycle assessment of cement-stabilized soft soils. Six ML models were evaluated, and the top-performing eXtreme Gradient Boosting (XGB) model was further improved using the Grey Wolf Optimizer (GWO). The optimized XGB-GWO model, integrated with a polynomial …