Digital Commons Network^™

A Novel Deliberative Multicriteria Evaluation Approach To Ecosystem Service Valuation, Georgia Mayrommati, Mark E. Borsuk, Richard B. Howarth

New Hampshire EPSCoR

Although efforts to address ecosystem services in decision making have advanced considerably in recent years, there remain challenges related to valuation. In particular, conventional economic approaches have been criticized for their inability to capture the collective nature of ecosystem services, for their emphasis on monetary metrics, and the difficulty of assessing the value of ecosystem services to future generations. We present a deliberative multicriteria evaluation (DMCE) method that combines the advantages of multicriteria decision analysis with a deliberation process that allows citizens and scientists to exchange knowledge and evaluate ecosystem services in a social context. Compared with previous applications we …

Metarag: Identifying Website Owner Using Meta-Path-Guided Dynamic Graph Retrieval-Augmented Generation, Cheng Tu, Yunshan Ma, Bingyang Guo, Qianyu Li, Yang Li, Min Zhang, Fan Shi, Xiang Wang

Research Collection School Of Computing and Information Systems

Website owner identification aims to link websites to their real-world owners, which is crucial for credibility assessment and information provenance in information retrieval and vital for applications in cybersecurity, Internet governance, and digital regulation. Existing approaches for website owner identification primarily rely on querying infrastructure registration records or analyzing webpage content. However, these methods often fail due to incomplete or outdated registration records and sparse webpage content. We observe that inter-website relationships, derived from shared infrastructure data such as primary domains, IP blocks, and geolocations, can provide valuable but underutilized ownership cues. To exploit this insight, we propose MetaRAG, a …

Mergerepair: An Exploratory Study On Merging Task-Specific Adapters In Code Llms For Automated Program Repair, Meghdad Dehghan, Jie Jw Wu, Fatemeh H. Fard, Ali Ouni

Michigan Tech Publications

Large Language Models (LLMs) have shown high capabilities in several software development-related tasks such as program repair, documentation, code refactoring, debugging, and testing. However, training these models requires massive amount of data and significant computational resources. Adapters are specialized, small modules designed for parameter efficient fine-tuning of LLMs for specific tasks, domains, or applications without requiring extensive retraining of the entire model. These adapters offer a more efficient way to customize LLMs for particular needs, leveraging the pre-existing capabilities of the large model. Model (and adapter) merging have emerged as a technique to develop one model capable of multiple tasks, …

Ai Failures In The Eyes Of The Downstream Developer: A First Look At Concerns, Practices, And Challenges, Haoyu Gao, Mansooreh Zahedi, Wenxin Jiang, Hong Yi Lin, James C. Davis, Christoph Treude

Research Collection School Of Computing and Information Systems

With the advancement of AI models, more software systems are adopting AI as a component to facilitate automation. Pre-trained models (PTMs) have become a cornerstone of AI-based software, allowing for rapid integration and development with lower training cost. However, their adoption also introduces failure modes such as data leakage and biased outputs, that may require careful handling by downstream developers. While previous research has proposed taxonomies of these technical concerns and various mitigation strategies, how downstream developers address these issues during the development of general AI-based software when reusing PTMs remains unexplored. Understanding downstream developers’ perspectives is essential because they …

Bridging The Gap Between Career Expectations Versus Labor Market Realities, Reinette P. Madrid, Grethel T. Ledesma, Ignatius Aryono Putranto, Jyro B. Triviño

Leadership and Strategy Faculty Publications

Most students lack awareness regarding the labor market outcomes for their chosen college majors. This study aims to answer what factors affect the career expectations of graduating students at Quezon City University and how these expectations align with the prevailing labor market situation. It employed descriptive, causal, and explanatory research using a sample of 108 respondents from fourth-year information technology students for the school year 2021 to 2022. Eight of the nine null hypotheses were rejected by employing multinomial logistic and linear regression. Student fixed effects and other labor market outcomes significantly predicted salary, estimated stability, and estimated skills in …

Logupdater: Automated Detection And Repair Of Specific Defects In Logging Statements, Renyi Zhong, Yichen Li, Jinxi Kuang, Wenwei Gu, Yintong Huo, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Developers write logging statements to monitor software runtime behaviors and system state. However, poorly constructed or misleading log messages can inadvertently obfuscate actual program execution patterns, thereby impeding effective software maintenance. Existing research on analyzing issues within logging statements is limited, primarily focusing on detecting a singular type of defect and relying on manual intervention for fixes rather than automated solutions.To address the limitation, we initiate a systematic study that pinpoints four specific types of defects in logging statements (i.e., statement code inconsistency, static dynamic inconsistency, temporal relation inconsistency, and readability issues) through the analysis of real-world log-centric changes. We …

Constitutional Limits On Occupational Licensing Bans As Collateral Consequences Of A Criminal Conviction, Imran Rabbani

Student Works

No abstract provided.

Beyond The Cash Kickback: Contractual Control As Remuneration In Private-Equity-Backed Physician Practices, Maxwell Dandrea

Student Works

No abstract provided.

Originalism’S Impact On The Sovereignty Of Indian Nations, Julian Allber

Student Works

No abstract provided.

Bodily Autonomy And Involuntary Servitude: Applying The Thirteenth Amendment To Restrictions On Abortion In The Case Of Pregnancy Induced By Rape, Joseph Innocente

Student Works

No abstract provided.

Multidisciplinary Practices (Mdps) In Elder Law, Bryan Koslow

Student Works

No abstract provided.

Imsa 2027 Profile, Office Of College And Academic Counseling

IMSA Profile

The nationally-ranked Illinois Mathematics and Science Academy (IMSA) develops creative, ethical leaders in science, technology, engineering and mathematics. As a teaching and learning laboratory created by the State of Illinois, IMSA enrolls academically talented Illinois students in its tuition-free residential Academy for grades 10-12. Students are challenged with a rigorous curriculum designed to develop them into problem solvers and critical thinkers.

Notable IMSA students include YouTube Co-Founder Steve Chen, PayPal Co-Creator Yu Pan, Yelp Co-Founder Russell Simmons, SparkNotes and OkCupid Co-Founder Sam Yagan, and Hearsay Social Founder Clara Shih.

Faculty Handbook, Georgia Southern University

Faculty Handbooks

Faculty Handbook for Georgia Southern University for the 2026-2027 academic year. The Faculty Handbook is published online by the Office of the Vice President for Academic Affairs and archived in Digital Commons@Georgia Southern.

Optimizing Human Fcrn Mouse Models To Improve Pharmacokinetic Evaluation Of Antibody Drug Candidates., Gregory J. Christianson, Zachary M Howard, Samantha Kenney, Emily Lowell, Nijaguna Bethur, Derry C. Roopenian, Elena Gonzalo-Gil

Faculty Research 2026

The use of animal models that can reliably predict drug performance in human patients is critical to antibody therapeutic development. Along with assessing toxicity and efficacy, determining the pharmacokinetic (PK) properties of therapeutics in Tg32 and Tg276 mice is essential to preclinical characterization. While Tg32 mice have been well established as indispensable in their ability to model the PK properties of antibody therapeutics, their intact immunity leaves them capable of mounting anti-drug antibody responses that interfere with PK interpretation. Here, we demonstrate the negative impact anti-drug responses can have on PK parameters derived from Tg32 mice, and provide strong evidence …

Optimizing Human Fcrn Mouse Models To Improve Pharmacokinetic Evaluation Of Antibody Drug Candidates., Gregory J. Christianson, Zachary M Howard, Samantha Kenney, Emily Lowell, Nijaguna Bethur, Derry C. Roopenian, Elena Gonzalo-Gil

Faculty Research 2026

The use of animal models that can reliably predict drug performance in human patients is critical to antibody therapeutic development. Along with assessing toxicity and efficacy, determining the pharmacokinetic (PK) properties of therapeutics in Tg32 and Tg276 mice is essential to preclinical characterization. While Tg32 mice have been well established as indispensable in their ability to model the PK properties of antibody therapeutics, their intact immunity leaves them capable of mounting anti-drug antibody responses that interfere with PK interpretation. Here, we demonstrate the negative impact anti-drug responses can have on PK parameters derived from Tg32 mice, and provide strong evidence …

Using Randomization To Compare Ai And Expert-Generated Formative Assessment Questions In Medical Education, Akshat Kumar, Katie Stinson, Litao Wang, Elizabeth Nugent, Yongsu Lee, Mark Hormann, Latanya Jones Love, Toufeeq Ahmed Syed

Faculty, Staff and Student Publications

Background: AI-generated content is being used across the education spectrum and is beneficial for creating complex multiple-choice questions, such as those used in medical education. However, evaluating AI-generated content is challenging, and existing testing and evaluation methods are falling short. This study uses randomization to compare medical students' performance on and subjective evaluation of AI versus expert-generated questions. We hypothesized that there would be no difference in student performance or subjective evaluation of AI vs expert-generated questions.

Methods: We designed a single-center, randomized study where medical student participants received either one AI- or expert-generated question per day over four weeks. …

Steroid Receptor Coactivator 3-Deficient Regulatory T Cells Eradicate Multiple Solid Tumors In Syngeneic Mouse Models, Nuri Sung, Eunsu Kim, Yosef Gilad, Yuri Park, Adam M Dean, Yan Xia, Jianming Xu, Clifford C Dacso, David M Lonard, Sang Jun Han

Faculty, Staff and Students Publications

Steroid receptor coactivator 3 (SRC-3) is highly expressed in regulatory T cells (Tregs) and is important for their immunosuppressive activity. Recently, we demonstrated that disrupting SRC-3 expression in Tregs eliminates triple-negative breast cancer (TNBC) and prostate cancer in syngeneic animal models by generating an anti-tumor immune microenvironment without inducing immune-related adverse events (irAEs). Further analysis of these mice revealed that SRC-3 knockout (KO) Tregs infiltrated breast tumors and facilitated the infiltration of CD8

Limosilactobacillus Reuteri Promotes Melatonin Release From Human Intestinal Organoids Via 5′Ectonucleotidase Activity, Micah D Forshee, Erika J Nachman, Esha R Shenoy, Heather A Danhof, Ludwig Ermann Lundberg, Stefan Roos, Robert A Britton

Faculty, Staff and Students Publications

Strains of Limosilactobacillus reuteri have been used to prevent or treat various conditions; however, the mechanisms by which they exert beneficial effects are not completely understood. Infant colic is one example in which L. reuteri DSM 17938 reduces clinical symptoms. While the etiology of colic is unknown, abnormal melatonin levels in infants have been suggested as a possible contributor. L. reuteri DSM 17938 has been shown to produce adenosine from AMP via production of the extracellular enzyme 5′ectonucleotidase (5′NT). Adenosine is a potent signaling molecule that impacts several important aspects of host physiology, including the release of melatonin from the …

Comparative Assessment Of Agmd And Vmd Systems Configured With Flat Sheet And Hollow Fibre Membranes: An Energy And Exergy, Thermo-Economic, And Environmental Analysis, Hamed Kariman, Mehdi Khiadani

Research outputs 2022 to 2026

Membrane Distillation (MD) systems, particularly Air Gap Membrane Distillation (AGMD) and Vacuum Membrane Distillation (VMD) in Flat Sheet (FS) and Hollow Fibre (HF) configurations, demonstrate strong potential for freshwater production, Yet, there remains a lack of comparative studies evaluating their energy, exergy, economic and environmental performance under similar conditions. This study presents a comparative analysis of four MD systems under similar operating conditions: FS-AGMD, HF-AGMD, FS-VMD and HF-VMD, and considers their respective costs and operation in Western Australia. The analysis was performed for single-stage and multi-stage configurations of up to ten modules, both with and without Heat Recovery (HR), to …

Navigating Urgency And Innovation: How Pandemic-Era Leadership Frames The Evolving Role Of Ai In Educational Leadership, Patricia Virella, Alexandra J. Lamb

Department of Educational Leadership Scholarship and Creative Works

Purpose: This paper examines how pandemic-era leadership lessons inform the current implementation of artificial intelligence (AI) in schools, focusing on adaptive strategies, distributed leadership, and equity-focused decision-making among US school principals during crisis-driven technological change.

Design/methodology/approach: A qualitative approach was employed, drawing on semi-structured interviews with fifty public school principals conducted between 2020 and 2022. Data were coded and analyzed iteratively using distributed leadership theory to identify key themes related to technology integration, professional development and leadership practices in rapidly changing environments.

Findings: Adaptive, distributed leadership and proactive planning for digital equity were vital for effective crisis response and technology …

Firms’ Darq Readiness And Marketing Implications: A Systematic Literature Review, Ali N. Tehrani, K. Roy, Richard Gruner

Research outputs 2022 to 2026

Purpose – This study aims to systematically review literature across diverse disciplines, including marketing, management and information systems, to synthesise insights on firms’ readiness to adopt and implement DARQ technologies and their marketing implications. DARQ technologies are emerging and cutting-edge technologies, including Distributed Ledger Technology, Artificial Intelligence, Extended Reality and Quantum Computing (hence, DARQ). Design/methodology/approach – Through a systematic review of over 2, 500 papers across three databases, this study distilled a focused sample of 88 papers. It comprehensively explores the reported dimensions, antecedents, outcomes and marketing implications of firms’ readiness for DARQ technologies. Findings – This study identified three …

Public Procurement’S Role In Shaping Supply Markets: A Taxonomy Of Local Contracting Authorities’ Approaches Using The Awareness-Motivation-Capability Framework, Steven Borobia, Frederik G.S. Vos, Louise Knight, Esmee Peters, Fons Wijnhoven, Niels Uenk

Business Faculty Publications and Presentations

Purpose: Public procurement is increasingly recognised as a tool for governing and shaping supply markets. Yet we still know little about how local authorities engage in market shaping through contracting practices, especially in newly decentralized markets. This study investigates the role of awareness, motivation and capabilities (AMC) in how municipalities influence (or fail to influence) social care markets, and how these dynamics manifest in contracting practice. Design/methodology/approach We combine secondary data with semi-structured interviews conducted with procurement professionals across municipalities, regional consortia, and expert organizations. The case context is Dutch social services procurement, which transitioned to a decentralised market in …

Social Procurement As A Catalyst For Dei In Construction: Some Takeaways For Hrm?, Jennifer Waterhouse, Robyn Keast, Judy Lundy, Martin Loosemore

Research outputs 2022 to 2026

Purpose: Diversity, equity and inclusion (DEI) initiatives aim to foster workplaces where all employees feel valued and can add value. Increasingly, the success of these initiatives is influenced by environments and interactions beyond organisational boundaries, including recent backlash. Despite this, most DEI research remains focused on intra-organisational aspects and human resource management (HRM) activities. The purpose of this paper is to introduce social procurement as a novel and promising framework for advancing DEI in theory and practice through a collaborative, inter-organisational approach that has the potential to overcome institutional barriers and mitigate backlash. Design/methodology/approach: Data were collected through 15 in-depth …

Ai-Driven Collision Risk Prediction And Debris Optimization In Low Earth Orbit, Emad Alkhazraji, Mohamed E. Yahia, R. E. Tolba, N. S. Alharthi

All Works

Debris congestion and collision in low Earth orbit have become a major point of concern due to the rapid expansion of activities in that region. In this work, an AI-driven framework is developed and deployed to predict, analyze, and optimize collision risk across the altitude inclination space. Local debris object population, mass density distribution, and conjunction derived risk are computed. Then, an AI surrogate model, viz., gradient-boosted decision trees, was trained to predict collision conjunction relative probabilities and risk. Thereafter, data analysis and explain ability techniques are utilized to uncover underlying risk drivers and reveal how altitude, inclination, mass loading, …

Dblp: Noise Bridge Consistency Distillation For Efficient And Reliable Adversarial Purification, Chihan Huang, Belal Alsinglawi, Islam Al-Qudah

All Works

Recent advances in deep neural networks (DNNs) have led to remarkable success across a wide range of tasks. However, their susceptibility to adversarial perturbations remains a critical vulnerability. Existing diffusion-based adversarial purification methods often require intensive iterative denoising, severely limiting their practical deployment. In this paper, we propose Diffusion Bridge Distillation for Purification (DBLP), a novel and efficient diffusion-based framework for adversarial purification. Central to our approach is a new objective, noise bridge distillation, which constructs a principled alignment between the adversarial noise distribution and the clean data distribution within a latent consistency model (LCM). To further enhance semantic fidelity, …

Reducing Water Absorption Of Cement Mortar By Using Modified Clay Brick Waste, Nuntaporn Kongkajun, Somyote Kongkarat, Wannasa Phukutnam, Warittha Sujaritpanich, Edward A. Laitila, Parinya Chakartnarodom

Michigan Tech Publications

Cement mortar is inherently hydrophilic due to its porous structure, which allows water penetration and adversely affects its durability and long-term performance. To mitigate this issue, hydrophobic cementitious materials can be developed by incorporating hydrophobic substances during mixing to provide hydrophobic properties throughout the material, achieved by introducing a wet chemical method using stearic acid-modified clay brick waste (MCBW) as a hydrophobic agent. The MCBW is prepared by treating clay brick waste with stearic acid (SA) and subsequently used as a partial replacement for fine aggregates. The effects of the MCBW incorporation on compressive strength and water resistance are investigated. …

Mtorc2-Nav1.2 Signaling Drives Early Hyperexcitability In Alzheimer’S Disease Mouse Model, Nolan M Dvorak, Jeffrey L Noebels

Faculty, Staff and Students Publications

Hyperexcitability is a biomarker of early-stage Alzheimer’s Disease (AD) and hastens cognitive decline later in its course. Mechanistic target of rapamycin (mTOR) signaling contributes to the slope of this trajectory, as evidenced by early increased brain expression and the rescue of hyperexcitability by genetic deletion of mTOR complex 2 (mTORC2); however, a molecular mechanism directly linking mTOR signaling to membrane hyperexcitability in early-stage AD remains elusive. Here, we show that hyperactive mTOR signaling stimulates the voltage-gated Na+ channel 1.2 (Nav1.2), a previously identified downstream phosphorylation target of mTORC2 and a key regulator of membrane electrogenesis. Augmented Nav1.2 channel function induced …

Long Range Battery-Free Wireless Power Transfer Testbed For Underground Mines Iot And Lpwan Devices, Anabi Hilary Kelechi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

Underground mines are susceptible to occasional roof falls and cave-ins, temporarily destroying the existing wireless communications and telemetry infrastructure. During this temporary outage, intermittent provision of electrical energy wirelessly to the already deployed low-power wireless area networks (LPWAN) and Internet of Things (IoT) devices assumes a fundamental requirement. In this article, we propose and design a long-range far-field radio frequency (RF) wireless power transfer (WPT) testbed to power LPWAN and IoT devices at 35 m in an underground mines facility. Class AB external power amplifier (PA) was introduced to achieve a long-distance RF WPT, in the 880 MHz band. Thus, …

Efficient Charging Scheduling Through Coordination Of Electric Vehicle Platoons And Charging Stations, Liwan Qi, Bochun Wu, Shoubo Li, Yi Gong, Wei Ni

Research outputs 2022 to 2026

This paper focuses on charging allocation in a vehicle-to-infrastructure (V2I) communications-enabled electric vehicle (EV) network with heterogeneous traffic flows, where manned EVs and EV platoons coexist, and each EV platoon may have a different size and travel speed. In such a network, hybrid traffic flows pose significant challenges since platoons with multiple EVs can easily cause severe station overloading and increase the total time cost for charging service, particularly when large platoons occur. To tackle this issue, a centralized approach is proposed to plan charging allocation and optimize the velocities of manned EVs and EV platoons with the assistance of …

Over A Century Of Global Decline In The Growth Performance Of Marine Fishes, Helen F. Yan, Hannah V. Watkins, Alexandre C. Siqueira, David R. Bellwood

Research outputs 2022 to 2026

Human-driven pressures are causing large-scale changes in the ecologies and life histories of fishes. Growth performance is a composite life-history trait that captures the trade-off between two fundamental traits: growth and body size. Here, we assess the impacts of fishing and temperature on the growth performance of marine teleost fishes globally over the last century. Using 7683 growth curves encompassing 1479 species, we find a global pattern of decline in growth performance from 1908 onwards, with the greatest declines in commercially valuable fishes. Indeed, managed fisheries experienced a 9% decline in growth performance over the last century, which can equate …