Digital Commons Network^™

Performing Democracy, Carliss N. Chatman

Faculty Journal Articles and Book Chapters

American universities are frequently portrayed as stewards of democracy—sites where dissent is protected, truth is pursued, and diversity is championed. Yet these institutions often betray these ideals, especially under the pressures of donor influence, reputational risk, and political retrenchment. This Essay interrogates the internal contradictions of the university by centering one of its most guarded rituals: faculty hiring. Building on my 2021 article The Soft Shoe and Shuffle of Law School Hiring Committee Practices, I argue that hiring serves as both a performance of inclusion and a mechanism for preserving institutional whiteness, elite networks, and gatekeeping norms. I extend …

Facilitating Mortgage Modification To Save Homes And Mitigate Lender Losses, Julia Patterson Forrester Rogers

Faculty Journal Articles and Book Chapters

Homeowners in financial distress or whose homes have been damaged by natural disaster may avoid foreclosure if their lender agrees to modify the loan to reduce payments. Commercial loans may also be modified to avoid foreclosure or in response to changed circumstances or changing market conditions. Although loan modifications are generally beneficial to both borrowers and lenders, barriers to modification exist. The Consumer Financial Protection Bureau (CFPB) has addressed some of the roadblocks to residential loan modifications by regulating the procedures that mortgage servicers must follow in dealing with delinquent borrowers, but the CFPB and its regulations are at risk …

Chat M.D., Nathan Cortez

Faculty Journal Articles and Book Chapters

Large language models (LLMs) such as Claude and ChatGPT are the most powerful artificial intelligence (AI) systems ever created, and they are being used to diagnose and treat patients. But LLMs have been shown to be unreliable, unpredictable, and unsafe on occasion. New AI guidelines recommend hundreds of standards, such as ‘transparency’, ‘trustworthiness’, and ‘safety’. But there is deep uncertainty whether these are sufficient. The literature focuses mostly on which standards best suit AI models, not on how to transmute standards into law. This article does that by considering AI guidelines as a starting point, then evaluating whether existing frameworks …

Let’S Modify Safety Valve To Value Family Ties, Laura Ginsberg Abelson

Faculty Journal Articles and Book Chapters

Federal sentencing law has long struggled to balance the breadth of drug conspiracy liability with the prin­ciple of proportional punishment. The statutory “safety valve” provision, codified at 18 U.S.C. § 3553(f) and mirrored in the U.S. Sentencing Guidelines, was designed to provide relief from mandatory minimum sentences for low- level, nonviolent offenders. Yet its requirement that defendants disclose all information concerning the offense sometimes places family-member codefendants in an untenable position: they may avoid harsh penalties only by incriminating loved ones. The requirement also conflicts with other provisions of the Guide­lines that provide guidelines reductions, but not relief from mandatory …

Rethinking Courtroom Presence In The Virtual Era, Jenia Iontcheva Turner

Faculty Journal Articles and Book Chapters

Technological innovation has made virtual appearances by criminal defendants increasingly common. These appearances have advanced efficiency but also raised questions about the scope of both the right and the duty of defendants to be physically present in court. Should judges, for example, be allowed to hold virtual arraignments, even if a defendant wishes to appear in person? Can defendants opt for virtual appearances at will? While courts are beginning to address these questions, they have yet to develop a coherent framework to evaluate when virtual appearances are constitutional and appropriate. This Article seeks to contribute to this project by examining …

Negotiated Outcomes And Abbreviated Trials In Criminal Cases: Balancing Fairness And Efficiency In Three Legal Systems, Michele Caianiello, Jenia I. Turner, Thomas Weigend

Faculty Journal Articles and Book Chapters

Facing expanded criminal dockets, justice systems around the world are looking for ways to expedite proceedings and save resources while still offering credible procedures for adjudicating criminal cases. In the United States, defendants tend to face an all-or-nothing choice between two alternatives: a full trial at which all relevant evidence is presented and examined; or a plea bargain leading to a conviction without any presentation of evidence and the waiver of the defendant’s procedural rights in exchange for a reduced sentence. Even in routine misdemeanor cases, a full trial requires substantial expenditures of resources, and its procedural complexity may be …

Physics-Informed Temperature Prediction Of Lithium-Ion Batteries Using Decomposition-Enhanced Lstm And Bilstm Models, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

Accurately forecasting the operating temperature of lithium-ion batteries (LIBs) is essential for preventing thermal runaway, extending service life, and ensuring the safe operation of electric vehicles and stationary energy-storage systems. This work introduces a unified, physics-informed, and data-driven temperature-prediction framework that integrates mathematically governed preprocessing, electrothermal decomposition, and sequential deep learning architectures. The methodology systematically applies the governing relations to convert raw temperature measurements into trend, seasonal, and residual components, thereby isolating long-term thermal accumulation, reversible entropy-driven oscillations, and irreversible resistive heating. These physically interpretable signatures serve as structured inputs to machine learning and deep learning models trained on temporally …

Mtl_Tx: A Multi-Task Transformer Model For Improved Radiation Time-Series Estimation, Hongfang Zhang, Adam Stavola, Hal Ferguson, Bence Budavari, Hongyi Wu, Chiman Kwan, Jiang Li

Electrical & Computer Engineering Faculty Publications

Controlling radiation doses at potential radioactive facilities is critical to ensuring the safety of both personnel and the public. At the Thomas Jefferson National Accelerator Facility (JLab), multiple sensors are deployed around the three experimental halls to monitor key parameters, including single-beam current, energy levels, current leakage, and radiation values during accelerator operations. In this study, we developed a Multi-task Transformer model, MTL_TX, to accurately estimate radiation doses at sensor locations based on historical data, with the aim of enhancing safety in accelerator facilities and surrounding public areas. To improve estimation accuracy, we integrated two innovative components into the proposed …

Machine Learning-Based Lifetime Prediction Of Lithium Batteries: A Comparative Assessment For Electric Vehicle Applications, Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Boubekeur Tala-Ighil, Philippe Makany Boussiengue, Hicham Chaoui, Hamid Gualous

Electrical & Computer Engineering Faculty Publications

This paper evaluates and compares four data-driven methods (Gaussian Process Regression (GPR), echo state network (ESN), gated recurrent unit (GRU), and long short-term memory (LSTM)) for lithium-ion capacity prognostics adapted to electric vehicle conditions. This comparison aims to find the most efficient prognosis method considering two constraints: the limitation of computational power and the unavailability of on-board capacity measurement that requires full charge and discharge conditions. The machine learning models are trained using capacity values estimated under vehicle conditions. The ageing data is collected from cycling tests of two battery chemistries, Lithium Fer Phosphate (LFP) and Nickel Manganese Cobalt (NMC), …

Fault Tolerance Of Accelerated Asynchronous Fixed-Point Iterations On Flexible Computing Infrastructure, Evan Coleman, Masha Sosonkina

Electrical & Computer Engineering Faculty Publications

Asynchronous iterative methods tolerate straggling processors by allowing workers to proceed with stale data, but at a cost: the iterates become inconsistent, potentially degrading convergence. We investigate whether convergence accelerators such as Anderson acceleration compensate for this degradation. We experimentally study three fixed-point iterations: the Jacobi method for sparse linear systems, value iteration for the Bellman equation, and the Hartree–Fock self-consistent field (SCF) iteration. The experiments are conducted using a high-performance execution framework, Ray, which abstracts the complexity of distributed systems and enables code parallelization and fault injection with minimal changes.

We establish two main results. First, straggler tolerance is …

Statewide Corridor Evacuation Response And Re-Entry Behaviors In Florida During Hurricane Irma, Xin Wang, Yuan Zhu, Hong Yang, Kun Xie

Electrical & Computer Engineering Faculty Publications

Hurricane Irma stands as one of the most destructive tropical storms to make landfall in the United States, particularly impacting the State of Florida, where it prompted the largest evacuation in history with approximately 7 million residents. The profound consequences of mass evacuation underscore the critical need to understand travel behaviors during hurricane evacuation and the recovery process. This research analyzes statewide evacuation and re-entry patterns, leveraging diverse datasets, including TTMS data from main corridors and GIS data. A statewide corridor-based empirical analysis framework is constructed to characterize evacuation and re-entry response patterns using sensor-based traffic observations. The results show …

Reforma Alutsista Dan Sumber Daya Alam: Menjawab Tantangan Hukum Internasional Dan Perdamaian Dunia, Wildan Azkal Fikri, Rohadhatul Aisy

Jurnal Hukum & Pembangunan

This study departs from the paradox of the failure to achieve world peace despite the existence of an established international legal regime. It addresses three main objectives: (1) identifying the key factors that undermine world peace; (2) analyzing the failure factors of international law to realize global peace; and (3) formulating a responsive international legal architecture to future peace agendas. The study employs a critical descriptive method with a socio-legal (non-doctrinal) approach, drawing on the analytical frameworks of neorealism, great powers oligarchy, and Third World Approaches to International Law (TWAIL). The qualitative analysis is conducted by examining power relations, the …

Multivariate Quantile Autoregression-Mixed Data Sampling (Mvqar-Midas) Modeling Of Cost Of Living And Supply Chain Dynamics In Canada., Patrick Gbolonyo

Theses and Dissertations (Comprehensive)

In recent years, the rising cost of living as a result of persistent inflationary pressures, disruptions in the global supply chains, and changes in the macroeconomic landscape has become a critical topic of discussion. To address this, we move beyond a mean-based framework and employ a quantile regression approach. This allows the persistence of each series and the transmis- sion of shocks between the Consumer Price Index (CPI) (the total CPI which is a percentage change over the past 12 months), the Interest Rate (IR)(the target for the overnight rate), the New Housing Price Index (NHPI), and high-frequency supply chain …

Machine Learning Classification Of Prostate Cancer Genomic Sequences Using K-Mer And Sequence-Derived Features, Kuldeep Rawat, Hirendra Nath Banerjee, Jamie Noble, Saa Naudia Deloatch, Satyendra Banerjee, Sachin Shetty, Soumya Banerjee

VMASC Publications

Prostate cancer disproportionately impacts African American men, who experience significantly higher mortality rates and earlier disease onset than other populations. Current diagnostic approaches, including prostate-specific antigen testing and biopsy, lack sufficient specificity and sensitivity, underscoring the need for accurate, molecular-level classification tools. This paper presents a machine learning framework for binary classification of genomic DNA sequences as cancerous or healthy. A dataset of 1684 FASTA-formatted sequences obtained from the National Library of Medicine - GenBank was analyzed, with 1662 sequences retained after quality control filtering. Feature engineering yielded 67 attributes, including GC content, Shannon entropy, sequence length, and trinucleotide k-mer …

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

On The Harm Of Being Deputized By God, Taylor-Grey Miller

Faith and Philosophy: Journal of the Society of Christian Philosophers

No abstract provided.

Meta V. Rawtani, Northern District Of California

Historical and Topical Legal Documents

No abstract provided.

Front Matter

SMU Science and Technology Law Review

No abstract provided.

State Ai Therapy Regulations – Analyzing The Illinois Wellness And Oversight For Psychological Resources Act, Natalie Browne

SMU Science and Technology Law Review

According to the Harvard Business Review, the top use case for generative artificial intelligence (AI) in 2025 was therapy and companionship. Accordingly, numerous “therapy-specific” AI tools have hit the market in recent years, vying to fill this growing need. However, individuals are also turning to generic large language models (LLMs), such as ChatGPT, to express their deepest anxieties, seek reassurance, and gather advice. While tech optimists assert that AI therapy tools will extend mental health treatment in care deserts, attention-grabbing headlines about such use cases have shattered communities and shocked legislatures. To address growing concerns about AI therapy, Illinois enacted …

Early Childhood Classrooms And Higher Education Faculty: Partnerships With Far-Reaching Benefits, Anita Weisburger

Essays in Education

The relationship between a community college early childhood teacher education faculty member and the director of an early learning center grew into a deep and meaningful partnership that went beyond the two main participants.  This description and analysis of their collaboration demonstrates the value of these partnerships to the early childhood classrooms and the faculty at the college, but it also highlights the positive impact on the college students, the young children, the school families and the community at large.  The goal of this article is to reflect on the benefits and challenges in these collaborative endeavors and highlight lessons …

Discern Magazine Fall 2026 Excerpt About New Faculty Hires, Santa Clara Law

Historical and Topical Legal Documents

No abstract provided.

Exploring Undergraduate Women’S Experiences Of Collaborative Learning In Engineering Education: A Phenomenological Study Of The Social World, Sandra Ireri Cruz Morena

Doctoral

The persistent underrepresentation of women in engineering education remains a concern across global and national contexts, despite rising overall enrolment of women in higher education. In Ireland, the national average of women entering Engineering, Manufacturing, and Construction (EMC) programmes has gradually increased; however, the rate at Technological University Dublin (TU Dublin) has stayed at approximately 15% since 2016. This study seeks to better understand the gendered challenges underlying such trends by exploring the lived experiences of female undergraduate engineering students at TU Dublin, particularly in relation to collaborative learning environments such as project- and problem-based learning (PBL).

Bariatric Surgery Impacts Immune Cell Metabolism And Function Dependent On Metabolic Status, Samantha N. Hart

University of Kentucky Doctoral Dissertations

Type 2 Diabetes (T2D), one of the top ten causes of death worldwide, is fueled by chronic inflammation. T2D is considered a metabolic disease, and there is a great push to target metabolic and associated inflammatory pathways to ameliorate the disease & its comorbidities i.e., obesity and cardiovascular disease. Thus far, clinical trials of anti-inflammatory drugs have had modest impacts on T2D and have not led to changes in clinical practice. This may in part be due to a gap in knowledge in the mechanism(s) driving obesity-associated chronic inflammation. I posit that metabolic abnormalities in immune cells in those with …

Metabolomics Driven Discovery Of Bioactive Natural Products Leads From Marine And Terrestrial Sources For The Development Of Analgesics, Sahar Mofidi Tabatabaei

University of Kentucky Doctoral Dissertations

Natural products remain a rich source of structurally diverse bioactive compounds for drug discovery, particularly for pain therapeutics. However, the chemical complexity of natural product extracts presents significant challenges for the efficient identification and prioritization of bioactive metabolites. This dissertation integrates untargeted LC-MS/MS-based metabolomics, molecular networking, classical natural products chemistry, and neurobiological assays to accelerate the discovery of analgesic lead compounds targeting the emerging pain-associated receptor σ₂R/TMEM97.

An untargeted metabolomics workflow was developed to systematically profile complex biological extracts and guide bioactive compound isolation. High-resolution LC-MS/MS data were analyzed using molecular networking (GNPS/GNPS2) to visualize chemical space, dereplicate known metabolites, …

Examining Marginalized Sexual Identity Development Through Perry’S Scheme Of Cognitive Development, Miranda Bejda

University of Kentucky Doctoral Dissertations

Existing models of LGBTQ+ sexual identity development are critiqued for their linearity and lack of inclusion for diverse experiences and sexual identities. There is a call for a more robust understanding of the cognitive aspect of sexual identity development. The purpose of this dissertation is to further the understanding of how people think about their sexual identity through the developmental process using Perry’s scheme of cognitive development as a framework. Through semi-structured interviews, I analyze the LGBTQ+ sexual identity development process (Stage 1), how Perry’s scheme applies to LGBTQ+ sexual identity development (Stage 2), and propose a Perry-informed model of …

Cognitive Validity In Listen-To-Write Summary Tasks: A Mixed-Methods Analysis Of Notetaking Data, Rebecca Yeager, Gomee Park, Junhee Park

Bilingual and Literacy Studies Faculty Publications

This study examines the cognitive validity of a listen-to-summarize task on a university placement test. Cognitive validity is underinvestigated in listening assessment, especially for higher-order listening processes (Holzknecht et al., 2017; Rukthong, 2021). However, student notes from listening tests can record evidence of these processes (Yeager et al., 2024; Cushing, 1991). This study employed an exploratory sequential mixed-methods design to investigate the higher-order listening processes elicited by an integrated listen-to-summarize task. First, notes from two administrations of the same test form – one with notetaking scaffolding (n = 25) and one without (n = 25) – were analyzed qualitatively. Second, …

Full Proceedings, Nckri

Sinkhole Conference 2026

No abstract provided.

Navigating Belonging: Exploring Self & Community Through Research & Creative Expression, Natasha Hutson

Athena: Undergraduate Research and Literary Journal

No abstract provided.

Understanding Addiction As A Disease: College Students’ Perspectives On Substance Use In The Covid-19 Era, Aditi Rudrashetty

Athena: Undergraduate Research and Literary Journal

This research explores the neurological basis of addiction as a disease and how the exacerbation of external factors has contributed to negative perceptions of addiction. Specifically, it examines the COVID-19 pandemic and contemporary college student experiences as contextual factors influencing attitudes toward substance use disorders. Negative perceptions contribute to stigma, reduce help-seeking behavior, and influence policy responses, hindering effective support and recovery for individuals with substance use disorders. By examining these perceptions, this study contributes to understanding how addiction is conceptualized and potentially addressed in public health and policy contexts. Surveys and semi-structured interviews were conducted with college students to …

Whole Genome Sequencing: Considering Regulations, Policies, And Procedures, Nyaw Lar Too

Athena: Undergraduate Research and Literary Journal

This research explores the opinions of young adults between the ages of 19 to 30 about the vulnerabilities of using DNA sequencing tests as a part of couples’ prenatal care to determine every possible mutation, variation, and cancers possible for future offspring. A survey-based experiment was used to gather information from a sample of 17 young adults within the aforementioned age group. The findings from the surveys are intended to assist scientists in acknowledging public opinion and aid in guiding their decisions on how to move forward with genome sequencing. Ultimately, the survey findings could give scientists an idea of …