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Closing The Door On Housing Discrimination: Why Rhode Island Must Enact A Fair Chance In Housing Act, Jessica Galego

Roger Williams University Law Review

No abstract provided.

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A Personal Take: An Argument In Favor Of Adopting The Uniform Partition Of Heirs Property Act In Rhode Island, Isiah Dipina, Natasha Varyani

Roger Williams University Law Review

No abstract provided.

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When Walking Out Doesn’T Mean Losing Out: Why Rhode Island Should Reform Its Model For Unemployment Insurance In Relation To Striking Workers, Trina Capezza

Roger Williams University Law Review

No abstract provided.

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Clinton V. Babcock, 332 A.3d 167 (R.I. 2025)., Greta Johnson

Roger Williams University Law Review

No abstract provided.

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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 …

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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 …

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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 …

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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 …

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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 …

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A Comprehensive Survey Of Prompt Engineering Techniques In Large Language Models, Tonmoy Debnath, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Prosenjit Das, Antu Kumar Guha, Muhammad Rezaur Rahman, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

Prompt engineering has arisen as a pivotal discipline in optimizing the performance of Large Language Models (LLMs) by structuring inputs to enhance coherence, accuracy, and task alignment. This paper comprehensively surveys various prompting techniques, systematically categorizing them according to their application domains and methodological foundations. Fundamental approaches like zero-shot and few-shot prompting are examined along with advanced strategies, including chain-of-thought reasoning, retrieval-augmented generation, and self-consistency mechanisms. A rigorous qualitative analysis is conducted to evaluate each technique's strengths, limitations, and optimal use cases, offering a structured framework for selecting the most effective prompting strategies. Theoretical insights and empirical findings are consolidated …

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Injectable Hydrogels For Bone Regeneration: Mechanical Reinforcement Strategies Using Nanoparticles And Nanofibers: Review Paper, Fariba Ganji, Morteza Mirzagoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: The growing demand for bone regeneration following severe injuries highlights the importance of scaffolds in bone tissue engineering (BTE). Injectable hydrogels have emerged as promising candidates because their properties closely mimic the native extracellular matrix (ECM). However, their limited mechanical strength and structural instability restrict their practical application. Approach: This review summarizes recent strategies for reinforcing in situ-forming injectable hydrogels to improve their mechanical performance for bone regeneration. Particular emphasis is placed on nanomaterial-based strategies, including the incorporation of nanoparticles and nanofibers, and their ability to enhance the physical properties of polymeric networks. Key Results: Evidence from …

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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 …

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Markov Chain Wave Generative Adversarial Network For Bee Bioacoustic Signal Synthesis, Kumudu Samarappuli, Iman Ardekani, Mahsa Mohaghegh, Abdolhossein Sarrafzadeh

Electrical & Computer Engineering Faculty Publications

This paper presents a framework for synthesizing bee bioacoustic signals associated with hive events. While existing approaches like WaveGAN have shown promise in audio generation, they often fail to preserve the subtle temporal and spectral features of bioacoustic signals critical for event-specific classification. The proposed method, MCWaveGAN, extends WaveGAN with a Markov Chain refinement stage, producing synthetic signals that more closely match the distribution of real bioacoustic data. Experimental results show that this method captures signal characteristics more effectively than WaveGAN alone. Furthermore, when integrated into a classifier, synthesized signals improved hive status prediction accuracy. These results highlight the potential …

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The Gut-Heart Axis: Exploring The Role Of The Gut Microbiome In Cardiovascular Health-A Focused Systematic Review, Yahya Makkieh, Haider Hussain Shah, Sakan Binte Imran, Shadman Mahmood Mahmood Khan Pathan, Anagha Chirayath Saju, Mounica Majooju, Aastha Garg, Tarun Naag, Rabeeul Islam, Cheeranthodika Fahima, Ramsha Ali

Electrical & Computer Engineering Faculty Publications

This focused systematic review examines the role of the gut microbiota in cardiovascular disease (CVD). The review explores mechanisms linking gut dysbiosis with CVD via microbial metabolites such as trimethylamine-Noxide (TMAO) and short-chain fatty acids (SCFAs), which affect inflammation, endothelial function, and lipid metabolism. Interventions including dietary modifications, probiotics, prebiotics, fecal microbiota transplantation, and pharmacological agents such as statins, rifaximin, and empagliflozin are evaluated for their impact on microbial composition and cardiovascular outcomes. Probiotic strains and fiber-rich diets demonstrated modest improvements in blood pressure, lipid profiles, and inflammatory markers. Studies revealed that gut microbiome alterations influence drug metabolism and bleeding …

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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 …

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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), …

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Recent Insight And Perspective Of Marine-Inspired Biopolymers For Wound Healing Applications - A Review, Muhammad Umar Aslam Khan, Saiqa Yousaf, Abdalla Abdal-Hay, Mohd Faizal Bin Abdullah, Sahar Madani, Muhammad Shahzad Zafar, Goran M. Stojanović, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

There is an increasing necessity for advanced, sustainable, and biocompatible materials for wound healing as therapeutic and diagnostic products. Marine environments, characterized by high biodiversity, offer an underutilized source of natural resources with enormous potential for creating novel materials for dressings. This review highlights the revolutionary nature of polymeric biomaterials of marine origin, with a focus on polysaccharides, like alginate, chitosan, and carrageenan; proteins, such as collagen and gelatin. These biopolymers are outstanding in their physicochemical properties, such as biodegradability, bioactivity, and modifiable mechanical strength, which enable their use in wound-healing systems. Besides, these biomaterials may be easily chemically and …

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Digital Twin Technologies For Battery Systems: Advancements, Applications, And Future Directions, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

The relationships among deep learning, edge computing, artificial intelligence (AI), and the most recent advancements in digital twin (DT) technology for battery energy storage systems are discussed in this paper. The study highlights the need for improved cloud-edge coordination, AI model development, and stronger cybersecurity features by demonstrating real-world applications of digital twin technology in electric vehicles (EVs), aircraft, and grid storage. It also described DT-based structures for fault detection, real-time monitoring, and optimization through standardization and battery management system (BMS) fusion. Because DT-based solutions for distributed energy resources (DERs) offer improved energy management systems, various studies have been conducted …

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Photobiomodulation Mitigates The Inhibitory Effects Of Pirfenidone On Cancer-Associated Fibroblasts And Their Pro-Tumorigenic Properties: A Cause For Concern, Nima Rastegar-Pouyani, Alireza Nasirpour, Fatemeh Javani Jouni, Hossein Vazini, Ahmad Moshaii

Electrical & Computer Engineering Faculty Publications

Cancer-associated fibroblasts (CAFs) within the tumor microenvironment highly contribute to cancer progression and poor prognosis. Recent findings introduce pirfenidone, a medication for pulmonary fibrosis, as a promising repurposed candidate for inhibiting CAFs. Moreover, photobiomodulation (PBM), or low-level laser therapy, has surfaced as a potential modality against cancer; however, its impact on CAFs is not thoroughly comprehended. The present study scrutinized the effects of PBM, pirfenidone, and PBM+pirfenidone on CAFs, and their consequent impact on cancer cells using the CAF-conditioned media. After treating CAFs with PBM at wavelengths 660 and 980 nm with/without PFD and then culturing cancer cells in the …

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Pin-Plane Electrical Discharge Driven By A Mosfet Dc Current Source, Myles Perry, Sidmar Holoman, Daniel Wozniak, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

The generation of atmospheric pressure nonequilibrium plasma using electrical discharges is an active area of research due to its significance in a wide spectrum of applications including medicine, combustion, and manufacturing. In our attempt to create a helium plasma jet in a pin-plane discharge with a constant current source, we observed self-pulsating behavior. We present the results of the electrical, optical, and spectroscopic measurements carried out to characterize the discharge. The duration of the discharge is a few tens of nanoseconds, and the repetition rate is in the few tens of kHz. The effect of the gap distance and gas …

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Interpretable Battery Soh Prediction: A Comparative Interpretability Framework For Multi-Architecture Ml Models, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

This work introduces a unified interpretability-efficiency framework for lithium-ion battery state of health (SOH) prediction using hybrid deep learning architectures. We comparatively analyze four hybrid models: CNN LSTM MultiHead, CNN Feature Extractor LSTM, DNN LSTM, and DNN BiLSTM to disentangle how network topology, feature composition, and computational design influence both predictive fidelity and physical interpretability. By integrating Monte Carlo Shapley (MC Shapley), background occlusion SHAP (BoSHAP), and ablation analysis, we quantify the contribution and robustness of five electrochemical feature groups: time, capacity, voltage, dQ/dV and peaks of dQ/dV from NASA battery dataset. The results reveal a consistent dominance of differential …

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Recent Advances In Bioceramics, Fundamental Properties And Future Perspective In Biomedical Applications ‒ A Review, Ayesha Younas, Muhammad Umar Aslam Khan, Mohd Faizal Binte Abdullah, Lobat Tayebi, Shuanghu Wang, Abdalla Abdal-Hay, Yichi Xu

Electrical & Computer Engineering Faculty Publications

Bioceramics are important biomaterials in biomedical engineering because of their biocompatibility, bioactivity, osteoconductivity, and structural resemblance to actual bone tissue. In recent years, materials science and nanotechnology have enabled the use of bioceramics in bone regeneration, dental restoration, tissue engineering, drug delivery systems, and implantable medical devices. This comprehensive review covers advances in bioceramics, including calcium phosphates, hydroxyapatite (HAp), tricalcium phosphate, bioactive glasses, zirconia, alumina, and multifunctional ceramic nanocomposites. Priority is given to techniques such as additive manufacturing, 3D printing, sol-gel processing, electrospinning, and nanostructuring to improve mechanical strength, porosity, bioactivity, and cell interactions. Recent advances include ion doping, surface …

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3d-Printed Alginate Scaffolds Incorporated With Synergistic Strontium/Magnesium - Doped Bioglass Nanoparticles For Bone Regeneration: An In Vivo Evaluation In Rabbit Cranial Defects, Mehraneh Movahedi Aliabadi, Afsaneh Jahani, Seyed Majdoddin Vahidi Toorchi, Ali Moradi, Mohammad Hossein Ebrahimzadeh, Fatemeh Kalalinia, Farkhonde Sarhaddi, Lobat Tayebi, Nafiseh Jirofti

Electrical & Computer Engineering Faculty Publications

Nonunion fractures remain a major orthopedic challenge, highlighting the need for improved bone tissue engineering (BTE) strategies. This study hypothesized that incorporating Sr/Mg-doped 58S bioglass nanoparticles into 3D-printed alginate (Alg) scaffolds would improve their physicochemical, mechanical, and biological properties and enhance bone regeneration. Structural characterization showed that Sr/Mg-doping reduced bioglass size and produced interconnected porous scaffolds. Under wet conditions, Alg scaffold incorporating 2.5%Sr/Mg-doped 58S bioglass showed the highest Young’s modulus (0.4356 ± 0.0244 MPa), whereas under dry conditions, the Alg scaffold incorporating 5%Sr/Mg-doped 58S bioglass achieved the highest value (0.1945 ± 0.0519 MPa). In vitro studies demonstrated biocompatibility and enhanced …

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Standardization Of Neuromuscular Reflex Analysis—Role Of Fine-Tuned Vision-Language Model Consortium And Openai Gpt-Oss Reasoning Llm-Enabled Decision Support System, Eranga Bandara, Ross Gore, Sachin Shetty, Ravi Mukkamala, Christopher K. Rhea, Brittany S. Samulski, Amin Hass, Atmaram Yarlagadda, Shaifali Kaushik, Malith De Silva, Andriy Maznychenko, Inna Sokolowska, Kasun De Zoysa

VMASC Publications

Background/Objectives: Accurate assessment of neuromuscular reflexes, such as the Hoffmann reflex (H-reflex), plays a critical role in sports science, rehabilitation, and clinical neurology. Conventional interpretation of H-reflex electromyography (EMG) waveforms is subject to inter-rater variability and interpretive bias, limiting reliability and standardization. This study aims to develop an automated, interpretable, and robust agentic AI–driven framework for H-reflex waveform analysis. Methods: We propose a fine-tuned Vision–Language Model (VLM) consortium combined with a reasoning Large Language Model (LLM)–enabled decision support system for automated H-reflex interpretation. Multiple VLMs were fine-tuned on curated datasets of H-reflex EMG waveform images annotated with expert clinical observations, …

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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 …

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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. …

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No Ghost In The Machine: Doubting Ai Ensoulment, Bálint Békefi

Faith and Philosophy: Journal of the Society of Christian Philosophers

No abstract provided.

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Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models …

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Front Matter

SMU Science and Technology Law Review

No abstract provided.

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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 …

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Full-Text Articles in Entire DC Network

Closing The Door On Housing Discrimination: Why Rhode Island Must Enact A Fair Chance In Housing Act, Jessica Galego

Roger Williams University Law Review

A Personal Take: An Argument In Favor Of Adopting The Uniform Partition Of Heirs Property Act In Rhode Island, Isiah Dipina, Natasha Varyani

Roger Williams University Law Review

When Walking Out Doesn’T Mean Losing Out: Why Rhode Island Should Reform Its Model For Unemployment Insurance In Relation To Striking Workers, Trina Capezza

Roger Williams University Law Review

Clinton V. Babcock, 332 A.3d 167 (R.I. 2025)., Greta Johnson

Roger Williams University Law Review

Performing Democracy, Carliss N. Chatman

Faculty Journal Articles and Book Chapters

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

Faculty Journal Articles and Book Chapters

Chat M.D., Nathan Cortez

Faculty Journal Articles and Book Chapters

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

Faculty Journal Articles and Book Chapters

Rethinking Courtroom Presence In The Virtual Era, Jenia Iontcheva Turner

Faculty Journal Articles and Book Chapters

A Comprehensive Survey Of Prompt Engineering Techniques In Large Language Models, Tonmoy Debnath, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Prosenjit Das, Antu Kumar Guha, Muhammad Rezaur Rahman, H. M. Dipu Kabir

Electrical & Computer Engineering Faculty Publications

Injectable Hydrogels For Bone Regeneration: Mechanical Reinforcement Strategies Using Nanoparticles And Nanofibers: Review Paper, Fariba Ganji, Morteza Mirzagoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

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

Markov Chain Wave Generative Adversarial Network For Bee Bioacoustic Signal Synthesis, Kumudu Samarappuli, Iman Ardekani, Mahsa Mohaghegh, Abdolhossein Sarrafzadeh

Electrical & Computer Engineering Faculty Publications

Electrical & Computer Engineering Faculty Publications

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

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

Recent Insight And Perspective Of Marine-Inspired Biopolymers For Wound Healing Applications - A Review, Muhammad Umar Aslam Khan, Saiqa Yousaf, Abdalla Abdal-Hay, Mohd Faizal Bin Abdullah, Sahar Madani, Muhammad Shahzad Zafar, Goran M. Stojanović, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Digital Twin Technologies For Battery Systems: Advancements, Applications, And Future Directions, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

Photobiomodulation Mitigates The Inhibitory Effects Of Pirfenidone On Cancer-Associated Fibroblasts And Their Pro-Tumorigenic Properties: A Cause For Concern, Nima Rastegar-Pouyani, Alireza Nasirpour, Fatemeh Javani Jouni, Hossein Vazini, Ahmad Moshaii

Electrical & Computer Engineering Faculty Publications

Pin-Plane Electrical Discharge Driven By A Mosfet Dc Current Source, Myles Perry, Sidmar Holoman, Daniel Wozniak, Shirshak Kumar Dhali

Electrical & Computer Engineering Faculty Publications

Interpretable Battery Soh Prediction: A Comparative Interpretability Framework For Multi-Architecture Ml Models, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Recent Advances In Bioceramics, Fundamental Properties And Future Perspective In Biomedical Applications ‒ A Review, Ayesha Younas, Muhammad Umar Aslam Khan, Mohd Faizal Binte Abdullah, Lobat Tayebi, Shuanghu Wang, Abdalla Abdal-Hay, Yichi Xu

Electrical & Computer Engineering Faculty Publications

Electrical & Computer Engineering Faculty Publications

VMASC Publications

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

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

No Ghost In The Machine: Doubting Ai Ensoulment, Bálint Békefi

Faith and Philosophy: Journal of the Society of Christian Philosophers

Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Front Matter

SMU Science and Technology Law Review

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

SMU Science and Technology Law Review