Digital Commons Network^™

The Boundaries Of Corporate Politicking, Ashlee A. Paxton-Turner

Maryland Law Review

No abstract provided.

In The Race Between The Federal Government And The States To Regulate Ai, Big Tech Is The Winner, Matthew Berger

Maryland Law Review

No abstract provided.

The Key Bridge Collapse: An Opportunity To Reel In Shipowners’ Protections, Elliott Lagorce

Maryland Law Review

No abstract provided.

Link, Retain, Suppress: A Grounded Theory Study Of Medical Case Management In The Philadelphia Hiv Service Agencies, Shakeera Wynne

Social Work Doctoral Dissertations

Medical case management (MCM) plays a critical role in supporting engagement in HIV care; however, differences in implementation across agencies may influence service delivery and outcomes. Existing research has focused primarily on outcomes such as retention in care and viral suppression, while less is known about how the MCM intervention is implemented in practice. The purpose of this grounded theory study was to explore how medical case management is implemented within HIV care settings and to examine the structural, organizational, and relational factors that shape service delivery. Semi-structured interviews were conducted with medical case managers working within Ryan White-funded agencies …

Bridging The Gap Towards Sustainable Development: A Systematic Literature Review On Orang Asli Communities In Peninsular Malaysia, Nurfatiha Akmal Fawwazah Abdullah-Fauzi, Nursyuhada Othman, Hidayah Haris, Nur Hartini Sariyati, Farah Farhana Ramli, Kaviarasu Munian, Mohd Faudzir Najmuddin, Mohd Tajuddin Abdullah, Muhammad Abu Bakar Abdul-Latiff

Forest and Society

Orang Asli communities in Peninsular Malaysia have a complex history marked by challenges related to land rights, environmental degradation, and cultural preservation. Despite ongoing efforts to address these challenges, significant obstacles persist, particularly in healthcare access and outcomes, education, language preservation, dietary practices, religious beliefs, and policy frameworks. This systematic literature review aims to provide a comprehensive analysis of past and current research on various aspects of Orang Asli communities in Peninsular Malaysia. The primary goal is to uncover the trends of challenges and unique characteristics of the Orang Asli communities while offering valuable recommendations for improvement. The Preferred Reporting …

Multi-Frequency Associative Memory For Continual Graph Learning Through Nested Optimization, Shuvam Kundu

Master’s Dissertations

Graph Neural Networks struggle to learn new tasks without forgetting old ones a problem known as catastrophic forgetting. In graph domains, this is compounded by structural shift, where newly added edges corrupt the learned representations of historical nodes even when model weights remain unchanged. We present CAM-Titans, a continual graph learning framework built around a two-buffer associative memory to address both parametric and structural forgetting. Our architecture operates across three timescales of adaptation: a slow base memory updated via ordinary gradient descent, an intermediate task buffer re-encoded after every task using the delta-rule, and a transient in-context state for rapid …

Development And Standardization Of Teds Actuator Templates Under Ieee 1451 Framework, Jim Kang

Theses and Dissertations

The IEEE 1451 standard is a family of standards that defines a framework for smart transducers, including both sensors and actuators, to support consistent, interoperable, and cost-effective integration across diverse applications. However, the current IEEE 1451.4 standard templates only define the method for encoding Transducer Electronic Data Sheet (TEDS) information for a broad range of sensor types and applications; they do not address actuator TEDS. Specific types of sensors and actuators are being developed to assess underground environmental conditions in cold regions with widespread permafrost. Evaluating subsurface conditions before construction can help prevent high construction expenses for structures built on …

The Role Of Chatgpt In Higher Education: A Systematic Literature Review Of Applications, Perceptions And Ethical Implications, Mahmoud Abdelrahman, Shiyu Hu, Ons Al-Shamaileh, Ramy Hammady, Nishara Nizamuddin

All Works

Purpose – This study aims to systematically review the emerging literature on ChatGPT in higher education, focusing on its applications, impacts and ethical implications from the perspectives of students and academic staff. By synthesising evidence across disciplines and geographical contexts, the review identifies key benefits such as enhanced learning efficiency and artificial intelligence (AI) literacy, alongside challenges including academic integrity risks and unequal access. The purpose is to provide a comprehensive, student-centred understanding of ChatGPT’s role in higher education and to offer actionable insights for policy, practice and future research. Design/methodology/approach – This study adopts a systematic literature review (SLR) …

Pinnlab: An Interactive Dashboard For Teaching Data-Driven Parameter Estimation In Differential Equations Using Physics-Informed Neural Networks, Mohan J. Parthasarathy, Padmanabhan Seshaiyer

CODEE Journal

Undergraduate instruction in ordinary differential equations (ODEs) is typically organized around the forward problem: finding solution trajectories when the governing equation and its parameters are known. In scientific practice, however, inverse problems are often more relevant, requiring unknown parameters to be inferred from noisy observations while assessing whether a proposed model is consistent with the data. We introduce PINNLab, an open-source MATLAB dashboard designed to help undergraduate students explore inverse modeling through physics-informed neural networks (PINNs). PINNLab presents PINNs as a complementary data-driven framework that connects differential equations, optimization, empirical data, and scientific machine learning. The instructional sequence is organized …

What Do Highly Successful Families Of Faith Teach Us About Trust?, Caleigh E. B. Kerr

Undergraduate Honors Theses

This study examined trust among diverse families of Abrahamic faiths across the United States. The 292 families who were part of this national study represent significant religious breadth (over 20 total denominations), geographic scope, and racial diversity, with 51% of the participants being racial/ethnic minorities. Married participants had at least one child. Education levels of participants ranged from G.E.D to Ph.D., with varying socioeconomic statuses. Semi-structured interviews were conducted with participants. Couples were hand-chosen by their respective religious leaders as being both relational and religious exemplars.

Using the qualitative responses of participants, a word search was conducted. Responses relevant to …

Learning To See Lesions, Not Skin Tone: Counterfactual Multimodal Learning For Fair, Trustworthy, And Text-Free Dermatology Ai, Shivam Jangid

Master’s Dissertations

Recent advances in deep learning have significantly improved the performance of automated skin lesion classification systems, enabling accurate detection of various dermatological conditions from medical images. Despite these achievements, concerns regarding fairness and generalization remain a major challenge for the deployment of such systems in real-world clinical settings. A key factor contributing to these challenges is the presence of bias in training datasets, particularly with respect to skin-tone representation. Most publicly available skin lesion datasets contain a disproportionate number of samples from individuals with lighter skin tones. As a result, deep learning models trained on these datasets often learn representations …

Adaptive Spectral Trust Gate For Physics- Constrained Operator Learning, Soham Chakraborty

Master’s Dissertations

Physics-informed machine learning improves the plausibility, data-efficiency and generalization of surrogate models by injecting prior physical knowledge into the learning process. The current approaches can be broadly divided into two main categories: soft constraints, which add a physics residual to the training loss but guarantee nothing at inference time, and hard constraints, which project the model output onto the constraint set exactly but apply the projection uniformly to every part of the signal — including parts that are dominated by noise, discretization error, or model mismatch, where the idealized physics is not actually trustworthy. This dissertation proposes the Adaptive Spectral …

Deep Reinforcement Learning With Directed Asymmetry And Kolmogorov-Arnold Networks For Dismantling Interdependent Multiplex Networks, Soumyajit Dev

Master’s Dissertations

Identifying the minimum-cost node-removal sequence that fragments a complex network - the network dismantling problem is NP-hard and central to infrastructure resilience. In interdependent multiplex networks, this difficulty is compounded by cascading cross-layer failures. While deep reinforcement learning (DRL) agents utilizing graph neural network (GNN) encoders achieve near-optimal dismantling, current state-of-the-art architectures suffer from two critical limitations. Topologically, existing agents strictly assume undirected edges, rendering them inapplicable to directed systems - such as supply chains or gene regulatory cascades - where failure propagation is fundamentally asymmetric. To resolve this, we propose Disassembling Directed Interdependent Networks (DDIN). DDIN introduces an asymmetric …

University Of New Hampshire Dean's List For Spring 2026 Semester, Unh Communications And Public Affairs

UNH Today Archive

No abstract provided.

From Centrality To Sustainability: How Connected Boards Shape Waste Management Outcomes, Irfan Haider Shakri, Anh Tuan Nguyen, Fnu Pratima

Faculty Publications

The escalating climate crisis has elevated waste management from an operational concern to a critical issue of corporate governance. However, the role of board connectedness in shaping firms' waste practices remains largely unexplored. Drawing on resource dependency and social capital theories, this study examines how board network centrality influences waste management practices. Employing pooled OLS on 4948 firm- year observations from US- listed firms during 2004–2023, we find that higher board connectedness leads to a significant reduction in waste generation. Economically, a one standard deviation increase in DEGREE centrality is associated with a 3.4% decrease in total waste generation. Our …

If Pets Are Family: Pet Loss And The Need For Grief Equity In One Health, Michele L. Whitney

Journal of One Health Systems

One Health frameworks increasingly recognize pets as integral to human health and well-being. However, these models often overlook the health and equity implications of pet loss. Culturally mediated grief experiences following pet bereavement represent a critical grief equity gap in One Health systems. Drawing on findings from a qualitative study of African American adults who experienced pet loss, along with existing literature, this Viewpoint highlights how pet loss is not only an emotional experience but also a socially structured one shaped by cultural norms, social recognition, and access to support. These dynamics contribute to inequities in how grief is experienced …

Using In-Home Air Quality Monitoring To Reduce Cannabis Secondhand Smoke Exposure In Children: Quantitative Pilot Feasibility Study, Vincent Berardi, Bradley N. Collins, Laura M. Glynn, Eusabeia Silfanus, Darby G. Lyons, Stephen J. Lepore

Psychology Faculty Articles and Research

Background: An estimated 5 to 8 million US children live with a parent who uses cannabis, and most cannabis users report smoking cannabis inside their homes, placing children at risk for cannabis secondhand smoke (cSHS) exposure. Indoor air quality (IAQ) monitoring provides real-time feedback on airborne pollutants and has shown promise in reducing in-home tobacco secondhand smoke exposure, suggesting its potential as an effective harm reduction strategy for cSHS.

Objective: This pilot study evaluated the feasibility, acceptability, and preliminary effectiveness of using low-cost, off-the-shelf IAQ monitors to increase caregivers’ awareness of children’s cSHS exposure risk and to change …

Applying Theory Of Planned Behavior To Examine Adolescent Female Athletes’ Intentions Of Continued Sport Participation, Chris Hopkins, Casey S. Hopkins

Open Access Fund Publications

Introduction: Adolescent females discontinue sports at higher rates than males, which contributes to their lower overall physical activity during this important period of development. Potentially useful for understanding this disparity, the Theory of Planned Behavior (TPB) provides a framework to study one's intentions through their attitudes, subjective norms, and perceived behavioral control. This study examined whether TPB constructs predict female adolescents’ intentions to continue participating in sports and remain physically active.

Methods: This cross-sectional study used an online questionnaire to collect data from 271 female adolescents who recently participated in organized sports. Structural equation modeling was used to test TPB's …

New Studies In Lattice-Based Cryptography, Quantum Algorithms, And Privacy-Preserving Computation, Hansraj Jangir

Electronic Theses and Dissertations 2020 - Present

Classical public-key cryptographic schemes primarily rely on the presumed hardness of the integer factorization and discrete logarithm problems. However, Shor’s algorithm demonstrates that both problems can be solved efficiently on a sufficiently powerful quantum computer. This breakthrough motivated the search for quantum-resistant hard assumptions. The assumptions based on lattices are one of the primary candidates in post-quantum cryptography due to their strong theoretical foundations and well-established hardness against both classical and quantum attacks. In this thesis, we explore several directions of lattice based cryptology and quantum algorithms.

On the construction side, we propose two compact encryption schemes based on the …

Paths To Stability And Wealth: Evidence From The Habitat For Humanity Wealth Building Project, Yung Chun, Somalis Chy, Laura Evans, Xueying Mei, Stephen Roll

Center for Social Development Research

Owning a home has long been the most common way for American families build wealth—but for low- and moderate-income families, the route is rarely open and rarely simple. And handing a family the keys does not guarantee that the house will become an asset. This report sets out to answer a hard question: Can homeownership deliver lasting wealth to the families who have been locked out of it the longest, and what does it take to make that happen? This study presents findings from the first national evaluation of the Habitat for Humanity Wealth Building Project. The report examines how …

A System For The Prediction Of Election Results Using Vader And Hybridized Machine Learning Model, Abraham E. Evwiekpaefe, Khadijah Kabir, Georgina N. Obunadike

Tanzania Journal of Science

Integrating different classifiers along with sentiment lexicons like Vader, can enhance the performance of sentiment analysis systems. However, such a hybrid model remains underexplored, particularly in the context of regional elections in developing countries like Nigeria. The aim of this research is to develop a hybrid model that combines three machine learning classifiers and Vader lexicon to possibly achieve a higher accuracy. A case study of the 2023 governorship election in Kogi, Bayelsa and Imo State, Nigeria was examined. Twitter API library was utilized to extracted public and personal tweets using hashtags and keywords related to the target data from …

Modelling And Analysis Of 50 Mwp Solar Pv Integration Into Tanzania’S Transmission Network: A Case Study Of Tagamenda Substation, Iringa Region, Santos Kihwele

Tanzania Journal of Science

While increasing the share of renewable energy in the grid, grid integration studies for the utility solar photovoltaic (PV) plants are vital, given their intermittency and the fact that Tanzania has never had one connected to the grid. This paper presents a 50 MWp grid integration study, including a technical analysis conducted using PSS®E software. The study investigates the grid behaviour during the integration of the 50 MWp solar plant, considering the most suitable technical and economic solutions. The study analysed the load flow under normal conditions, contingency analysis (N-1), short- circuit analysis, and voltage stability assessment. The results show …

Operation No Noro: A Multidisciplinary Approach To Containing A Norovirus Outbreak In An Inpatient Rehabilitation Unit, Donika Marko, Roula Hilli, Priscila Bercea, Pamela S. Bozigar, Levi Launder, Stephanie Robertson, Trini A. Mathew

Conference Presentation Abstracts

Norovirus is a highly contagious viral gastroenteritis and can rapidly spread in healthcare settings, particularly in congregate environments such as inpatient rehabilitation units. In March 2025, a cluster of acute gastrointestinal illness was identified on a 34-bed inpatient rehabilitation unit within a 150-bed acute care hospital. Eight patients developed: • Nausea • Vomiting • Diarrhea • Abdominal pain Due to shared spaces, communal therapy activities, and high patient interaction, rapid intervention was initiated to prevent further spread.

Moving Through Disasters: Spatial Analysis And Modeling Of Evacuation, Migration, And Socioeconomic Selectivity In The United States, Xiang Li

USF Tampa Graduate Theses and Dissertations

Disasters increasingly affect population movement in the United States, but their relationships with mobility and migration at various spatio-temporal scales are not fully understood. Disaster-related movement may appear as short-term evacuation during hazardous events, long-term migration after major or repeated disaster exposure, or selective redistribution across socio-economic groups. Therefore, this dissertation aims to address three main questions: 1) What are the spatial patterns of evacuation, and how do evacuation rates vary across space during a major disaster? 2) To what extent are natural disasters associated with long-term human migration patterns in the United States, and how can their contributions be …

Effects Of Peer Tutoring Training Duration And Group Piano Level On Harmonization And Transposition Achievement And Learning Attitudes Of Undergraduate Non-Keyboard Music Students, Jinnan Liu

LSU Doctoral Dissertations

The purpose of this study was to examine the relationships among peer tutoring training duration, group piano level, and undergraduate non-keyboard music students’ achievement in harmonization and transposition, as well as their learning attitude following peer tutoring. Based on the literature on cooperative learning, peer-assisted learning, and reciprocal peer tutoring, this study examined whether differences in training duration and group piano level were related to student performance and learning experiences in university group piano.

A quasi-experimental 2  2 design was used. The independent variables were peer tutoring training duration (2-day vs. 4-day) and group piano level (Group Piano II vs. …

Development Of Blue And Near-Uv Iii-Nitride Laser Diodes, Matthew Seitz

Theses

III-Nitrides show tremendous promise for a wide range of laser diodes and other optoelectronics devices. The wide range of emission wavelengths possible makes these devices ideal candidates for a wide range of applications. Despite this, several challenges remain unsolved, limiting the efficiency and output power from III-Nitride optoelectronics. Three of the most significant remaining challenges surround the formation of low resistance ohmic electrical contacts, poor p-type doping of III-Nitride crystals as well, and the fabrication of the smooth, mirror facets needed for optical feedback and laser operation. Inefficient dopant activation leads to poor conductivity and increased electrical resistance due to …

Topological Tools For The Analysis Of Complex Networks And Higher-Order Networks, Jason P. Laruez

Theses

This dissertation investigates the intersection of topological data analysis and network science, applying and extending persistent homology, Betti numbers, and simpliciality measures to study temporal, evolving, and coevolving networked systems. We introduce a multi-layer zigzag persistent homology framework for analyzing temporal hypergraphs across multiple timescales simultaneously, and validate it on the DARPA Operationally Transparent Cyber dataset, where it produces topological signatures that distinguish malicious from benign network activity by source IP. We then apply topological tools to classical generative network models and their hypergraph extensions, characterizing how Betti numbers, filling efficiencies, and simpliciality measures evolve as these models grow or …

Junk Journaling For Graphic Designers: Analog Play & Process In An Increasingly Digital Design Landscape, Kristina Rosgen

University Honors Theses

This thesis explores junk journaling as an accessible analog practice for young graphic designers experiencing digital fatigue, creative stress, and perfectionism. Through historical research, a hands-on workshop, and an interactive Readymag website, the project shows how junk journaling can help designers reconnect with play, process, physical materials, and the joy of making.

Hdfs Grpc Writer: A Unified High-Performance Data Ingestion Engine, Raouf Khan Mr, Mahendra Yadav Mr

Defensive Publications Series

The present disclosure relates to a method and a system for HDFS gRPC writer for unified, high-performance data ingestion system designed to modernize the way both streaming and batch data are written into HDFS. The present disclosure suggests single, scalable gRPC-based ingestion interface capable of handling multiple data formats, while also efficiently managing batching, schema evolution, fault tolerance, and security. After receiving the data, the present disclosure suggests HDFS gRPC writer addresses the small files problem at its source by implementing intelligent size-based and time-based batching. Thereafter, the present disclosure ensures optimal HDFS file sizes without the need for downstream …

Notifications Management Via Attention Budgeting And Collision Detection, Ashwin Goyal

Defensive Publications Series

Notifications to mobile devices that persist beyond their contextually relevant windows cease to be informative prompts and can become annoyances. Current notification paradigms treat the notification tray as a static, append-only data repository, placing the burden of notification lifecycle management and cleanup on the user. This disclosure describes automated notifications management techniques that transform notifications from static payloads into dynamic, self-resolving objects. The techniques include temporal notifications-lifecycle management, app-ecosystem intelligence, state synchronization, spatial optimization, device context, etc. Leveraging automated notification updates and retractions, the techniques reduce or eliminate disadvantages of persistent notifications. The techniques change the notification management paradigm by …