Digital Commons Network^™

The Invisible Influencer In Information Infrastructure, Herbert Van De Sompel, Michael L. Nelson

Computer Science Faculty Publications

The UPS Prototype was a proof-of-concept web portal built in preparation for the Universal Preprint Service Meeting held in October 1999 in Santa Fe, New Mexico. The portal provided search functionality for a set of metadata records that had been aggregated from a range of repositories that hosted preprints, working papers, and technical reports. Every search result was overlaid with a dynamically generated menu, called an SFX-menu, that provided a selection of value-adding links for the described scholarly work. The meeting eventually led to the Open Archives Initiative and its Protocol for Metadata Harvesting (OAI-PMH), which remains widely used in …

Sting: A Stealthy Backdoor Attack On Gnn-Based Malicious Domain Detection Via Dns Perturbations, Muhammad Anan, Mahmoud Nazzal, Abdallah Khreishah, Issa Khalil, Nhathai Phan, Ahmad Sawalmeh

Computer Science Faculty Publications

Detecting malicious Internet domains is essential for safeguarding against various online threats. The current approach to detecting malicious domains (MDD) employs a graph neural network (GNN) method, which uses DNS logs to construct heterogeneous graphs for determining the maliciousness of unknown domains. Despite its success, this method is vulnerable to data poisoning attacks where an adversary can manipulate specific graph nodes to implant a backdoor into the model during training. To showcase the vulnerability, we propose a stealthy trigger injection attack on node features and graph structure in MDD, dubbed (STING). The attacker carefully manipulates selected features and edges of …

Coldstartcpi: Induced-Fit Theory-Guided Dti Predictive Model With Improved Generalization Performance, Qichang Zhao, Haochen Zhao, Linyuan Gao, Kai Zheng, Yajie Li, Qiao Ling, Jing Tang, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Predicting compound-protein interactions (CPIs) plays a crucial role in drug discovery. Traditional methods, based on the key-lock theory and rigid docking, often fail with novel compounds and proteins due to their inability to account for molecular flexibility and the high sparsity of CPI data. Here, we introduce ColdstartCPI, a framework inspired by induced-fit theory, which leverages unsupervised pre-training features and a Transformer module to learn both compound and protein characteristics. ColdstartCPI treats proteins and compounds as flexible molecules during inference, aligning with biological insights. It outperforms state-of-the-art sequence-based models, particularly for unseen compounds and proteins, and shows strong generalization capability …

Insights In Adaptation: Examining Self-Reflection Strategies Of Job Seekers With Visual Impairments In India, Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Significant changes in the digital employment landscape, driven by rapid technological advancements and the COVID-19 pandemic, have introduced new opportunities for blind and visually impaired (BVI) individuals in developing countries like India. However, a significant portion of the BVI population in India remains unemployed despite extensive accessibility advancements and job search interventions. Therefore, we conducted semi-structured interviews with 20 BVI persons who were either pursuing or recently sought employment in the digital industry. Our findings reveal that despite gaining digital literacy and extensive training, BVI individuals struggle to meet industry requirements for fulfilling job openings. While they engage in self-reflection …

Coming Back Differently: An Exploratory Case Study Of Near Death Experiences Of Webpages, Lesley Frew, Michael L. Nelson, Michele Weigle

Computer Science Faculty Publications

In this case study, we use web archives to analyze 8,824 webpages that were taken offline and subsequently put back online, thus experiencing a “near death experience.” We enumerate the stages of a webpage’s near death experience, including the change from a successful HTTP status code to non-successful and back, the intermediate stage with markers such as an under construction banner, and an analysis of how the pages came back differently.

From Philosophy To Nlu: Evolving Definitions With Research Hypotheses, Jian Wu, Sarah Rajtmajer

Computer Science Faculty Publications

Over the past decades, alongside advancements in natural language processing, significant attention has been paid to training models to automatically extract, understand, test, and generate hypotheses in open and scientific domains. However, interpretations of the term hypothesis for various natural language understanding (NLU) tasks have migrated from traditional definitions in the natural, social, and formal sciences. Even within NLU, we observe differences defining hypotheses across literature. In this paper, we overview and delineate various definitions of hypothesis. Especially, we discern the nuances of definitions across recently published NLU tasks. We highlight the importance of well-structured and well-defined hypotheses, particularly as …

From Philosophy To Nlu: Evolving Definitions Of Research Hypotheses, Jian Wu, Sarah Rajtmajer

Computer Science Faculty Publications

Over the past decades, alongside advancements in natural language processing, significant attention has been paid to training models to automatically extract, understand, test, and generate hypotheses in open and scientific domains. However, interpretations of the term hypothesis for various natural language understanding (NLU) tasks have migrated from traditional definitions in the natural, social, and formal sciences. Even within NLU, we observe differences defining hypotheses across literature. In this paper, we overview and delineate various definitions of hypothesis. Especially, we discern the nuances of definitions across recently published NLU tasks. We highlight the importance of well-structured and well-defined hypotheses, particularly as …

S²Il: Structurally Stable Incremental Learning, S. Balasubramanian, P. Yedu Krishna, Talasu Sai Sriram, M. Sai Subramaniam, Manepalli Pranav Phanindra Sai, Ravi Mukkamala

Computer Science Faculty Publications

Feature Distillation (FD) strategies are proven to be effective in mitigating Catastrophic Forgetting (CF) seen in Class Incremental Learning (CIL). However, current FD approaches enforce strict alignment of feature magnitudes and directions across incremental steps, limiting the model’s ability to adapt to new knowledge. In this paper, we propose Structurally Stable Incremental Learning (S²IL), a FD method for CIL that mitigates forgetting by focusing on preserving the overall spatial patterns of features which promote flexible (plasticity) yet stable representations that preserve old knowledge (stability). We also demonstrate that our proposed method S²IL achieves strong incremental accuracy and outperforms other FD …

Humans Vs. Llms On Open Domain Scientific Claim Verification: A Baseline Study, Benjamin Curtis, Stefania Dzhaman, Matthew Maisonave, Jian Wu

Computer Science Faculty Publications

Verifying scientific claims is challenging for the general public because most people lack domain knowledge. Manual verification by subject domain experts is accurate, but it is obviously not scalable to meet the rising number of scientific claims on the Web. Whether the emerging large language models and large reasoning models can be used for scientific claim verification, and how their performances compare to humans, are still research questions. To this end, we developed a new benchmark MSVEC2 that consists of 138 claims from credible fact verification websites and science news outlets. Two tasks were given to both human and LLM …

Privshap: A Finer-Granularity Network Linearization Method For Private Inference, Xiangrui Xu, Zhenzhen Wang, Rui Ning, Chunsheng Xiu, Hongyi Wu

Computer Science Faculty Publications

Private inference applies cryptographic techniques like homomorphic encryption, garble circuit and secret sharing to keep both sides privacy in a client-server setting during inference. It is often hindered by the high communication overheads, especially at non-linear activation layers such as ReLU. Hence ReLU pruning has been widely recognized as an efficient way to accelerate private inference. Existing approaches to ReLU pruning typically rely on coarse hypothesis, which assume an inverse correlation between the importance of ReLU and linear layers or shallow activation layers have less importance for universal models, to assign the budgets according to the layer while preserving the …

From Ambiguity To Accountability: The Case For A Legal Definition Of Antisemitism In Academia, Andrea Martin

Faculty Scholarship

Following the October 7, 2023, Hamas attacks on Israel, U.S. college campuses experienced a sharp rise in antisemitic incidents, driven by an antizionism movement aimed at demonizing and delegitimizing the Jewish state and its supporters. A congressional investigation found that antisemitism persisted at prominent universities because administrators repeatedly failed to denounce antizionist conduct that functions as a vehicle for harassment of Jewish students and neglected to enforce their own nondiscrimination policies. The congressional committee, as well as several university antisemitism task forces, identified antizionism as a primary driver of campus antisemitism and strongly recommended that university leaders recognize and address …

Engineering Extracellular Vesicles (Evs) To Combat Infection And Inflammation In Cystic Fibrosis, Sharanya Sarkar

Dartmouth College Ph.D Dissertations

Cystic Fibrosis (CF) is a multisystemic genetic disorder caused by mutations in the CFTR gene, resulting in chronic pulmonary infections, hyperinflammation, and progressive lung damage. Among the pathogens that colonize CF lungs, Pseudomonas aeruginosa (P. aeruginosa) is predominant, infecting over 50% of adults with CF and developing antibiotic resistance over time. Current modulator therapies fail to address persistent bacterial infections, chronic inflammation, or irreversible lung damage, underscoring the need for novel therapeutic strategies. In our previous in vitro studies, we demonstrated that extracellular vesicles (EVs) secreted by primary Human Bronchial Epithelial Cells (HBECs) inhibit P. aeruginosa growth by reducing the …

Beyond Diagnostic Thresholds: Measures Of The Maternal Cardiometabolic Health Continuum And Their Association With Placental Function, Elizabeth Cook Anderson

Dartmouth College Ph.D Dissertations

Diabetes and hypertension during pregnancy adversely impact maternal and offspring health. Altered placental function is hypothesized to be involved, but impacts of elevated glucose and blood pressure (BP) within the subclinical range are unknown. The objective of this thesis is to evaluate how elevated glucose and BP, above and below diagnostic thresholds, impact measures of placental development and function including gross morphology (Aim 1), histopathology (Aim 2), and maternal circulating miRNAs (Aim 3), many of which originate in the placenta. Gross morphology and histopathology data from the New Hampshire Birth Cohort Study were used for Aims 1 and 2, and …

Integrated Roadside Vegetation Management Technical Manual [2025], Kristine Nemec, Josh Brandt, Kirk Henderson, Jim Uthe

Faculty Book Gallery

The objective of this publication is to provide basic technical support for new and existing Iowa county roadside programs. This manual is also intended to provide guidance to policymakers and engineers interested in adopting or expanding integrated roadside vegetation management in county rights-of-way.

Original Discontent, William Magnuson

Vanderbilt Law Review

There are many theories of constitutional interpretation. Most, but not all, assert that, in interpreting the U.S. Constitution’s provisions, we should start by taking seriously the intentions of the enactors, meaning, roughly speaking, its drafters, defenders, and ratifiers. This Article argues that, in doing so, judges, scholars, and policymakers have underestimated an important feature of the process of constitution-making: the discontent of the enactors themselves with the Constitution they were enacting. Time and again, during the Philadelphia Convention of 1787, during the penning of the Federalist Papers, and during the state ratifying conventions, the enactors expressed deep reservations about the …

Final Horseshoe Bend Effluent Line (Hbel) Discharge Structure Surface Enhancements Work Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

An Analytical Review Of Preprocessing Techniques In Bengali Natural Language Processing, Sovon Chakraborty, Protiva Das, Shakib Mahmud Dipto, Md Aktaruzzaman Pramanik, Jannatun Noor

Computer Science Faculty Publications

Research in Bengali Natural Language Processing (BNLP) is rapidly expanding. Despite being one of the most widely spoken languages in the world, BNLP research remains insufficient, particularly in Bengali speech recognition. The languages rich morphology, agglutinative structure, and diverse dialects make text and speech processing especially challenging. However, these challenges can be addressed with effective preprocessing techniques. Various organizations in Bangladesh and West Bengal are integrating Natural Language Processing (NLP) into their services, but without a thorough understanding of preprocessing, these implementations remain incomplete. Applying proper preprocessing techniques to the Bengali language will serve as a foundation for developing robust …

Position: Benchmarking Is Broken - Don't Let Ai Be Its Own Judge, Zerui Cheng, Stella Wohnig, Ruchika Gupta, Samiul Alam, Tassallah Abdullahi, João Alves Ribeiro, Christian Nielsen-Garcia, Saif Mir, Siran Li, Jason Orender, Seyed Ali Bahrainian, Daniel Kirste, Aaron Gokaslan, Carsten Eickhoff, Pramod Viswanath, Ruben Wolff

Computer Science Faculty Publications

The meteoric rise of Artificial Intelligence (AI), with its rapidly expanding market capitalization, presents both transformative opportunities and critical challenges. Chief among these is the urgent need for a new, unified paradigm for trustworthy evaluation, as current benchmarks increasingly reveal critical vulnerabilities. Issues like data contamination and selective reporting by model developers fuel hype, while inadequate data quality control can lead to biased evaluations that, even if unintentionally, may favor specific approaches. As a flood of participants enters the AI space, this "Wild West" of assessment makes distinguishing genuine progress from exaggerated claims exceptionally difficult. Such ambiguity blurs scientific signals …

Benchmarking Batch-Effect Correction Methods Towards The Construction Of A Triple-Negative Breast Cancer Cell Atlas, Peter Scheible, Amy H. Tang, Jing He, Jiangwen Sun

Computer Science Faculty Publications

Triple-negative breast cancer (TNBC) requires detailed cellular mapping given its aggressive nature, immense tumor heterogeneity and genetic diversity. We integrated 156,794 cells from six scRNA-seq datasets—including tumors, metastases, and cell lines—to build a TNBC scRNA cell atlas, focusing on batch effect mitigation while maintaining biological and molecular details. Preprocessing f ilters noise, normalizes data, and leverages PCA for integration readiness. We utilized scANVI, a semi-supervised tool, to align datasets, preserving TNBC’s complex tumor heterogeneity via marker annotations [1]. UMAPs demonstrate biological clustering in integrated data, contrasted with datasetdriven unintegrated patterns. Assessments verifying effective batch correction. This method aligns with NASA’s …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Computer Science Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

Multi-Modal Mri Based Segmentation Of Brain Metastases Using Adaptive Self-Attention, Evan Savaria

Computer Science Faculty Publications

Brain metastases (BMs) are the most common adult central nervous system malignancy, affecting 20–40% of cancer patients. Accurate segmentation of metastatic lesions in multi-modal MRI is essential for treatment planning and prognosis however, manual delineation is time consuming and prone to variability. Traditional deep learning models such as U-Net, have improved segmentation accuracy but capture limited long-range dependencies and struggle with variations in metastasis size, shape, and distribution. This study introduces the Adaptive Integrated Multi-modal Segmentation (AIMS) model, an adaptive self-attention framework within a hybrid U-Net and Transformer architecture to enhance BM segmentation by leveraging multi-modal MRI integration. The proposed …

Accessmenu: Enhancing Usability Of Online Restaurant Menus For Screen Reader Users, Nithiya Venkatraman, Akshay Kolgar Nayak, Suyog Dahal, Yash Prakash, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Online food ordering has become commonplace due to its convenience. The wide variety of culinary choices, combined with fast and economical door-delivery services, encourages more people to order food online. To facilitate this process, food vendors, including restaurants, often provide full menus on their websites, typically in visual formats such as images or PDFs. While this is convenient for sighted users, blind and visually impaired (BVI) individuals face significant challenges accessing these visual menus with their screen reader assistive technology. An interview study with 12 BVI screen reader users revealed that present assistive tools do not adequately satisfy the needs …

Adapting Online Customer Reviews For Blind Users: A Case Study Of Restaurant Reviews, Mohan Sunkara, Akshay Kolgar Nayak, Sandeep Kalari, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Online reviews have become an integral aspect of consumer decision-making on e-commerce websites, especially in the restaurant industry. Unlike sighted users who can visually skim through the reviews, perusing reviews remains challenging for blind users, who rely on screen reader assistive technology that supports predominantly one-dimensional narration of content via keyboard shortcuts. In an interview study, we uncovered numerous pain points of blind screen reader users with online restaurant reviews, notably, the listening fatigue and frustration after going through only the first few reviews. To address these issues, we developed QuickCue assistive tool that performs aspect-focused sentiment-driven summarization to reorganize …

Icu-Length Of Stay Prediction On Electronic Health Records Using Graph Neural Networks And Homogeneous Similarity Graphs, Ahmad F. Al Musawi, Pratip Rana, Sibtanu Raha, Joshua Braunstein, William C. Sleeman Iv, Rishabh Kapoor, Preetam Ghosh

Computer Science Faculty Publications

Predicting the length of stay (LoS) is important for hospital administration, as it helps allocate proper resources, such as bed management and hospital staffing. Patients' Electronic Health Records (EHRs) contain highly relevant data for LoS prediction; however, their integration and effective use in predictive modeling for accurately estimating LoS remain challenging. To address this, we propose a homogeneous Graph Neural Network (GNN)-based framework for predicting LoS. This method employs a comprehensive data fusion strategy based on the hospital Visit-based Similarity Graph (VSG), which integrates diverse multi-modal clinical features into a coherent, homogeneous graph representation. Next, this VSG is fed into …

Characterizing Language Use In Online Accessibility Discussion Forums, Nithiya Venkatraman, Anand Ravi Aiyer, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Discussion forums are one of the favored platforms for knowledge sharing. Given their popularity, copious research exists on understanding the linguistic and behavioral characteristics of forum conversations, so as to inform the design of many downstream applications including discourse visualization, sentiment analysis, and question answering. However, prior investigations have mainly focused on general forums designed primarily for sighted users, and as such the applicability of their findings to dedicated accessibility discussion forums frequented by blind screen reader users remains unanswered. To bridge this knowledge gap and facilitate the development of better-informed assistive technologies for blind people, we investigated language use …

Keynote Address For The 2025 University Of The Pacific Law Review Symposium: The Crime Victims' Rights Movement: Historical Foundations, Modern Ascendancy, And Future Aspirations, Paul Cassell

Utah Law Faculty Scholarship

This article, which serves as the keynote address for the 2025 University of Pacific Law Review Symposium, explores the past, present, and future of America's crime victims' rights movement-one of the most successful social movements in modern history.

Historically, crime victims played a central role in criminal justice processes through private prosecutions-i.e., the ability of victims to initiate or participate in criminal prosecutions. Today, while private prosecutions have been largely supplanted by public prosecutions, the victims' rights movement has successfully restored the victims' voice in criminal processes. The movement has reformed contemporary American criminal justice so that criminal processes now …

Loper Bright’S Deregulatory Synergies, Renee Farmer, Daniel G. Aaron

Utah Law Faculty Scholarship

For over 40 years, Chevron U.S.A. v. National Resources Defense Council stood as a keystone of administrative law. It infused agencies with the discretion to leverage the edges of statutory language and granted them the security that day-to-day agency actions would survive judicial review. Although Chevron’s demise in Loper Bright Enterprises v. Raimondo elicited rebuke from many legal scholars, it struck some as unsurprising, unimportant, or unconcerning, whether due to the narrowing of Chevron over time, the Supreme Court’s disuse of it in recent years, or the belief that its holding flew in the face of the Administrative Procedure Act. …

Future Giving Intention As Related To An Individual's Donor And Volunteer Status Within A Charitable Nonprofit Organization, Adrienne Darrah

Iowa Journal of Communication

Charitable nonprofit organizations have a responsibility not only to the communities they serve but also to the individuals who support them. When nonprofits fail to act as good stewards of raised monies, they may find themselves caught in a scandal that not only holds legal ramifications but financial and ethical implications as well. Drawing on resource dependence and stewardship theories, manipulated stimuli related the American Red Cross’ response to the 2010 Haitian earthquake was utilized to analyze the relationship between future giving intention and current monetary donor, blood donor, and volunteer status. This paper also considers crisis communication in examining …

Breaking Barriers: Designing An Effective Early Intervention Process For Enhanced Developmental Outcomes In Private Schools, Breanne Kristen Cox

Graduate Student Dissertations, Theses, Capstones, and Portfolios

The challenge of ensuring inclusive and equitable support for students with disabilities is increasingly prominent in education, particularly in private school settings. This dissertation explored the implementation and effectiveness of an early literacy intervention process, the “Bright Beginnings Boost Initiative,” in a small Montessori preschool in South Florida. The study addresses the gap in support services for students with disabilities in private schools, which often lack the comprehensive frameworks mandated by public education systems under the Individuals with Disabilities Education Act (IDEA).

Through a qualitative two-phase action research design, this study gathered insights from preschool teachers, the preschool director, the …

Discriminatory Censorship Laws, Jonathan Feingold, Joshua Weishart

Faculty Scholarship

The summer of 2020 ignited global protests for racial justice. Across the United States, millions marched with a modest plea: that America reckon with its racism. For K-12 schools, this moment pushed local communities and district leaders to create more inclusive classrooms and curricula. Yet before the summer had ended, America's antiracist turn provoked a backlash campaign that has proven far more impactful and enduring.

This campaign has featured the rise and spread of "discriminatory censorship laws"-a term we apply to government action designed to demean inclusionary values and to deny students access to critical knowledge, inquiry, and thinking. As …