Digital Commons Network^™

Connecticut, Elizabeth Ford

Thin Blue Advantage: Police Exceptionalism and the Two-Tier System of Public Sector Collective Bargaining

In general, the Connecticut commission is hostile to expansive definitions of mandatory subjects of bargaining, sometimes issuing decisions that are results-driven and an expression of a preference for the substance of the employer’s decision. There are a couple of distinctions between police and other units:

• The Commission is more likely to weigh safety on the side of bargaining for police than others.
• The Commission treats the requirement to bargain surveillance-based decision more expansively for non-police units than police-units.

The Commission is more likely to find subcontracting of police work to an outside agency to be a mandatory subject of bargaining.

Iowa, Elizabeth Ford

Thin Blue Advantage: Police Exceptionalism and the Two-Tier System of Public Sector Collective Bargaining

In general, the differences between police and non-police units are dramatic. This is mostly due to statutory changes in 2017, making the scope of bargaining much more constrained for non-police bargaining units. Those amendments also constrained the scope of an interest arbitrator’s decision, again excluding police units. There are not many Board decisions in Iowa, and even fewer after 2017, but in the cases that exist, there are differences even before the statutory amendment.

Illinois, Elizabeth Ford

Thin Blue Advantage: Police Exceptionalism and the Two-Tier System of Public Sector Collective Bargaining

As compared with other states, the Illinois Labor Relations Board (“ILRB” or “Board) is unusually protective of the right to bargain. The Board is more protective still of the ability of police unions to bargain over employer decisions. In the last several years in cases involving the Chicago Police Department, the Board has moderated somewhat by, in key cases, refusing to issue a decision but rather holding the matter “in abeyance.” A few highlights follow:

• Only Police Have the Right to Interest Arbitration. The Illinois Labor Relations Act requires police bargaining units to resolve contractual impasses through interest arbitration. …

Delaware, Elizabeth Ford

Thin Blue Advantage: Police Exceptionalism and the Two-Tier System of Public Sector Collective Bargaining

Delaware law governing police and non-police bargaining is separated into two largely identical statutory schemes. Both statutes provide for interest arbitration and adopt “baseball arbitration” to expedite the arbitration process. Keeping with the goal of expedient dispute resolution, the state’s ULP process seems designed to facilitate settlement.

As a result of this ULP structure, there are few cases from Delaware’s PERB compared to other states. This may have to do with the fact that the myriad preliminary stages of ULP proceedings serve as “off-ramps” to encourage settlement and that the agency’s Executive Director (E.D.) has more power than non-Delaware analogs. …

Assessing Inter-Organizational Collaboration Within The Transboundary Network Governing The Conservation Of Southern Resident Killer Whales, Dane Pedersen, Owen Temby, Antonia Sohns, Evelyn Roozee, Gordon M. Hickey

School of Earth, Environmental, & Marine Sciences Faculty Publications

The Southern Resident Killer Whale (SRKW) is an endangered and charismatic species whose home range spans the Salish Sea, an ecosystem that extends across the Canada-US border. Conserving and recovering the SRKW represents a high-profile transboundary governance challenge that depends heavily on collaboration between a wide range of organizations. To better understand the factors affecting transboundary SRKW governance in the Salish Sea, this study applies a multi-dimensional trust, control, perceived risk framework to assess the inter-organizational architecture supporting collaboration. The analysis is based on key informant interviews (n=32) and surveys (n=35) conducted with policy actors working for different organizations involved …

Lrtm Left-Right Transition Matrices For Molecular Interaction Prediction, Kaitlin Zheng, Guihua Duan, Mengyun Yang, Wei Wu, Yao-Hang Li, Jianxin Wang

Computer Science Faculty Publications

Molecular interactions are central to most biological processes. The discovery and identification of potential associations between molecules can provide insights into biological exploration, diagnostic and therapeutic interventions, and drug development. So far many relevant computational methods have been proposed, but most of them are usually limited to specific domains and rely on complex preprocessing procedures, which restricts the models’ ability to be applied to other tasks. Therefore, it remains a challenge to explore a generalized approach to accurately predicting potential associations. In this study, We propose Left-Right Transition Matrices (LRTM) for molecular interaction prediction. From the perspective on the diffusion …

Vaim-Cff: A Variational Autoencoder Inverse Mapper Solution To Compton Form Factor Extraction From Deeply Virtual Compton Scattering, Manal Almaeen, Tareq Alghamdi, Brandon Kriesten, Douglas Adams, Yaohang Li, Huey-Wen Lin, Simonetta Liuti

Computer Science Faculty Publications

We develop a new methodology for extracting Compton form factors (CFFs) from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized inverse problem solver, a variational autoencoder inverse mapper (VAIM). The VAIM-CFF framework not only allows us access to a fitted solution set possibly containing multiple solutions in the extraction of all 8 CFFs from a single cross section measurement, but also accesses the lost information contained in the forward mapping from CFFs to cross section. We investigate various assumptions and their effects on the predicted CFFs such as cross section organization, number of extracted …

Cath-Ddg: Towards Robust Mutation Effect Prediction On Protein-Protein Interactions Out Of Cath Homologous Superfamily, Guanglei Yu, Xuehua Bi, Teng Ma, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Protein-protein interactions (PPIs) are fundamental aspects in understanding biological processes. Accurately predicting the effects of mutations on PPIs remains a critical requirement for drug design and disease mechanistic studies. Recently, deep learning models using protein 3D structures have become predominant for predicting mutation effects. However, significant challenges remain in practical applications, in part due to the considerable disparity in generalization capabilities between easy and hard mutations. Specifically, a hard mutation is defined as one with its maximum TM-score < 0.6 when compared to the training set. Additionally, compared to physics-based approaches, deep learning models may overestimate performance due to potential data leakage.

Results: We propose new training/test splits that mitigate data leakage according to the CATH homologous superfamily. Under the constraints of physical …

Optiselect And Enshap: Integrating Machine Learning And Game Theory For Ischemic Stroke Prediction, Pritam Chakraborty, Anjan Bandyopadhyay, Sricheta Parul, Sujata Swain, Partha Sarathy Banerjee, Tapas Si, Hong Qin, Saurav Mallik

Computer Science Faculty Publications

Stroke analysis using game theory and machine learning techniques. The study investigates the use of the Shapley value in predictive ischemic brain stroke analysis. Initially, preference algorithms identify the most important features in various machine learning models, including logistic regression, K-nearest neighbor, decision tree, support vector machine (linear kernel), support vector machine ( RBF kernel), neural networks, etc. For each sample, the top 3, 4, and 5 features are evaluated and selected to evaluate their performance. The Shapley value method was used to rank the models using their best four features based on their predictive capabilities. As a result, better-performing …

Ai For Nuclear Physics: The Exclaim Project, S. Liuti, D. Adams, M. Boër, G. W. Chern, M. Cuic, M. Engelhardt, G. R. Goldstein, B. Kriesten, Y. Li, H. W. Lin, M. Sievert, D. Sivers

Computer Science Faculty Publications

An overview of the recent activity of the newly funded EXCLusives with AI and Machine learning (EXCLAIM) collaboration is presented. The main goal of the collaboration is to develop a framework to implement AI and machine learning techniques in problems emerging from the phenomenology of high energy exclusive scattering processes from nucleons and nuclei, maximizing the information that can be extracted from various sets of experimental data, while implementing theoretical constraints from lattice QCD. A specific perspective embraced by EXCLAIM is to use the methods of theoretical physics to understand the working of ML, beyond its standardized applications to physics …

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 …

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 …

Effective Pii Extraction From Llms Through Augmented Few-Shot Learning, Shuai Cheng, Shu Meng, Haitao Xu, Haoran Zhang, Shuai Hao, Chuan Yue, Wenrui Ma, Meng Han, Fang Zhang, Zhao Li

Computer Science Faculty Publications

Large Language Models (LLMs) exhibit strong natural language processing capabilities but also pose significant privacy risks, particularly regarding the leakage of Personally Identifiable Information (PII) embedded in their training data. Existing PII extraction methods suffer from the limitations of low success rates or impracticality for large-scale PII extraction. In this study, we propose a novel PII extraction approach based on enhanced few-shot learning techniques, which achieves efficient and cost-effective PII retrieval without relying on fine-tuning or jailbreaking. We evaluated our approach on both open-source and closed-source LLMs. The experimental results demonstrate that, for non-targeted PII extraction, the attack success rate …

Exploring The Educational Gap Of Virginia English Language Learners: Challenges And Opportunities For Academic Success, Amanda Purcell, Sochitl Rodriguez Kauffman

UROP Posters

English Language Learners (ELLs) in the state of Virginia have significantly lower scores in the Standards of Learning (SOL) assessment exam than those of their English-speaking peers. The SOL measures students’ mastery of knowledge and skills taught in the classroom, and over the last decade, passing rates of the assessment’s core subjects amongst ELLs have continued to decrease and remain relatively low. In the 2023-2024 academic year, the average passing rate for ELLs who took the Writing SOL was only 26%, with Science being not much higher at 29%, and Reading at 33%. For the non-ELL student body, average rates …

Ocean Acidification Mitigation: Potential Expansion Of Sav Restoration Strategy In The Chesapeake Bay, Cree N. Taylor

UROP Posters

Zostera marina is a species of marine macrophyte that has been largely prioritized in past submerged aquatic vegetation (SAV) restoration initiatives within the Chesapeake Bay because of its 1) previous abundance, 2) demonstrated carbon burial abilities, and 3) observed ability for meadows of Z. marina to ameliorate low pH conditions. Due to the temperature variability and poor water quality associated with anthropogenic disturbances in the Chesapeake Bay, Z. Marina beds have experienced several die-off events with limited capacity for regrowth. This systematic review explored the possible benefits of focusing future SAV recovery initiatives on ensuring a diverse variety of SAV …

Affordable And Sustainable: Innovating Filament Extrusion For Recycled Materials, Turab S. Rizvi

UROP Posters

The chemical stability, toxicity and non-biodegradability of the polymers pose a significant environmental threat. Addressing end-of-life treatment sustainability is crucial for mitigating these issues. The customized Lyman filament extruder in the Advanced Magnetic Materials Processing Laboratory represents an innovative approach to advancing sustainability in renewable energy production and CO₂ mitigation. Redesigning the thermal system and screw operation will tackle key challenges, including precise temperature control, consistent material flow to handle diverse recycled materials. Integrating an advanced thermal regulation system will reduce the energy consumption by maintaining optimal thermal conditions, thereby lowering the CO₂ footprint of the recycling process. The optimized …

The Romanticization Of Human-Vampire Relationships: How 'Twilight' And 'The Vampire Diaries' May Prime Young Women To Accept Dating Violence, Natalie M. Bowen

UROP Posters

The first literary vampire can be traced back to 18th century Germany, with Johann Wolfgang von Goethe’s poem “Die Braut von Korinth,” but the stereotypical features of a vampire are traditionally accredited to Bram Stoker’s Dracula. Modern vampires, such as Edward Cullen and Stefan Salvatore of the Twilight and The Vampire Diaries series respectively, have managed to win the hearts of teenage girls all across America with their sex appeal and charismatic nature. According to Bandura’s Social Cognitive Theory, individuals learn new behaviors by modeling and imitating the actions of those around them. This comprehensive literature review investigates the connection …

Using Test-Crosses To Investigate Mendelian Inheritance Patterns In Brassica Rapa, Jacob Batson, Amy Nguyen, Ethan Do

UROP Posters

The Wisconsin Fast Plants, Brassica rapa, are an ideal model organism for exploring patterns of inheritance and phenotype expression due to their rapid life cycle and observable traits. In this experiment, we examined the controlled crosses between the two phenotypes, anthocyanin-producing (ACN) and anthocyaninless (ANL), to observe allele inheritance. We observed phenotypes in the F1 generation to see if it followed the Mendelian inheritance patterns of homozygous dominant. By planting and watering the plants for two weeks, we tracked their growth and traits of ACN and ANL phenotypes. We used honey bees to cross pollinate the parent ACN and ANL …

Analysis Of Differential Gene Expression In Androgen-Independent Clones Derived From The Mycap Pca Cell Line, Jessie L. Tignor, Melanie Sinanian, Richard Inho Joh, David Gewirtz, Jason Reed

UROP Posters

Androgen deprivation therapy (ADT) is a primary treatment strategy for prostate cancer (PCa), yet many tumors eventually develop androgen independence, leading to treatment resistance. To investigate the molecular changes underlying this transition, we analyzed differential gene expression in four androgen-independent (AI) clones derived from the Myc-CaP prostate cancer cell line using RNA sequencing. Gene expression profiles were compared to the parental Myc-CaP line, and differentially expressed genes (DEGs) were identified using DESeq2 and edgeR. The AI clones exhibited significant downregulation of senescence-associated genes, including Ezh2 and lamin B1, suggesting a loss of senescence-related chromatin repression. Additionally, upregulation of Wnt pathway …

The Built Environment And The Systemic Agenda, Heciel J. Nieves Bonilla

UROP Posters

The built environment in the United States, characterized in large part by suburban sprawl and car-dependent infrastructure, has significant negative impacts on public health, economic mobility, and environmental sustainability. This paper examines the consequences of car-centric development, highlighting its role in exacerbating social and economic inequalities, increasing traffic-related fatalities, and contributing to climate change through excessive carbon emissions. The analysis reveals that a majority of Americans feel forced into car ownership due to inadequate alternative transportation options, leading to financial strain and adverse health outcomes, including obesity and air pollution-related diseases. The historical roots of these development patterns are traced …

Acer Rubrum: Descending Towards Forest Dominance, Elyssa L. Pearson, Christopher M. Gough

UROP Posters

Acer rubrum, more commonly known as the red maple, is a hardwood, late successional species of tree commonly planted for its deciduous nature and vibrant coloring of its leaves in the beginning of autumn (Abrams, 1998). The species is very tolerant of varying light and soil moisture levels and often dominates sub and mid-canopy levels of hardwood forests (Missouri Botanical Gardens). It was hypothesized that as the I moved from an upland location to a lowland location near a wetland that the A. rubrum trees would be more productive and have a greater above ground biomass. This was not …

Examining Sociodemographic And Clinical Factors Associated With Smoking Behaviors Among Black Breast And Gynecological Cancer Survivors, Ida M. Adeso, Jian He, Ashley Turner, Arnethea L. Sutton

UROP Posters

Black breast and gynecological cancer survivors experience poorer outcomes than their non-Black counterparts. Although multifactorial, one contributor may be cigarette smoking behaviors. The purpose of this study was to identify demographic, clinical, and social drivers of health (SDoH) factors associated with smoking behaviors in Black breast and gynecological cancer survivors.

We conducted a secondary analysis of survey data collected from an ongoing cross-sectional study. Summary statistics (e.g., means, frequencies) were computed for all factors of interest. Chi square test of independence, t test, and logistic regression assessed the associations between demographic, clinical, and SDoH factors (e.g., social support) and the …

Still Faces, Different Places: An Assessment Of The Literature On The Face-To-Face Still Face Procedure For Cultural Congruence, Merilyn Arikkat, Leslie B. Lantz, Patricia Kinser

UROP Posters

Cultural understanding is a factor that impacts reliability of research results for observational studies. It is important to include participants of minority groups in research, as many people of color face disproportionate challenges in terms of healthcare access and resources. Within the context of mother-infant attachment, a technique known as the Face-to-Face Still Face procedure can be utilized to observe attachment styles and the bond between a parent and their infant. In order to combat subjectivity within the coding process for this Face-to-Face Still Face procedure, cultural congruence between the participants being observed in the study and the coding researchers …

Using Fungal Dna Barcoding To Identify Fungal Species In A James River Park System Soil Microbiome, Erwin Murray, D Jennings

UROP Posters

Fungi in the soil have the ability to form mutualistic relationships with plant roots and improve the way they resist a variety of plant diseases and abiotic stressors, influencing the survivability of the plants. The James River Park System (JRPS) is home to a variety of ecosystems that support diverse plant and fungal populations, including native plants and invasive plants. Therefore, it is important to identify what is present in the soil microbiome. The purpose of this project is to isolate fungal sequences from soil samples collected in the JRPS to identify what fungal species are present in the JRPS …

Isolation And Molecular Identification Of Pathogens Causing Sea Turtle Egg Fusariosis In Key Nesting Beaches In Costa Rica, Keilor E. Cordero-Umaña, Ruth Hernando-Martínez, María Martínez-Ríos, Jaime Restrepo, Roldán A. Valverde, Laura Martín-Torrijos, Pilar Santidrián Tomillo, Javier Diéguez-Uribeondo

School of Earth, Environmental, & Marine Sciences Faculty Publications

The global rise of fungal pathogens presents an emerging threat to biodiversity, with significant risks to species such as endangered sea turtles. The fungal disease known as sea turtle egg fusariosis (STEF) is associated with high embryo mortality rates and represents a substantial conservation challenge. This disease is caused by two fungal species, namely Fusarium falciforme (Ff) and Fusarium keratoplasticum (Fk), and their identification is essential for guiding future efforts to address potential fungal infections, particularly on important nesting beaches such as those in Costa Rica. In this study, we conducted fungal isolations from sea turtle eggshells …

Doping Hybrid Photopolymerisable Glass With Bodipy Photosensitiser: An Efficient Approach To Improve Uv-Resistance, Luca Sorridente, Tatsiana Mikulchyk, Metodej Dvoracek, Mikhail A. Filatov, Izabela Naydenova, Kevin P. Murphy

Conference Papers

The development of photosensitive materials with improved performance and extended functionality is crucial for advancing holographic technologies. This study presents the modification and characterization of a recently reported photopolymerisable glass composition, focusing on achieving an optimal balance between maximizing photosensitivity of the material during recording and minimizing the impact of UV light on the performance of the recorded holographic structure. Building on these findings, the ultimate goal is to develop UV-resistant holographic optical elements for wavefront sensing in space applications. The research approach is based on introducing a photosensitiser with weaker UV absorption than the typically used in this material …

Unprecedented Visible Light-Initiated Topochemical [2 + 2] Cycloaddition In A Functionalized Bimane Dye, Metodej Dvoracek, Brendan Twamley, Mathias O. Senge, Mikhail A. Filatov

Research Outputs: 2025-Present

Bimanes, a class of molecules based on the 1H,7H-pyrazolo[1,2-a]pyrazole-1,7-dione scaffold, were first introduced by E. M. Kosower in 1978. In this study, we report the topochemical cycloaddition of diethyl 2,6-dichloro-1,7-dioxo-1H,7H-pyrazolo[1,2-a]pyrazole-3,5-dicarboxylate (Cl₂B), initiated by visible light. Crystal structure analysis confirmed that the reactive double bonds are parallel and coplanar, in line with the Schmidt criteria for topochemical cycloaddition. Additionally, two other bimane derivatives with different substitution patterns were synthesized and investigated. Our findings suggest that functionalizing bimanes to redshift their absorption maxima into the visible-light spectrum provides a promising strategy for synthesizing substituted cyclobutanes without the need for ultraviolet …

A New G Family: Properties, Characterizations, Different Estimation Methods And Port-Var Analysis For U.K. Insurance Claims And U.S. House Prices Data Sets, Ahmad M. Aboalkhair, Gholamhossein Hamedani, Nazar Ali Ahmed, Mohamed Ibrahim, Mohammad A. Zayed, Haitham M. Yousof

Mathematical and Statistical Science Faculty Research and Publications

This paper introduces a new class of probability distributions, termed the generated log exponentiated polynomial (GLEP) family, designed to enhance flexibility in modeling complex real financial data. The proposed family is constructed through a novel cumulative distribution function that combines logarithmic and exponentiated polynomial structures, allowing for rich distributional shapes and tail behaviors. We present comprehensive mathematical properties, including useful series expansions for the density, cumulative, and quantile functions, which facilitate the derivation of moments, generating functions, and order statistics. Characterization results based on the reverse hazard function and conditional expectations are established. The model parameters are estimated using various …

A Bayesian Complex-Valued Latent Variable Model Applied To Functional Magnetic Resonance Imaging, Chase J. Sakitis, D. Andrew Brown, Daniel B. Rowe

Mathematical and Statistical Science Faculty Research and Publications

In linear regression, the coefficients are simple to estimate using the least squares method with a known design matrix for the observed measurements. However, real-world applications may encounter complications such as an unknown design matrix and complex-valued parameters. The design matrix can be estimated from prior information but can potentially cause an inverse problem when multiplying by the transpose as it is generally ill-conditioned. This can be combat by adding regularizers to the model but does not always mitigate the issues. Here, we propose our Bayesian approach to a complex-valued latent variable linear model with an application to functional magnetic …

Bayesian Merged Utilization Of Grappa And Sense (Bmugs) For In-Plane Accelerated Reconstruction Increases Fmri Detection Power, Chase J. Sakitis, Daniel B. Rowe

Mathematical and Statistical Science Faculty Research and Publications

In fMRI, capturing brain activity during a task is dependent on how quickly the k-space arrays for each volume image are obtained. Acquiring the full k-space arrays can take a considerable amount of time. Under-sampling k-space reduces the acquisition time, but results in aliased, or “folded,” images after applying the inverse Fourier transform (IFT). GeneRalized Autocalibrating Partial Parallel Acquisition (GRAPPA) and SENSitivity Encoding (SENSE) are parallel imaging techniques that yield reconstructed images from subsampled arrays of k-space. With GRAPPA operating in the spatial frequency domain and SENSE in image space, these techniques have been separate but can …