Digital Commons Network^™

Design And Manufacturing Of Multifunctional Piezoelectric Composites, Huan Zhao

Dartmouth College Ph.D Dissertations

Piezoelectric materials possess a unique ability to convert mechanical energy into electrical signals and have broad industrial applications. However, monolithic piezoelectric materials such as piezoceramics and piezopolymers often suffer from inherent trade-offs among mechanical strength, elasticity, and durability. Piezoelectric composites, typically consisting of a polymer matrix with ceramic reinforcements, offer a solution by combining the advantages of each constituent. Nevertheless, maintaining stable mechanical performance in high-temperature environments remains a significant challenge as conventional polymer matrices usually experience structural degradation.

In this thesis, a novel piezoelectric composite is developed using a preceramic polymer (PCP) matrix with barium titanate (BTO) inclusions. PCPs …

Optical Methods For Time-Resolved Dosimetry And Oximetry Of Ultra-High Dose Rate Radiation Therapy, Megan A. Clark

Dartmouth College Ph.D Dissertations

Radiotherapy (RT) is a cornerstone method used to treat over 50% of the 2 million new cancer diagnoses each year in the United States. The success of RT directly relies on an optimal balance between maximizing the dose to the tumor while minimizing dose to surrounding normal tissues. Achieving this balance is often challenging due to underlying radiation transport and the presence of anatomical constraints that limit the beam delivery geometry. In turn, minimizing healthy tissue toxicity prevents use of a more aggressive tumor killing approach, and even in curative cases may decrease the patient’s quality of life due to …

Understanding Oncology Physician Movement And Its Implications On Cancer Care Teams And Patients, Sarah L. Cornelius

Dartmouth College Ph.D Dissertations

Nearly 20% of oncology physicians planned to move to new practices or leave practice altogether in 2023, with common stressors related to limited staffing and increased clinical burden. This combination of movement and departures is collectively referred to as turnover. High-quality cancer care relies on access to well-staffed and coordinated clinical teams, and thus, turnover within these teams can compromise care access, delivery, and quality. Prior research within primary care has demonstrated that turnover can result in delayed or worsened care and higher health care spending. However, there are limited studies of turnover within the oncology workforce. Understanding how oncology …

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.

Discharging Government Debt, Nicole Langston

Vanderbilt Law Review

The bankruptcy system tries to strike a balance between a fresh economic start through debt forgiveness, or discharge, and the need to repay creditors. When the debt is owed to the government, however, the scale seemingly tips toward repayment because of the government’s role in providing essential services to society. But there are certain debts owed to the government that can be forgiven in bankruptcy and some that cannot. The consumer bankruptcy system does not forgive government-owed child support debt, penal debt, and student loan debt, which are disproportionally carried by poor women and racial minorities, but the system does …

Draft Final Silver Bow Creek Conservation Area Repository Data Gap Data Summary Report (Dsr), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

This Silver Bow Creek Conservation Area (SBCCA) Repository Data Gap Data Summary Report (DSR) presents the results from the soil sampling activities conducted as specified in the SBCCA Repository Data Gap Quality Assurance Project Plan (QAPP) (referred to herein as the SBCCA Repository Data Gap QAPP; Atlantic Richfield Company, 2024). The information presented in this DSR includes laboratory analytical results from subsurface soil sampling collected from Buffalo Gulch (BG), Butte Reduction Works (BRW), Diggings East (DE), and Northside Tailings (NST) within the SBCCA. This DSR was prepared by Pioneer Technical Services, Inc. (Pioneer), 1101 S. Montana Street, Butte, Montana 59701 …

Draft Final Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites: Ur-03 Site Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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.

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 …

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 …

A Survey On Deep Learning For Drug-Target Binding Prediction: Models, Benchmarks, Evaluation, And Case Studies, Kusal Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Conventional drug discovery is expensive, time-consuming, and prone to failure. Artificial intelligence has become a potent substitute over the last decade, providing strong answers to challenging biological issues in this field. Among these difficulties, drug-target binding (DTB) is a key component of drug discovery techniques. In this context, drug-target affinity and drug–target interaction are complementary and essential frameworks that work together to improve our comprehension of DTB dynamics. In this work, we thoroughly analyze the most recent deep learning models, popular benchmark datasets, and assessment metrics for DTB prediction. We look at the paradigm shift in the development of drug …

Decode The Workload: Training Deep Learning Models For Efficient Compute Cluster Representation, Ahmed Hossam Mohammed, Mark Jones, Diana Mcspadden, Malachi Schram, Bryan Hess, Kishansingh Rajput

Computer Science Faculty Publications

In this study, we address the mounting challenge of monitoring high throughput computing clusters running computationally intensive jobs, which increasingly strains system administrators. We develop autoencoders that analyze traces of Linux kernel CPU metrics to capture salient system features by producing robust compressed embeddings for various downstream tasks. In addition, we employ graph neural networks to incorporate contextual information from surrounding CPUs and assess their performance. We also demonstrate the enhanced job differentiation achieved by increasing the sampling rate of these traces. Our models are evaluated based on their ability to generate meaningful latent representations, detect anomalies, and distinguish between …

Deepssetracer 2.0: Improved Deep Learning Model Performance For Protein Secondary Structure Segmentation From Cryo-Em Maps, Bryan Hawickhorst, Thu Nguyen, Willy Wriggers, Jiangwen Sun, Jing He

Computer Science Faculty Publications

DeepSSETracer is a method for segmenting protein secondary structure from medium-resolution (5-10Å) cryogenic electron microscopy (cryo-EM) density maps. We conducted experiments and ablation studies to examine the effects of normalization methods, max-pooling, activation functions, and loss calculation region on DeepSSETracer. By combining multiple technical improvements, the performance of the new version, DeepSSETracer 2.0, was significantly enhanced compared to DeepSSETracer 1.1. On a set of 77 test cases, the weighted average per-voxel F1 score increased from 62.1% to 70.3% for helix detection, and from 47.8% to 62.5% for β-sheet detection. While each of the five modifications in the network enhanced the …

Benchmarking And Improving Foundation Model Dietary Estimates From Meal Images, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Accurate quantifying dietary contents, such as calories, proteins, carbohydrates, and fats, from an image of a meal plate is vital for managing diabetes. Recently, Large Multimodal Models (LMMs) have excelled in complex vision-language tasks due to their use of very large, highly diverse data. This study benchmarked the use of seven LMMs that include full and lightweight models of GPT, Gemini, and Llama for nutrition estimation based on Google's Nutrition5k dataset and our own phone-collected DonateAndLearn dataset. We analyzed the performance of LMMs and the RGB-D fusion model, in which the RGB-D model was specifically trained using Nutrition5k data. On …

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 …

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 …

A Plain Language Summary Of The Final Analysis Of The Griffin Study Of Daratumumab Plus Lenalidomide, Bortezomib, And Dexamethasone For People With Newly Diagnosed Multiple Myeloma, Peter M Voorhees, Douglas W Sborov, Jacob Laubach, Jonathan L Kaufman, Brandi Reeves, Cesar Rodriguez, Rebecca Silbermann, Luciano J Costa, Larry D Anderson, Nitya Nathwani, Nina Shah, Naresh Bumma, Yvonne A Efebera, Sarah A Holstein, Caitlin Costello, Andrzej Jakubowiak, Tanya M Wildes, Robert Z Orlowski, Kenneth H Shain, Andrew J Cowan, Shira Dinner, Katharine S Gries, Huiling Pei, Annelore Cortoos, Sharmila Patel, Thomas S Lin, Saad Z Usmani, Paul G Richardson

Faculty, Staff and Student Publications

No abstract provided.

Longitudinal Genomic Profiling Of Chemotherapy-Related Chip Variants In Patients With Ovarian Cancer, Sara Corvigno, Jun Yao, Amma Asare, Li Zhao, Joseph Celestino, Richard A Hajek, Ency A Arboleda Goette, Ridge T Rogers, Raymond N Montoya, Ping Song, Qingxiu C Zhang, Xingzhi Song, Mohammad M Mohammad, Kenna R Shaw, Jianhua Zhang, Karen H Lu, Amir A Jazaeri, Shannon N Westin, Anil K Sood, Sanghoon Lee

Faculty, Staff and Student Publications

Introduction: Clonal hematopoiesis (CH) is characterized by the presence of hematopoietic stem cells (HSCs) with the potential of clonally expanding and giving rise to hematological malignancies. Clonal hematopoiesis of indeterminate potential (CHIP) is the outgrowth of a single HSC clone with an acquired somatic mutation in the absence of hematological abnormalities. CHIP variants occur with a variant allele frequency (VAF) of at least 2% in peripheral blood. This definition does not account for less frequent mutations that give rise to hematopoietic clones. Previous studies indicate an association between CH and secondary hematologic malignancies in cancer patients who receive chemotherapy.

Methods: …

A Serum Biomarker Panel And Miniarray Detection System For Tracking Disease Activity And Flare Risk In Lupus Nephritis, Chenling Tang, Gongjun Tan, Aygun Teymur, Jiechang Guo, Arturo Haces-Garcia, Weihang Zhu, Richard Williams, Jing Ning, Ramesh Saxena, Tianfu Wu

Faculty, Staff and Student Publications

Introduction: Lupus nephritis (LN) leads to end stage renal disease (ESRD), and early diagnosis and disease monitoring of LN could significantly reduce the risk. however, there is not such a system clinically. In this study we aim to develop a biomarker-panel based point-of-care system for LN.

Methods: Immunoassay screening combined with genomic expression databases and machine learning techniques was used to identify a biomarker panel of LN. A quantitative biomarker-panel mini-array (BPMA) system was developed and the sensitivity, specificity, reproducibility, and stability of the were examined. The performance of BPMA in disease monitoring was validated with machine models using a …

Research News, Publications, 2025, Volume 4, Soumyajit Majumdar

Publications (2015-)

Publications that appeared during the period of October 1 - December 31, 2025.

Research News, Publications, 2025, Volume 3, Soumyajit Majumdar

Publications (2015-)

Publications that appeared during the period of July 1 - September 30, 2025.

Research News, Publications, 2025, Volume 2, Soumyajit Majumdar

Publications (2015-)

Publications that appeared during the period of April 1 - June 30, 2025.

Disparities In Breast Cancer Detection Modalities And Outcomes Among Geriatric Female Cancer Patients, Zhaoli Liu, Mathilda Nicot-Cartsonis, Biai D E Digbeu, Daoqi Gao, Sharon H Giordano, Yong-Fang Kuo

Faculty, Staff and Student Publications

This study examined racial and geographic disparities in breast cancer detection modalities (screening-, diagnostic-, or non-mammography) with cancer stage and mortality. A retrospective cohort study was conducted using Texas Cancer Registry-Medicare linkage data for geriatric women. Cancers detected through screening and diagnostic mammography had 43 % (95 % CI, 39 %-46 %, p < .0001) and 31 % (95 % CI, 27 %-35 %, p < .0001) lower all-cause mortality, and 49 % (95 % CI, 41 %-54 %, p < .0001) and 37 % (95 % CI, 32 %-43 %, p < .0001) lower cancer-specific mortality, respectively, compared to non-mammography-detected breast cancers. Patients from rural areas were 17 % (95 % CI, 1.06 - 1.29) more likely to be diagnosed with mid- (p = .0023) and advanced stage (p = .003) cancers compared to their urban counterparts. Racial or geographic disparities in cancer detection modalities with associated mortality no longer exist after adjusting for covariates. Healthcare professionals can leverage these findings to promote rural cancer health equity.

Improved Survival And Decreased Cancer Deaths In Young Adults With Cancer After Passage Of The Affordable Care Act Dependent Coverage Expansion, Michael Roth, Clark R Andersen, Amy Berkman, Stuart Siegel, Branko Cuglievan, J Andrew Livingston, Michelle Hildebrandt, Jaime Estrada, Archie Bleyer

Faculty, Staff and Student Publications

Background: The Patient Protection and Affordable Care Act (ACA) allowed Americans aged 19-25 years to remain on their parents' health insurance plans until age 26 years (the Dependent Care Expansion [DCE]). Have those with cancer diagnoses benefited?

Methods: The ACE DCE 7-year age range of 19-25 years was compared for changes in cancer survival and mortality before and after enactment of the ACA with groups that were younger and older (in 7-year age spans: ages 12-18 and 26-32 years, respectively). Cancer death data for the entire United States were obtained from the Centers for Disease Control and Prevention, and relative …

Recovery Of Verbal Working Memory Depends On Left Hemisphere White Matter Tracts, Randi C Martin, Junhua Ding, Ali I Alwani, Steve H Fung, Tatiana T Schnur

Faculty, Staff and Student Publications

Researchers propose that the recovery of language function following stroke depends on the recruitment of perilesional regions in the left hemisphere and/or homologous regions in the right hemisphere. Many investigations of recovery focus on changes in gray matter regions, whereas relatively few examine white matter tracts and none address the role of these tracts in the recovery of verbal working memory. The present study addressed these gaps, examining the role of left versus right hemisphere tracts in the longitudinal recovery of phonological and semantic working memory. For 24 individuals with left hemisphere stroke, we assessed working memory performance within 1 …