Physical Sciences and Mathematics Commons^™

Development Of Low Threshold Germanium Detectors For The Search Of Low Mass Dark Matter, Pramod Acharya

Dissertations and Theses

This dissertation explores using high-purity germanium (Ge) crystals for low-mass dark matter (DM) detection, focusing on enhancing crystal quality and identifying key crystal growth parameters. The study assesses the electrical properties of refined Ge materials through Hall Effect measurements and uses machine learning to predict impurity profiles, achieving levels conducive to high-resolution DM detectors. Utilizing a planar Ge detector fabricated at Texas A$\&$M and operated at cryogenic temperatures at the University of Minnesota, the study reveals time-dependent internal charge amplification through impact ionization. Research on charge transport dynamics in a cryogenic p-type Ge detector uncovers evolving charge dynamics and cluster …

Development Of A Modular Lab Automation System With Applications To Animal And Bacteria Cell Culture, Timothy William Hartman

Dissertations and Theses

The challenges faced while executing wet lab protocols encourage the development of automation systems to come alongside human scientists. Today’s cutting-edge experiments involve complex protocols with precise measurements usually performed manually. Even simpler biological protocols can be tedious and prone to error, as was seen during the COVID-19 pandemic and society’s demand for high-volume, rapid sample analysis. Moreover, reproducibility suffers when there is excessive variability and insufficient data. Here, we leveraged the Stanford Biodesign process to develop a modular lab automation system and image analysis workflow to address challenges like these. This flagship automation platform at The University of South …

Artificial Intelligence And News Consumption: A Study Of Trust, Credibility And Transparency In Automated Journalism, Julia Lobo Paes

Dissertations and Theses

According to Gallup poll (2023), over the last 50 years there has been a decline in how much Americans trust mass media. While in the 1970’s 72% of the population responded that they trust the media a 'great deal/fair amount', this number dropped to 34% in 2023. Given the decreasing public trust in news, this thesis focused particularly on analyzing trust in the organization, trust in the news story and perceived credibility in AI generative content. In addition to articles created by AI, this study also aimed to analyze how the public perceives information that has been personalized and distributed …

Geodatabase And Automation Code Used For Past And Real-Time Dynamic Landslide Hazard Maps In Eastern Kentucky, Nathaniel O'Leary, L. Sebastian Bryson, Jason M. Dortch

Earth and Environmental Sciences Research Data

We developed spatiotemporal landslide hazard maps (LHMs) using soil, hydrologic, and geomorphic parameters from the subaerial infinite slope factor of safety (FS) equation under unsaturated conditions. Soil properties were sourced from the NRCS WSS, while geomorphic variables were derived from a 1.5 m LiDAR-based DEM and ArcGIS Online. Soil moisture from Hydrus-1D, driven by precipitation and evapotranspiration (ET) data from Irrigation Manager, introduced temporal variability. Validation against known landslide sites demonstrated FS accuracy both spatially and temporally, despite some false positives. To reduce false positives and enhance slope stability representation, novel depth-to-bedrock (DTB) and soil root cohesion maps were incorporated …

Crowdsourced Geospatial Data Is Reshaping Urban Sciences, Xiao Huang, Siqin Wang, Tianjun Lu, Yisi Liu, Leticia Serrano-Estrada

Earth and Environmental Sciences Faculty Publications

For many years, urban sciences relied heavily on traditional, authoritative data sources. However, a paradigm shift has occurred recently with the advent of citizen-driven data contribution. This evolution in data acquisition for urban science is attributable to advancements in positioning and navigation technologies, widespread use of digital devices, the rise of Web 2.0, enhanced broadband communications, and refined data management techniques. The significance of crowdsourced geospatial data in the realm of urban sciences is now widely acknowledged. A diverse array of novel data sources has been increasingly gaining prominence. These include, but are not limited to, social media platforms, street …

Crowdsourcing Geospatial Data For Earth And Human Observations: A Review, Xiao Huang, Siqin Wang, Di Yang, Tao Hu, Meixu Chen, Mengxi Zhang, Guiming Zhang, Filip Biljecki, Tianjun Lu, Lei Zou, Connor Y. H. Wu, Yoo Min Park, Xiao Li, Yunzhe Liu, Hongchao Fan, Jessica Mitchell, Zhenlong Li, Alexander Hohl

Earth and Environmental Sciences Faculty Publications

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and …

Impacts Of Anthropogenic Sedimentation On Shell-Bed Habitats In Lake Tanganyika, Africa, Michael Soreghan, Andrew Cohen, Michael M. Mcglue, Kevin M. Yeager, Emily Ryan, Alison Johns, Ishmael Kimirei

Earth and Environmental Sciences Faculty Publications

Lake Tanganyika, in central Africa, contains a diverse and endemic fauna under threat from global climate change, overfishing, and nearshore sediment pollution. Previous studies of sediment pollution focused justifiably on impacts along rocky shorelines where diversity is high, but Lake Tanganyika also contains widespread shelly accumulations (shell beds) unprecedented in the modern East African lakes, but where impacts are less con- strained. Here we integrate multiple datasets from three sites along the Tanzanian shoreline to explore how variation in sedimentation rates and sediment quality impacts shell-bed substrate and diversity and abundance of ostracodes and sponges across sites that exhibit varying …

Governance Policy Evaluation In The United States During The Pandemic: Nonpharmaceutical Interventions Or Else?, Danlin Yu, Shenyang Guo, Yuanyuan Yang, Linyun Fu, Timothy Mcbride, Ruopeng An

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Scientific evidence suggests that nonpharmaceutical interventions (NPIs) effectively curb the spread of COVID-19 before a pharmaceutical solution. Implementing these interventions also significantly affects regular socioeconomic activities and practices of social, racial, and political justice. Local governments often face conflicting goals during policymaking. Striking a balance among competing goals during a global pandemic is a fine science of governance. How well state governments consume the scientific evidence and maintain such a balance remains less understood. This study employs a set of Bayesian hierarchical models to evaluate how state governments in the United States use scientific evidence to balance the fighting against …

Research On Multiscale Openstreetmap In China: Data Quality Assessment With Ewm-Topsis And Gdp Modeling, Chuqiao Han, Binbin Lu, Jianghua Zheng, Danlin Yu, Shudan Zheng

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

OpenStreetMap (OSM) is a voluntary platform designed to provide free and up-to-date geographic data. Since OSM is based on multisource geographic data provided by the public, the quality of the data has become a concern of researchers. In this study, a unified measure for evaluating OSM data quality was constructed, and the entropy weight method (EWM) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) model were used to evaluate the quality of multiscale OSM data in China from 2014 to 2020. In addition to evaluating the data quality, the use of OSM data quality index factors in …

Early Oligocene Record Of An “Iceberg Alley” In The Weddell Sea From Quartz Sand Microtextural Analysis At Odp Site 696, Victoria Hojnacki, Sandra Passchier

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

The greenhouse to icehouse transition at the Eocene-Oligocene boundary (34 Ma) marked the appearance of continental-scale glaciation in Antarctica. The material recovered from Ocean Drilling Program Site 696 is the only record spanning this major climatic shift in the Weddell Sea region. Using scanning electron microscopy, quartz microtextures in 13 samples across the Eocene-Oligocene transition were analyzed to understand the degree of glacial modification and the transportation history of the >150 µm material. The quartz grains were visually grouped, characterized, and interpreted by grain outline, relief, and surface microtextures. Glacial textures are present throughout the entire interval (34.4–33.2 Ma), with …

Exploring The Potential Of Openstreetmap Data In Regional Economic Development Evaluation Modeling, Zhe Wang, Jianghua Zheng, Chuqiao Han, Binbin Lu, Danlin Yu, Juan Yang, Linzhi Han

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

In regional development studies, GDP serves as an important indicator for evaluating the developing levels of a region. However, due to statistical methods and possible human-induced interfering factors, GDP is also a commonly criticized indicator for less accurately assessing regional economic development in a dynamic environment, especially during a globalized era. Moreover, common data collection approaches are often challenging to obtain in real-time, and the assessments are prone to inaccuracies. This is especially true in economically underdeveloped regions where data are often less frequently or accurately collected. In recent years, Nighttime Light (NTL) data have emerged as a crucial supplementary …

An Evaluation Of Features Extracted From Facial Images In The Context Of Binary Age Classification, Malik Awais Khan, Aurelia Power, Peter Corcoran, Christina Thorpe

Conference Papers

Age verification via facial images is used to enhance security, ensure online child safety, and manage access control with many approaches using classification models. However, many existing classification approaches face generalisation challenges due to homogenous racial nature of datasets. Moreover, many approaches fail to explicitly address the predictive potential of extracted facial features. To address the lack of racial diversity we selected representative samples from four different benchmark datasets: UTK-Face, Fg-Net, Morph and All-Age-Faces. Subsequently, we examined the predictive potential of local, global and hybrid sets of facial features. We extracted local features using two types of Local Binary Pattern …

Impossibility Of Artificial Inventors, Matt Blaszczyk

Fellow, Adjunct, Lecturer, and Research Scholar Works

Recently, the United Kingdom Supreme Court decided that only natural persons can be considered inventors. A year before, the United States Court of Appeals for the Federal Circuit issued a similar decision. In fact, so have many the courts all over the world. This Article analyses these decisions, argues that the courts got it right, and finds that artificial inventorship is at odds with patent law doctrine, theory, and philosophy. The Article challenges the intellectual property (IP) post-humanists, exposing the analytical and normative perils of their argumentation, and recommends against getting rid of the nominally central place of humans in …

Geological And Environmental Sciences - 2024, Dept. Of Geological And Environmental Sciences

Geological and Environmental Sciences News

• Greetings from the Department Chair
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• Publications 2023–24

Sscm: A Secured Approach To Supply Chain Management Using Blowfish Optimization, Shitharth Selvarajan, Hariprasath Manoharan, Alaa O. Khadidos, Achyut Shankar, Adil O. Khadidos, Wattana Viriyasitavat, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

This study examines the importance of enterprise information systems that link several corporate organisations to share information about diverse products under high security settings. The primary goal of the proposed strategy is to create a direct link between product demand and production to minimise the impact of rising costs. The research motive to make a connection cannot be resolved without suitable data that shows both quantity and quality in each organisation unit. The suggested method is designed to deliver accurate data to authorised end users while preventing any data exposure to unauthorised users. Security cryptographic keys are utilised to create …

Next-Generation High-Performance Virtual Reality And Augmented Reality Light Engines, Zhiyong Yang

Graduate Thesis and Dissertation 2023-2024

The immersive virtual reality (VR) and the optical see-through augmented reality (AR) are expected to revolutionize human lives in work, education, entertainment, healthcare, spatial computing, and digital twins, just to name a few. Next-generation VR/AR devices should exhibit a wide field-of-view (FoV), crisp image without screen-door effect, high dynamic range, compact form factor and lightweight, and low power consumption. Such demanding requirements pose a significant challenge to traditional direct-view display panels. To address these technical challenges, novel approaches need to be proposed. This dissertation is devoted to developing next-generation high-performance display light engines toward high resolution density, high optical efficiency, …

Fr1: Comics, Cyborgs, And “In Between” Identities, Ella Lehavi

Scripps Senior Theses

As a queer Jew who grew up surrounded by immigrant cultures and communities, I find myself in a liminal space between my identities and the dominant culture of my country– one where my perspective on gender and my cultural experiences aren’t fully understood by the world I exist in. Comics and cartoons are an explorational platform for concepts of reality and identity; they are one of very few spaces where I see my identities explored with so much depth and care.

Cartoons and comics exist in between realistic depictions and abstraction. This makes them a great place to express all …

Transition Towards A Brighter Future: Energy Usage Analysis At Pilgrim Place And Recommendations For Decarbonization, Zhuoyao Wu

Scripps Senior Theses

This thesis summarizes the semester-long project I and other Environmental Analysis major students collaborated on for the EA 190 Capstone Project aims to find effective methods to reduce emissions and increase energy efficiency. Our group partnered with the Climate Resilience Initiative team (CRI) at Pilgrim Place, a social and environmental justice-focused retirement community in Claremont, CA. As the demand for effective methods for energy efficiency in communal spaces increases, we have conducted an energy analysis and researched potential functional technologies to replace high fossil fuel consumption sources. Our final deliverable is a written report that analyzes the data we collected …

Probing The Ising Model’S Thermodynamics Through Restricted Boltzmann Machines, Xiaobei (Emma) Zhang

HMC Senior Theses

This thesis explores the connection between physics and machine learning by using Restricted Boltzmann Machines (RBMs) to study the thermodynamic properties of the Ising model. The Ising model is a simple but realistic model that captures the magnetic behavior of a system, where spins occupy a lattice of sites and different spin configurations correspond to different energies. The model exhibits phase transitions between ferromagnetic and paramagnetic phases as a function of temperature. RBMs are two-layered neural networks that can learn probability distributions over binary spins. The study generates 2D Ising model data at different temperatures using Monte Carlo simulations, including …

Exploring Sigmoidal Bounded Confidence Models With Mean Field Methods, Tian Dong

HMC Senior Theses

Mathematicians use models of opinion dynamics to describe how opinions in a group of people change over time, which can yield insight into mechanisms behind phenomena like polarization and consensus. In these models, mathematicians represent the community as a graph, where nodes represent agents and edges represent possible interactions. Opinion updates are modeled with a system of differential equations (ODEs). Our work focuses on the sigmoidal bounded confidence model (SBCM), where agents update their opinion toward a weighted average of their neighbors' opinions by weighting similar opinions more heavily. Using tools developed in physics (mean-field theory), we derive a continuity …

Adaptive Multi-Label Classification On Drifting Data Streams, Martha Roseberry

Theses and Dissertations

Drifting data streams and multi-label data are both challenging problems. When multi-label data arrives as a stream, the challenges of both problems must be addressed along with additional challenges unique to the combined problem. Algorithms must be fast and flexible, able to match both the speed and evolving nature of the stream. We propose four methods for learning from multi-label drifting data streams. First, a multi-label k Nearest Neighbors with Self Adjusting Memory (ML-SAM-kNN) exploits short- and long-term memories to predict the current and evolving states of the data stream. Second, a punitive k nearest neighbors algorithm with a self-adjusting …

Revolutionizing Campus Communication: Nlp-Powered University Chatbots, Ritu Ramakrishnan, Priyanka Thangamuthu, Austin Nguyen, Jinzhu Gao

Pacific Faculty Work

Artificial intelligence (AI) based chatbots leverage programmed software instructions to simulate human speech and user interaction. These versatile tools can be employed in various domains, from managing smart home devices to providing personal virtual assistants. They can also be useful in responding to common queries and can make information easier to access. In response to this need, we developed a specialized chatbot tailored for the academic environment by training an NLP model to answer frequently asked questions (FAQs) the need of searching through the university website. The main goal is to optimize user engagement and streamline information retrieval within a …

Behaviour And Attitudes Of Non-Resident Waterfowl Hunters In Saskatchewan, Matthew P. Gruntorad, Mark P. Vrtiska, Christopher J. Chizinski

School of Natural Resources: Faculty Publications

No abstract provided.

The North American Trumpeter Swan Survey: Retain Or Find Something New?, Mark P. Vrtiska, J. A. Dubovsky, M. G. Anderson

School of Natural Resources: Faculty Publications

No abstract provided.

Exploring Heterogeneity In Waterfowl Hunter Trip Preferences: A Discrete Choice Experiment, K. A. Sainsbury, H. W. Harshaw, D. C. Fulton, N. W. Cole, A. A. Dayer, J. N. Duberstein, A. H. Raedeke, R. M. Schuster, Mark P. Vrtiska

School of Natural Resources: Faculty Publications

No abstract provided.

Exploring Recruitment, Retention, And License Purchase Probability Of Waterfowl Hunters Using A Mark-Recapture Approach, K. A. Graham, Mark P. Vrtiska, D. H. Humburg, Larkin A. Powell, A. H. Raedeke, P. K. Devers, Christopher J. Chizinski

School of Natural Resources: Faculty Publications

No abstract provided.

Calcium Carbonate-Based Stimuli-Responsive Microcarriers For Targeted Drug Delivery Against Oral Bacterial Infections And Development Of Glass-Free Microfluidics As An Analytical Platform, Krishantha Wijewardhane

Dissertations and Theses

Dental diseases present a significant global health challenge, affecting individuals across all age groups. This spectrum of oral health issues encompasses conditions like dental caries, periodontitis (gum disease), and oral infections. In the customer discovery interviews, dental patients have raised concerns about potential drug overexposure during and after procedures, driven by fears of adverse effects, allergies, and the increasing use of antibiotics and anesthesia. Dentists are increasingly focused on minimizing opioid and steroid-based medication doses due to potential side effects and addiction risks. This study explores an innovative approach to targeted drug delivery in the dental environment using eco-friendly and …

Antibiotic Resistance In A Coastal River In Mississippi, Usa – Potential Drivers, Shuo Shen, Wei Wu, Eric A. Saillant, Darrell Jay Grimes

Gulf and Caribbean Research

Wastewater treatment plants (WWTPs) are major sources of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in water bodies. Most studies on the impact of WWTPs on antibiotic resistance have focused on freshwater systems, with little information on coastal and estuarine waters with variable salinity. This study monitored seasonal levels of ARGs at the effluent and downstream of the Pascagoula— Moss Point WWTP in the lower Pascagoula River, a coastal river in southeastern Mississippi, USA. Surface water samples were collected seasonally at upstream, outflow, and 3 downstream sites from February to November 2016. Bacterial resistance to sulfamethazine, tetracycline, and …

Bridgewater Magazine, Volume 34, Number 1, Spring 2024, Bridgewater State University

Bridgewater Magazine

Lighting the Way: the nation's last lighthouse keeper and first woman in that role, Sally Snowman, '76. Also in this issue: The multiple sides of climate change; A program that helps students with an autism spectrum disorder or related social profile gain real-world experience; an article on Peter Weyand, G'88; Two decades of The Bridge; and eclipsing expectations: on-campus viewing event draws hundreds to BSU, observatory.

Modeling Health Insurance Premium Using Bayesian Hierarchical Models, Bennedict Kongyir, Emil Agbemade

Data Science and Data Mining

Insurance pricing requires pragmatism and creativity due to the unpredictable nature of risk [3]. This paper explores Bayesian hierarchical models to model health insurance premiums using individual and group predictors like demographics, health status, and geography. Data from Kaggle on health insurance policyholders was utilized, with prior distributions enhanc­ing model interpretability and credibility. Bayesian models improve predictive accuracy and provide valuable insights for actuaries and policymakers, highlighting the signifcant impact of factors such as age and BMI on premium pricing.