Digital Commons Network^™

Deforestation Dynamics In The Amazon: Impacts, Socio-Environmental Drivers And Restoration Pathways, Maria Natalia Rodriguez

Master's Projects and Capstones

The Amazon, which is the largest tropical rainforest in the world, experienced 542,581 km² of forest loss between the years 2000 and 2020. The process of deforestation endangers the ecological system results which maintain ecosystem connectivity and the Earth's climate system. The Amazon rainforest supplies essential ecological services which include maintaining soil fertility, storing carbon, purifying water and climate stability. The fundamental ecosystem of this area faces new threats because of increasing forest destruction. The research study adopts a combined methodology that uses Geographic Information Systems (GIS) with a comprehensive literature review to study Amazon deforestation patterns and its driving …

Climate-Driven Maritime Hazards And Marine Fuel Oil Spill Risk In The Northwest Passage, Emily Grace Parker

Master's Projects and Capstones

Shipping activity across the Northwest Passage has increased by 46% since 2011 as climate forcing drives sea ice decline, but associated risks to vessels and the environment are underestimated and rarely examined together. A literature review conducted in this study indicated that by 2070, a 5-month navigation window will expose vessels to increasingly unpredictable hazards as the region transforms from an ice- to wave-dominated regime, with wave heights increasing by 10-13% per decade. Ice hazards persist, and vessels operating in early summer and late fall will be exposed to elevated ice accretion risk that can cause capsizing and marine fuel …

Uncovering Discrete States From Multimodal Psychophysiological Data Using Gaussian Latent Dirichlet Allocation (Glda), Congyu Wu, Aaron Fisher, David Schnyer

Northeast Journal of Complex Systems (NEJCS)

In this article we explore and validate the utility of an unsupervised probabilistic model, Gaussian Latent Dirichlet Allocation (GLDA), for discovering discrete states from repeated, multimodal psychophysiological samples collected from multiple individuals. Psychology and medical research heavily involves measuring potentially related but individually inconclusive variables from a cohort of participants to derive diagnosis, necessitating clustering analysis for state identification. Traditional probabilistic clustering models such as Gaussian Mixture Model (GMM) assume a global mixture of component distributions, which may not be realistic for observations from different patients. The GLDA model borrows the individual-specific mixture structure from a popular topic model Latent …

Finding A Way Out Of The Filter Bubble: The Confusion Of A Heavy Social Media User, Longwen Miao

Masters Theses

This thesis studies how algorithmic recommendation systems reshape visual perception, aesthetic judgment, and the construction of selfhood within contemporary digital culture.

Everything begins with the experience of repeatedly encountering algorithmically recommended content on everyday digital platforms. On these platforms, images, sounds, and social interactions are continuously selected, repeated, and reorganized by predictive systems, forming an environment in which perception is constantly structured and adjusted.

From this observation, the research raises two central questions: how do algorithmic recommendation systems reshape visual perception, aesthetic judgment, and self-recognition, and how might these systems be intervened in or made perceptible through artistic practice? Within …

Frictional Intelligence, Posheng Cheng

Masters Theses

This is an experimental interaction design project that challenges anthropomorphism in human-computer interaction. In particular, the recent advancement of artificial intelligence technologies like Large Language Models has taken anthropomorphism to new heights. The conversational chatbot interface of AI prioritizes mimicking an inherently human communication medium to maximize human-likeness. However, anthropomorphism has several downsides. Conversational interfaces obscure the limitations and the tangible cost of the technology. They also imply fictional moral status and human-level cognitive capabilities, which means general public sentiment focuses on the ``overhyped'' excitement and fear rather than on other socio-ethical and capacity questions that are far more urgent …

Somatic Prosthetics For Planetary Resonance, Disha Dharesh Kumar R

Masters Theses

This thesis investigates how industrial design can transcend extractive technological paradigms in favor of relational interfaces that foster planetary attunement. Framing the climate crisis as a 'crisis of imagination', the research challenges the Western bifurcation of nature and culture by drawing on Indic cosmologies- which recognize stones, plants, and ecosystems as conscious at different levels and participants in a shared cosmic field. By synthesizing research in Biosemiotics, Quantum Information Pansycishm, and Neuroscience, the project redefines intelligence as a distributed, more-than-human phenomenon.

The research materializes as a speculative design artifact: a device that functions as a somatic prosthetic for planetary resonance. …

Environmental Mercury Alters Immune Pathways Linked To Autoimmune Risk In Mice Mirroring Humans, Maurgan Lee, Paul Stemmer, Randall Gill, Allen Rosenspire, Anil Aranha, Heather Gibson

Medical Student Research Symposium

Background and Purpose: Mercury is a pervasive environmental contaminant, and human epidemiologic studies have linked chronic low-level exposure to increased autoimmune disease-risk. Dysregulated lymphocyte activation and impaired signaling tolerance are central mechanisms in human autoimmunity. Protein phosphorylation governs lymphocyte differentiation and function, alterations in phosphoproteomic networks may represent a signature of immune disruption. This study evaluates how low dose mercury exposure modifies B and T cell abundance and intracellular signaling patterns in BALB/c and Diversity Outbred (DO) mice.

Methods: BALB/c and DO mice were exposed to low dose HgCl2 in their water for two weeks or provided standard water controls. …

Dialogue Between Mind And Algorithm: Deep Symbiosis Of Psychology And Artificial Intelligence, Xiaolan Fu, Zheng Yan

Bulletin of Chinese Academy of Sciences (Chinese Version)

As artificial intelligence (AI) evolves from a supportive tool into a collaborative partner, the convergence of psychology and AI is gradually shifting from one-way application toward deep symbiosis. This study discusses the mutual empowerment resulting from their interaction, as well as the challenges they face and potential pathways to breakthroughs. On the one hand, psychology empowers AI by enhancing its human-like intelligence and social adaptability through cognitive modeling and ethical constraints; on the other hand, AI empowers psychology by leveraging multimodal data and algorithmic models to revolutionize psychological assessment and intervention methods. This deep symbiosis requires a clear-eyed acknowledgment of …

Enhanced No₂ Gas Sensing Using Silver-Doped Cadmium Telluride Nanocrystalline Thin Films, Tunis Balasim Hassan

Karbala International Journal of Modern Science

Nitrogen dioxide (NO₂) is a toxic pollutant that necessitates sensitive and reliable monitoring systems. Conventional gas sensors often lack adequate responsiveness and fast recovery under changing conditions and therefore create a need for semiconductors with enhanced performance, especially at high industrial temperatures (around 250 °C). The study therefore aims to synthesis and evaluate silver-doped cadmium telluride (Ag:CdTe) thin films as NO₂ gas sensors. Pure CdTe and Ag:CdTe with silver concentrations of 5, 10, and 15 wt% were prepared by a co-precipitation process. XRD verified cubic symmetry with a progressive fall in crystallite size (6.67 nm to 5.46 nm at 15 …

A Formal Ontology Of Combat Feel, Grayson Julian Von Goetz Und Schwanenfliess

LMU Theses and Dissertations

Combat feel, the moment-to-moment subjective character of real-time melee combat in ac- tion games, is a central concern of game design and a recurring subject in design literature, but practitioners currently navigate it through intuition and reference to admired prior work, with no shared formal vocabulary for the design trade-o!s being made. This thesis presents a decision-theoretic framework that formalizes combat feel as a Bayesian network in which designer decisions act as interventions on measurable system variables, those variables drive latent perceptual states whose conditional distributions are grounded in the psychophysics literature on input-lag detection, duration discrimination, and audiovisual temporal …

Geometric Structure In High-Dimensional Representations: Theory And Applications To Language, Jiayi Chen

Dartmouth College Ph.D Dissertations

This thesis develops a geometric perspective on high-dimensional representations, motivated by applications to language. Rather than treating representations solely as inputs to predictive models, we view them as structured objects whose geometry encodes meaningful information. In particular, we argue that such representations exhibit organization at multiple scales: at a global level, metric and clustering structure capture relationships such as genre, authorship, and discourse; at a local level, geometric quantities such as intrinsic dimension and curvature describe how these relationships vary across the space.

To study these phenomena, we combine empirical analysis with theoretical development. On the empirical side, we examine …

Shaping Emergent Competitive And Cooperative Behaviors In Multi-Agent General-Sum Games, Ethan F. Erickson

Honors Projects

Reinforcement learning (RL) algorithms can train agents to solve problems in environments using complex behaviors that are not explicitly programmed, known as emergent behaviors. The goal of our research is to investigate how different RL reward values influence the emergence of competitive and cooperative behaviors in games with teams of multiple agents. Specifically, we focus on general-sum games, in which the sum of gains and losses of each team may be non-zero, allowing situations for agents to mutually benefit or mutually fail. Using Unity’s ML-Agents Toolkit to train agents with RL self-play in bounded 2D environments, we identify high-level behaviors …

Accurate Diagnosis Of Diseases By A Novel Ai Pipeline Based On Feature Extraction, Feature Ranking, And Feature Selection From Medical Images, Tuğba Nur Bozkurt, Mehmet Emi̇n Yüksel

Turkish Journal of Electrical Engineering and Computer Sciences

The rapid growth of the global population has led to a substantial increase in the number of patients, while the availability of healthcare professionals has not expanded at a comparable rate. This imbalance highlights the urgent need for efficient and reliable computer-aided decision support systems that can reduce clinical workload while maintaining high diagnostic accuracy. In this study, a novel and systematically integrated artificial intelligence-based pipeline is proposed for medical image classification, combining statistical significance-driven feature ranking with evolutionary feature selection in a unified framework. The proposed pipeline consists of four sequential stages: feature extraction, ranking, selection, and classification. Features …

The Extraction And Chemical Characterization Of The Avian Pigments Turacin And Turacoverdin, Sarah R. Bekkali

Honors Scholar Theses

Bird coloration is a trait that extends beyond mere aesthetics as it has an extensive range of biological significance. Plumage patterns and hues can influence camouflage, mate choice, social dominance, and physiological performance. Bird fitness, their ability to survive and reproduce, is greatly dependent on color. Melanins, carotenoids, and pterins are well-studied pigment systems that are commonly found across many avian species’. Alternatively, porphyrin-based pigments are rare and less-studied as they only found in turacos a sub-Saharan African bird belonging to the family Musophagidae. This thesis focuses on two pigments of interest: turacin, the deep crimson-red pigment found in …

Saving The Great Basin: Creating Places For The Birds, Bees And Beyond, Carlos Gomez

Hospitality Design Graduate Student Capstones

This project looks at how vacant and underused parcels along the Truckee River in Reno, Nevada, can be rethought as part of a larger ecological system. Rather than treating these parcels as empty leftover spaces, the project sees them as opportunities to create small habitat patches that can support native species, improve stormwater function, and strengthen the river corridor over time. The work focuses on three sites along the Truckee River: California Avenue, Island Avenue, and Commercial Row. Each site responds to a different condition along the urban transect, from a sloped residential river edge to a tighter urban parcel …

The Biowell System: An Integrative Framework That Connects Ecological Sustainability And Mental Wellbeing Through The Regenerative Processes Of Bioswales, Nathan A. Bussa

Hospitality Design Graduate Student Capstones

The Biowell System is an evaluative framework that connects ecological sustainability and mental well-being through the regenerative processes of bioswales.

Unknowing Sacrifices: Public Health And Radiation Illness In New Mexico And Nevada, 1940s-1960s, Beatriz Avila-Marquez

UNLV Theses, Dissertations, Professional Papers, and Capstones

The detonation of the first atomic bomb in the early morning of July 16, 1945, in New Mexico welcomed the atomic age that forever changed the world. After that day, thousands of lives were lost due to nuclear weapons, and hundreds of thousands more continued to suffer from the effects of atomic testing. The Atomic Energy Commission, fueled by the arms race of the Cold War, chose Nevada to continue the United States’ nuclear weapons testing. Knowledge of the dangers of radiation exposure, the effects of radiation, and techniques to prevent exposure are now available in part due to the …

“A Land No One Would Want”: Environmental Activism And The Rejection Of ‘Wasteland’ Narratives In Southern Nevada, Steven Butler

UNLV Theses, Dissertations, Professional Papers, and Capstones

This paper traces events within the history of environmental activism in Southern Nevada. The first chapter discusses the proposed high level nuclear waste repository at Yucca Mountain. The second chapter examines the closure of the Reid Gardner Generating Station in Moapa, Nevada. The third chapter details the Southern Nevada Water Authority’s Groundwater Development Project. Each of the three chapters is linked by common themes within the history of Southern Nevada environmental activism, including dedicated coalition-building and the refusal of “wastelanding” of the region.

Methylation-Dependent Regulatory Pathway That Governs The Stability Of The Sox Family Proteins And Related Developmental Regulators, Keshari Gayathri Rajawasam

UNLV Theses, Dissertations, Professional Papers, and Capstones

The SRY (Sex-determining Region Y) protein is a transcription factor encoded on the Y chromosome and is the key regulator responsible for initiating male sex determination in mammals. During early embryonic development, SRY activates the genetic program that leads to testis formation by promoting the expression of downstream genes involved in male gonadal differentiation. Mutations or dysregulation of SRY can lead to disorders of sex development such as male-to-female sex conversion and hermaphroditism, highlighting its critical role in sex determination.

SRY belongs to the SOX (SRY-related HMG-box) family of transcription factors, which includes the proteins SOX1, SOX2 and SOX3. These …

Visual Interpretability Of Multimodal Tissue Perfusion Classification Using Grad-Cam And Saliency Maps, Metehan Zorluoglu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Accurate identification of the tissue perfusion phase from hand images can aid doctors in decision-making with non-invasive techniques. The present study proposes a multimodal deep learning model for classifying the tissue perfusion phase using infrared, thermal, and visible spectrum images of the human hand. The proposed model consists of various preprocessing techniques such as manipulation, homography alignments, and masking. The significant contribution of this thesis is the interpretability analysis of deep learning models, achieved through the analysis of saliency maps and the Gradient-weighted Class Activation Mapping (Grad-CAM) methods. The purpose of this method is to find out how the convolutional …

A Descriptive Analysis Of Plant Leaf Disease Detection Using Machine Learning And Deep Learning Models: A Systematic Review, Arzoo Chamoli, Anuj Kumar

Turkish Journal of Electrical Engineering and Computer Sciences

Plant leaf disease detection (PLDD) is a growing active research area with burgeoning practical applications across various sectors such as agricultural monitoring, food security, and environmental conservation. Accurate segmentation and classification of plant leaf diseases remains a key challenge in the field of plant leaf disease prediction. The challenge demands automated methods for the plant disease identification because it needs to develop better crop management systems, which will boost agricultural production. In this article, we provide a systematic review of various machine learning (ML) and deep learning (DL) methods extensively used for PLDD. The review strategy follows a formal protocol, …

Thermal Physiological Ecology Of The Relict Leopard Frog At Hot And Cold Springs, Robert P. Pelletier Iii

UNLV Theses, Dissertations, Professional Papers, and Capstones

The relict leopard frog (Rana onca) once ranged across drainages in southern Nevada, northwestern Arizona, and southwestern Utah. Following a decline, the species only persisted in a few geothermally influenced hot springs, which led to the perspective that hot springs were high-quality habitat. Rana onca has been under intensive, multiagency management and the species has been translocated to establish additional populations, including at cold-water sites. Three research studies are presented into the thermal physiological ecology of R. onca with the aim of informing conservation strategy. The research was focused at a thermally influenced hot spring and a cold-water spring to …

Semi-Rational Strategies For Antifungal Peptide Design, Akilah I. Mateen

Seton Hall University Dissertations and Theses (ETDs)

A recently emerged opportunistic fungi, Candida auris, has been subject to increased scrutiny due to its virulence and rapid geographical spread. Due to the indiscriminate use of antimicrobials as treatments for infectious diseases and as pesticides, the ubiquitous threat of multidrug resistance (MDR) looms large. The lack of progress in antifungal development is of high concern in the treatment of infectious diseases and a rise in fungal resistance highlight the need for updated treatment strategies. This work describes three strategies used to address these concerns:

•  The synthesis of a photosensitizer-membrane-active peptide (PS-MAP) conjugate, Ir-HKII15, that combines the ability of …

Digital Literacy And Language Proficiency As Factors Of Accessible Digital Training In The Hospitality Industry: Employee Perspectives Of Training And Working In A Diverse Industry, Gillian Bowden

UNLV Theses, Dissertations, Professional Papers, and Capstones

This explanatory sequential mixed methods study explored how digital literacy and language proficiency impact employees’ access to and engagement with digital training, as well as how these experiences influence their perceptions of training and the organization. In the quantitative phase, survey data were collected from hourly employees at a large foodservice corporation (n=67). Four constructs were assessed: digital literacy, language proficiency, accessibility, and engagement. Results indicated strong, statistically significant relationships with higher levels of digital literacy and language proficiency associated with greater accessibility and increased engagement with digital training materials. The large effect sizes suggest these competencies play a meaningful …

Integrating Augmented Reality Visualizations Into Data Science Notebooks Using Microsoft Hololens 2, Derek Willis

Theses and Dissertations

Data-science notebooks support iterative analysis but are limited to two-dimensional (2D) displays. This work presents an approach to extend such environments with rapid augmented reality (AR) visualization while preserving conventional 2D workflows. An opensource R package was developed to convert notebook objects into three-dimensional (3D) models, export them in the Graphics Language Transmission Format (glTF), and transfer directly to a Microsoft HoloLens 2 via a USB connection for viewing in the native 3D Viewer application. The proposed workflow eliminates manual conversion and transfer steps required by earlier methods. A user study employing a post-session questionnaire indicated that participants found the …

Assessing The Relationship Between Subsurface Geology And Surficial Geomorphology: Remotely Predicting Geologic Features And Geohazards Using An Elevation-Trained Machine Learning Algorithm In The Northern Gulf Of Mexico, Allison L. Wing

Theses and Dissertations

This thesis evaluates the capacity to predict subsurface geologic features and submarine landslide susceptibility using surficial geomorphology derived from bathymetric elevation data in the Northern Gulf of Mexico. Quantitative geomorphic variables including slope, curvature, aspect, rugosity, geomorphons, and Bathymetric Position Index were generated from 30-meter digital elevation models and used as explanatory variables in presence-only Maximum Entropy models. Known locations of faults, pockmarks, mud volcanoes, hydrocarbon seeps, and landslides (particularly intact scarps) were used to train and validate predictive models through k-fold cross validation. Model performance was assessed using omission rates and AUC values. Results demonstrate that specific geomorphic signatures, …

Impact Of The Dose And The Number Of Transmitted/Founder Viruses On Siv Dynamics, Sunil Maity, Vitaly V. Ganusov

Biology and Medicine Through Mathematics Conference

No abstract provided.

Digging Deep Into Curation: A Guide To Creating A Local Fossil Museum, Syd Joheim, René Shroat-Lewis

Research and Creative Works Expo

In Arkansas, the dissemination of educational content related to evolution and natural history is often constrained by prevailing cultural dynamics. This has resulted in a significant gap in the exposure of primary and secondary school students to foundational concepts in natural history and physical sciences. Even the state’s most popular science and history museums often intentionally exclude exhibits that risk upsetting a large portion of their visitors, further exacerbating the issue. As a consequence, many children do not receive proper education on natural history and physical sciences.  To address this educational deficiency, researchers identified and cataloged specimens from a collection …

High-Surface-Area Ficus Leaf-Extracted Cuo-Zno-Nio Ternary Nanocomposites For Rapid Adsorption-Assisted Uv-A Degradation Of Direct Blue 15, Kafa’A H. Ali, Mohammed A. Atiya, Ahmed K. Hassan

Karbala International Journal of Modern Science

Direct Blue 15 (DB15) is a long-lasting synthetic dye that pollutes water and is difficult to remove during wastewater treatment. Conventional treatments fail to remove DB15 adequately due to rapid electron-hole recombination, which necessitates photocatalysts with reduced recombination rates for effective dye removal. The study aims to synthesize and evaluate a CuO-ZnO-NiO ternary system as an integrated adsorption and UV-A photocatalysis platform for DB15 removal. Ficus leaf-extracted CuO-ZnO-NiO nanocomposites with four Cu:Zn:Ni ratios (1:1:1, 1:1:2, 1:2:1, 2:1:1) were prepared by co-precipitation, followed by extensive chemical and physical characterization and dye-removal performance measurements. The CuO-ZnO-NiO nanocomposite exhibited hexagonal zinc oxide, cubic …

Uncovering The Impact Of Youtube's Hidden Algorithm On Its Users, Oscar Perez

COD Library Student Research and Award Symposium

YouTube is a well-known platform that offers users endless hours of news, entertainment, and education. This research seeks to understand how the algorithm functions and uncover the effects of allowing a system to curate content for viewers. The research combines academic sources with fieldwork to understand the impact of YouTube's algorithm.

Faculty Sponsor:  Professor Jacqueline McGrath