Digital Commons Network^™

Mems 4110: Air Cannon Launcher Demo, Jackson Strauss, Avery Cohen, Wilson Gao, Jack Galloway

Mechanical Engineering Design Project Class

For our senior design class (MEMS 4110) at Washington University in St. Louis, we were tasked with creating a demonstration for the St. Louis Science Center that demonstrated an engineering principle or concept. The Science Center functions as a science-oriented museum and saw more than 600,000 visitors in 2024. For our demonstration, we wanted to showcase the principles of kinematic motion. Kinematic motion is study of the motion of objects without considering applied forces. Additionally, when the acceleration of an object is either zero or held constant, the trajectory path that the object follows can be described by a few …

Paraconsistent Logic And The Metaphysics Of The Incarnation: A Defense Of Jc Beall’S Contradictory Christology, Vincent Ray M. Daut

Loyola Papers

This article explores the application of paraconsistent logic to one of theology’s enduring challenges: the metaphysics of the Incarnation. The claim that Christ is both fully human and fully divine, as defined by the Council of Chalcedon, presents a significant ontological dilemma, as these two natures are inherently incompatible and mutually exclusive according to classical logic: on the one hand, human nature is defined by finitude, mutability, and moral fallibility, and divine nature is understood as infinite, immutable, and morally impeccable, on the other. Drawing on Jc Beall’s contradictory Christology, this article argues that paraconsistent logic provides a coherent framework …

Fall 2025: Antimatter

The Weldon Times

A student-run publication from the Schulich School of Law at Dalhousie University.

Co-Editors in Chief: Kimberly Gilson, Carleigh MacKenzie

Fcrh Honors Program: Fall 2025 Program Highlights, Fcrh Honors Program

FCRH Honors Program Newsletters and Reports

No abstract provided.

Analysis Of The Prevalence Of Dissociative Identity Disorder Using Neutrosophic Plithogenic Statistics, Verónica Elizabeth Saltos Paz, Tanya Elizabeth Borja Pante, Gloria Madaly Plasencia Álvarez, Milena Rodríguez Salcedo

Neutrosophic Sets and Systems

Dissociative Identity Disorder (DID) is one of the most enigmatic, intricate issues of contemporary psychiatry. It is challenging to assess how prevalent it is and what diagnosis means because dissociative identity disorder is a complicated disorder that manifests differently across populations. Yet when the disorder can be analyzed with statistically significant results from solid populations, critical advances in disorder awareness, treatment, and quality of life for those with IDD exist. Yet the literature does not provide such a statistical approach that will process uncertainty and vagueness based upon clinical observation of persons with DID. Therefore, this research attempts to apply …

Evaluating Community Satisfaction With Cultural Educational Projects Through Neutrosophic Plithogenic Iadov, Claudia Yadira Cuenca Macas, Jack Franck Jaramillo Herrera, Isaac Roger Martinez, Rudy Garcia Cobas, Nayade Caridad Reyes Palau

Neutrosophic Sets and Systems

This study addresses the gap of assessing the Kawymeno indigenous community's satisfaction with an interdisciplinary teaching project which was designed to enhance cultural identity for these children at risk of cultural loss due to other identity-possessing persons' facilitation. Preservation of cultural identity is important because with indigenous people and non-indigenous persons, for example, globalization might facilitate the loss of the ancestral tongue and age-old activities, thus, it's important to know whether such communities approve or not of such teaching endeavors. Relative to the international findings about intercultural education, very few studies exist that assess the phenomenon from a multicultural perspective …

Predictive Model Of School Dropout In Higher Education Through Learning Analytics With Neutrosophic Plithogenic Hypotheses, David Núñez, Purificación Galindo-Villardón

Neutrosophic Sets and Systems

Higher education dropout rates are an international problem, as many people abandon their studies, especially in the early years. This problem affects institutions, causing significant losses. In this context, it is essential to consider methods that allow for predicting dropout rates and taking rapid and effective measures. Objective: The main objective is to analyze prediction models using Learning Analytics, integrating neutrosophic plithogenic hypotheses, to identify early the risk of dropout in higher education. This provides institutions with useful tools to implement actions that help retain more students, considering uncertainty and complex interactions between academic and non-academic factors. Methodology: The method …

Write Free Or Die: Vol. 12, No. 01, Unh Writing Programs

Writing Program Newsletter

No abstract provided.

Aquinas And The Over-Hasty Conclusion, Charles Perkins

Faith and Philosophy: Journal of the Society of Christian Philosophers

No abstract provided.

Stem Integration In The Classroom: An Exploratory Case-Study On Teachers Defining Their Stem Identity And Role As A Stem Educator, Tawana Guillaume

Theses and Dissertations

The push for inclusion of science, technology, engineering, and mathematics (STEM) as a meta-discipline in K-12 education is recognition that the challenges faced by society require technology skills, interdisciplinary problem-solving, and an increased number of people entering STEM professions (Dare et al., 2014; English, 2016; Fan et al., 2021; Holstein & Keene, 2013; Roehrig et al., 2012, 2021; Sanders, 2008). The dissertation in practice explored STEM teacher identity and conceptions of STEM as a function of STEM professional experience outside of the field of education. The exploratory casestudy sought to identify the relationship between STEM career-based experiences – specifically the …

Improved Extraction And Detection Of Disinfection Byproducts, Impacts Of Wildland-Urban Interface Wildfires On Drinking Water, And Change In Disinfection Byproducts Over Time In Chlorinated Vs. Chloraminated Distribution Systems, Patrick Thomas Justen

Theses and Dissertations

Drinking water disinfection is critical to prevent the occurrence of waterborne pathogens in drinking water. However, disinfection causes the unintended formation of disinfection byproducts (DBPs) through the reaction of disinfectants (e.g., chlorine, chloramine) with natural organic matter (NOM), algal matter, or anthropogenic pollutants present in source waters. Exposure to DBPs is associated with increased bladder cancer, colorectal cancer, miscarriage, and birth defects. The U.S. EPA currently regulates eleven DBPs in drinking water—four trihalomethanes, five haloacetic acids, bromate, and chlorite. However, research shows that DBP related toxicity in drinking water is driven mainly by other, non-regulated DBPs, particularly iodinated DBPs and …

Coefficients Of The Characteristic Polynomial Of A Hypergraph And Their Combinatorial Properties, Utku Okur

Theses and Dissertations

We investigate the combinatorial properties of the characteristic polynomial $\phi_\mathcal{H}\ev{t}$ of a hypergraph $\mathcal{H}$, in particular, its coefficients. Due to a classical result of Jacobi, the generating function of closed walks at a vertex $u$ in a graph $G$ is determined by the rational function $\phi_{G-u}(t) / \phi_G(t)$. The connection between closed walks of $G$ and its characteristic polynomial has a known elegant proof via an application of Viennot's Heaps of Pieces framework, where cycles are taken as pieces and the concurrence relation is sharing a vertex. Here, we prove a bijection between heaps with a unique maximal piece containing …

Thesis: Comparing Functional And Effective Brain Connectivity Metrics For Eeg, Diksha Srishyla

Theses and Dissertations

Background:Brain connectivity measures have been used to study communication between brain regions using electroencephalography (EEG). Functional and effective connectivity estimate the synchronization and the flow of information between regions, respectively. However, findings from studies using different measures to investigate similar connections do not converge. To guide the selection of functional and effective connectivity measures in future studies, we systematically compared a set of measures in the context of resting state EEG. We examined four functional connectivity metrics (coherence (Coh), the imaginary part of coherence (imCoh), the corrected imaginary part of phase lagged value (ciPLV), the debiased weighted phase-locking index (dwPLI)) …

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

Hearing The Difference: Just Intonation Techniques Utilizing Distortion Product Otoacoustic Emissions In Viola Performance, Calj Green Umezono

Theses and Dissertations

Difference tones, also known as distortion product otoacoustic emissions, are the result of active phenomena in the human cochlea during the conversion of sound waves into bioelectrical signals. Difference tones make it possible to explore alternative musical tuning systems beyond the twelve-tone, equally tempered regime. Musicians have investigated difference tones since the 18th Century in Euro-American musical contexts, but their application has so far been limited in scope. Advances in science, technology, and music theory from the late 19th Century through the early 21st Century have given present-day violists the opportunity to more fully understand the virtues of difference tones …

Multi-Perspective Feature Learning For Facial Expression Recognition In The Wild, Xiangyu Hu

Theses and Dissertations

With the rapid progress of deep learning, Facial Expression Recognition (FER) has seen substantial improvements in performance, particularly “in the wild” meaning real world conditions. Despite these advances, most existing methods extract features from facial images as the sole emotional cues, which limits the model’s ability to capture the full complexity of human emotional expressions.

In reality, facial expressions are composed of diverse and multi-perspective information, including appearance-based cues and geometric structural deformations due to activations of facial muscles. Depending exclusively on one type of representation may fail to exploit the complementary nature of these cues, an issue that becomes …

New Approaches On Source Coding For Quantum Stochastic Sources And Implementation Of Quantum Fanout Gate, Rabins Wosti

Theses and Dissertations

The accurate computation of advanced quantum algorithms like Shor’s integer factorization, quantum phase estimation (QPE), and the quantum Fourier transform (QFT) requires quantum circuits of considerable size and depth. It is difficult to achieve reliable computation with deep quantum circuits due to the limited coherence times of the current noisy quantum devices. The quantum fanout gate is known to be a powerful primitive for reducing the depth of many quantum circuits (Høyer and Špalek 2003; Gottesman and Chuang 1999). Shallow or constant-depth quantum circuits are desirable for both near-term and fault-tolerant quantum computations as they reduce noise and allow faster …

The Church As An Ecological And Cultural Anchor: Examining Its Role In Gifted Education, Advanced Academic Access, And Educational Equity, Matrissa Bennett

Theses and Dissertations

This action research study examines the role of the Black church as an ecological and cultural anchor in addressing the inequities of gifted education and expanding access to advanced academic opportunities for Black students. The study is grounded in Bronfenbrenner’s ecological systems theory, critical race theory, and racial and ethnical socialization, and it explores how the Black church can support student development, empower parental advocacy, and partner with schools to promote educational equity. Conducted at Mountain Valley Baptist Church in South Carolina, the interventions included student mentoring, goal setting sessions, academic enrichment, emotional support initiatives, a parent workshop, and a …

Investigating The Influence Of Instructional Strategies On The Development Of Procedural And Conceptual Knowledge In Advanced Algebra Ii Students, Maura Frances Yinger

Theses and Dissertations

This mixed-methods action research study investigated the influence of instructional strategies shown to improve students’ procedural and conceptual understanding in a rational expressions and equations unit in Advanced Algebra II. The instructional strategies used in the study include comparing, self-explaining, and exploring before instruction. The students (N=27) completed a pre-test and a post-test, both of which were followed by questions asking students to justify their responses on two questions. All students also responded to six digital self-explanation journal prompts. Randomly selected students were placed into three homogenous groups to participate in performance task observations. Analysis of the data …

A Data-Driven Framework For Optimal Retail Store Location, Ming Hui Tan

Dissertations and Theses Collection (Open Access)

This study develops a data-driven framework for optimal retail store location planning that integrates road network analysis, mobility data and optimization techniques. By addressing the limitations of traditional approaches that rely on outdated census data and manual site selection, this research offers a scalable and adaptable solution for retail expansion in diverse urban environments. Chapters 1 and 2 establish the foundational context and theoretical underpinnings of this research. Chapter 1 introduces the research problem and motivation, highlighting the limitations of existing approaches and defining three key research objectives: automating candidate site identification, improving footfall estimation, and developing a scalable multi-site …

Harnessing Se Community Knowledge For Developer-Centric Code Intelligence, Chengran Yang

Dissertations and Theses Collection (Open Access)

The integration of Large Language Models (LLMs), particularly those tailored for programming tasks—referred to as code LLMs—has created novel opportunities to enhance developer productivity. These advanced models automate routine and repetitive coding tasks, such as code generation and debugging, and enable faster prototyping and more efficient problem-solving. Despite these remarkable advantages, the current generation of code LLMs exhibits notable limitations that impact their practical effectiveness in real-world software engineering scenarios. These models frequently produce code that is inefficient or suboptimal in runtime performance, demonstrate opaque reasoning processes, and struggle to adapt effectively to diverse developer contexts and specific requirements. Moreover, …

Creating Blender Animations To Help Students Visualize Organic Chemistry Concepts, Vasilina Vikareva, Jeffrey Hansen

Annual Student Research Poster Session

Many students struggle with organic chemistry because they find it difficult to visualize molecular structures and interactions in three dimensions. Concepts like bond rotation for conformational isomers and intermolecular forces require strong spatial imagination, which traditional 2D drawings fail to develop effectively. This spatial visualization deficit contributes significantly to high failure rates and student anxiety in organic chemistry courses, creating a substantial barrier to success in STEM fields. This project aims to solve this problem by creating animations that demonstrate complex chemical concepts in clear, visual ways that enhance student comprehension and retention. The research methodology involves developing a comprehensive …

Finding Aid For University Of Mississippi Small Manuscripts(Mum01771)

Archives & Special Collections: Finding Aids (alphabetical)

The collection contains items related to the University of Mississippi. The collection is arranged by subject.

Effectiveness Is Not A Criterion Here: The Curriculum Marketplace And The Students It Leaves Behind, Serena E. Roche

Cardozo Journal of Equal Rights & Social Justice

No abstract provided.

Investigating The Presence Of R-Loops At The Centromeres Of Drosophila Melanogaster, Daniel D'Souza

Holster Scholar Projects

This study investigates the presence and localization of R-loops at the centromeres of Drosophila melanogaster. R-loops are non-canonical nucleic acid structures that have been implicated in various cellular processes, including genomic instability and accurate chromosome segregation. Although previous research has found R-loops at Drosophila satellite sequences and LTR retrotransposons, their presence and function at the centromeres of a whole organism remain largely unknown. Using IF-FISH (immunofluorescence-fluorescence in situ hybridization), we stained R-loops with the S9.6 antibody. A UAS-rnh1 overexpression line was used to induce the overexpression of RNase H1, an enzyme that resolves R-loops, to confirm the specificity of …

Lightweight Population-Based Policy Optimization For Pickup And Delivery Problems, Yizhou Liu, Li Li, Yixin Xu, Tang Liu, Rong Cheng, Die Wu, Jilin Yang, Jingwen Li

Research Collection School Of Computing and Information Systems

In recent years, applying deep models to automatically learn construction heuristics for vehicle routing problems has achieved remarkable advancements. However, they are less effective in searching solutions due to two primary limitations: relying on deterministic probability distributions and overlooking the strategic advantage of prioritizing nearby unvisited nodes during the route construction process, resulting in suboptimal policies In this paper, we propose a novel lightweight population-based policy optimization (LPPO) framework that learns a diverse population of solution strategies through the utilization of innovative perturbation factors, in order to facilitate search exploration. Moreover, we design a localized attention synthesis (LAS) network to …

Look Before You Decide: Prompting Active Deduction Of Mllms For Assumptive Reasoning, Yian Li, Wentao Tian, Yang Jiao, Jingjing Chen, Tianwen Qian, Bin Zhu, Na Zhao, Yu‑Gang Jiang

Research Collection School Of Computing and Information Systems

Recently, Multimodal Large Language Models (MLLMs) have achieved significant success across multiple disciplines due to their exceptional instruction-following capabilities and extensive world knowledge. However, whether these MLLMs possess human-like compositional reasoning abilities remains an open problem. To unveil their reasoning behaviors, we first curate a Multimodal Assumptive Reasoning Benchmark (MARS-Bench) in this paper. Interestingly, we find that most prevalent MLLMs can be easily fooled by the introduction of a presupposition into the question, whereas such presuppositions appear naive to human reasoning. Besides, we also propose a simple yet effective method, Active Deduction (AD), a novel reinforcement learning paradigm to encourage …

Memory-Efficient 4-Bit Preconditioned Stochastic Optimization, Jingyang Li, Kuangyu Ding, Kim-Chuan Toh, Pan Zhou

Research Collection School Of Computing and Information Systems

Preconditioned stochastic optimization algorithms, exemplified by Shampoo, outperform first-order optimizers by offering theoretical convergence benefits and practical gains in large-scale neural network training. However, they incur substantial memory overhead due to the storage demands of non-diagonal preconditioning matrices. To address this, we introduce 4-bit quantization for Shampoo’s preconditioners. We introduce two key methods: First, we apply Cholesky decomposition followed by quantization of the Cholesky factors, reducing memory usage by leveraging their lower triangular structure while better preserving spectral properties to minimize information loss. To our knowledge, this is the first quantization approach applied to Cholesky factors of preconditioners. Second, we …

Probabilistic Prototype Calibration Of Vision-Language Models For Generalized Few-Shot Semantic Segmentation, Jie Liu, Jiayi Shen, Pan Zhou, Jan-Jakob Sonke, Stratis Gavves

Research Collection School Of Computing and Information Systems

Generalized Few-Shot Semantic Segmentation (GFSS) aims to extend a segmentation model to novel classes with only a few annotated examples while maintaining performance on base classes. Recently, pretrained vision-language models (VLMs) such as CLIP have been leveraged in GFSS to improve generalization on novel classes through multi-modal prototypes learning. However, existing prototype-based methods are inherently deterministic, limiting the adaptability of learned prototypes to diverse samples, particularly for novel classes with scarce annotations. To address this, we propose FewCLIP, a probabilistic prototype calibration framework over multi-modal prototypes from the pretrained CLIP, thus providing more adaptive prototype learning for GFSS. Specifically, FewCLIP …

From Holistic To Localized: Local Enhanced Adapters For Efficient Visual Instruction Fine-Tuning, Pengkun Jiao, Bin Zhu, Jingjing Chen, Chong-Wah Ngo, Yugang Jiang

Research Collection School Of Computing and Information Systems

Efficient Visual Instruction Fine-Tuning (EVIT) seeks to adapt Multimodal Large Language Models (MLLMs) to downstream tasks with minimal computational overhead. However, as task diversity and complexity increase, EVIT faces significant challenges in resolving data conflicts. To address this limitation, we propose the Dual Low-Rank Adaptation (Dual-LoRA), a holistic-to-local framework that enhances the adapter’s capacity to address data conflict through dual structural optimization. Specifically, we utilize two subspaces: a skill space for stable, holistic knowledge retention, and a rank-rectified task space that locally activates the holistic knowledge. Additionally, we introduce Visual Cue Enhancement (VCE), a multi-level local feature aggregation module designed …