Physical Sciences and Mathematics Commons^™

Analytic Wavefront Sets Of Spherical Distributions On The De Sitter Space, Iswarya Sitiraju

LSU Doctoral Dissertations

In this work, we determine the wavefront set of certain eigendistributions of the Laplace-Beltrami operator on the de Sitter space. Let G′ = O_1,n(R) be the Lorentz group, and let H′ = O_1,n−1(R) ⊂ G′ be its subset. The de Sitter space dSⁿ is a one-sheeted hyperboloid in R^1,n isomorphic to G′/H′. A spherical distribution is an H′-invariant eigendistribution of the Laplace-Beltrami operator on dSⁿ. The space of spherical distributions with eigenvalue λ, denoted by D_λ^H'(dSⁿ), has dimension 2. We construct a basis for the space of …

The Modular Generalized Springer Correspondence For The Symplectic Group, Joseph Dorta

LSU Doctoral Dissertations

The Modular Generalized Springer Correspondence (MGSC), as developed by Achar, Juteau, Henderson, and Riche, stands as a significant extension of the early groundwork laid by Lusztig's Springer Correspondence in characteristic zero which provided crucial insights into the representation theory of finite groups of Lie type. Building upon Lusztig's work, a generalized version of the Springer Correspondence was later formulated to encompass broader contexts.

In the realm of modular representation theory, Juteau's efforts gave rise to the Modular Springer Correspondence, offering a framework to explore the interplay between algebraic geometry and representation theory in positive characteristic. Achar, Juteau, Henderson, and Riche …

Exploration Of Characteristic Curve In Fox Float 3 Shock Dampers To Expedite Shock Damp Tuning., Joshua R. Moore

Honors College Theses

The shock absorber is an integral part of a vehicle suspension system and has a strong influence on its performance, especially in the case of motorsports. It is important to study the force versus velocity relationship, commonly known as the characteristic curve of the shock absorber both during compression and rebound. Vendor-supplied characteristics often reflect the behavior of the shock absorber in a particular setting. However, during the installation, the settings inside the shock absorber are adjusted to increase the human comfort level and performance of the vehicle. This may change the characteristic curve of the shock. The available data …

Localized Collocation Meshless Method For Modeling Transdermal Pharmacokinetics In Multiphase Skin Structures, Eduardo Divo

Math Department Colloquium Series

The human skin has a complicated structure with many multi-scale, biophysical effects impacting the propagation of skin-injected substances, such as partitioning, metabolic reactions, adsorption and elimination. An extended version of Fick’s second law governing the process of the compound diffusion in various skin layer is employed in the current work by considering the conservation of mass of the substance and the metabolic reaction of the substance in viable skin. Additionally, a model assuming linear coupling between the substance concentrations that are bound and unbound with blood was developed. Using such a model, a set of coupled partial differential equations are …

Advanced Electroanalysis For Electrosynthesis, Monica Brachi, Wassim El Housseini, Kevin Beaver, Rohit Jadhav, Ashwini Dantanarayana, Dylan G. Boucher, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Electrosynthesis is a Popular, Environmentally Friendly Substitute for Conventional Organic Methods. It Involves using Charge Transfer to Stimulate Chemical Reactions through the Application of a Potential or Current between Two Electrodes. in Addition to Electrode Materials and the Type of Reactor Employed, the Strategies for Controlling Potential and Current Have an Impact on the Yields, Product Distribution, and Reaction Mechanism. in This Review, Recent Advances Related to Electroanalysis Applied in Electrosynthesis Were Discussed. the First Part of This Study Acts as a Guide that Emphasizes the Foundations of Electrosynthesis. These Essentials Include Instrumentation, Electrode Selection, Cell Design, and Electrosynthesis Methodologies. …

Navigating Murky Waters: State-Level Strategies For Wetland Preservation And Tile Drainage Regulation After Sackett V. Epa, Caleb M. Swanson

Honors Thesis

Wetlands are some of the world’s most valuable ecosystems, serving as provisioners of species habitat, carbon sequestration, flood mitigation, water quality purification, and other ecosystem services. Human development has resulted in substantial wetland loss the world over. In the 1970s, the United States Congress passed the Clean Water Act, giving the EPA broad authority over wetland protection. However, in the summer of 2023, the United States Supreme Court decided Sackett v. EPA, limiting the EPA’s jurisdiction over wetlands to those indistinguishably connected to generally recognized “Waters of the United States” and removing federal protection for millions of acres of wetlands, …

Mourning The Planet And Signs Of Hope: The Role Of Grief And Resilience In How Students Understand Climate Change, Zachary C. Wooten, Jocelyn Brown

Sustainability Research & Practice Seminar Presentations

Professor Zachary Wooten (Honors College) and Jocelyn Brown '23 present "Mourning the Planet and Signs of Hope: The Role of Grief and Resilience in How Students Understand Climate Change"

Final 2024 Butte Priority Soils Operable Unit Helehan Borrow Submittal #2, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

From A Shorter Winter Season To More Storm Damage: New Hampshire Outdoor Recreation Providers Feel Climate Impacts Far More Than Visitors, Maddie Smith, Michael D. Ferguson, Lauren A. Ferguson, Alexandra R. Contosta, Elizabeth Burakowski, Dovev Levine, Shannon Rogers

The Carsey School of Public Policy at the Scholars' Repository

In this brief, the authors examine to what extent outdoor recreation providers and visitors in New Hampshire are impacted by annual climatic conditions representative of long-term trends, specifically, through the 2024–2028 New Hampshire Statewide Comprehensive Outdoor Recreation Plan (SCORP). For the first time, the New Hampshire SCORP included an investigation of climate-related impacts on outdoor recreation from the perspective of both visitors and providers.

The findings of the study uncovered notable disparities in how New Hampshire’s outdoor recreation providers and visitors perceive climate conditions’ impact on outdoor recreation, particularly in the categories of “winter” and “extreme weather.” Understanding the perspectives …

Applying Mathematical Modeling To The Study Of Family Systems, Dahlia Maxwell

Theses and Dissertations

Mathematical modeling provides a powerful framework for insight into current scientific theories as well as hypothesis generation for further research. Despite its undeniable potential to enrich scientific advancement, the application of mathematical modeling remains conspicuously scarce in the field of family science. The complexity inherent in family dynamics, coupled with the intricate interplay of emotions in the individual, underscores the necessity of a robust analytical approach. Addressing this critical gap in the literature, this thesis introduces a sophisticated mathematical model of family dynamics integrating essential elements from family systems theory, emotion dynamics, and appraisal theory. The model is implemented as …

Employing Ai To Enhance In-Class Role Playing Scenarios, Eric Fournier

Generative AI Teaching Activities

Role playing can deepen student’s engagement with course content and help them develop skills while learning course material. Students will use AI to develop their characters and help them craft compelling arguments in the role-play scenarios

Residential Metals Abatement Program Investigation Summary Report (Non-Residential Parcels – Indoor Dust) United Congregational Church (Crayon Academy Preschool), Environmental Resource Management (Erm)

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites Field Sampling Plan (Fsp) Package #10: Ur-44, Ur-45, Ur-46, Ur-47, And Ur-48, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Chiral Recognition Of Chiral (Hetero)Cyclic Derivatives Probed By Tetraaza Macrocyclic Chiral Solvating Agents Via ¹H Nmr Spectroscopy, Yu Wang, Hongmei Zhao, Chunxia Yang, Lixia Fang, Li Zheng, Hehua Lv, Pericles Stavropoulos, Lin Ai, Jiaxin Zhang

Chemistry Faculty Research & Creative Works

In the Field of Chiral Recognition, Chiral Cyclic Organic Compounds, Especially Heterocyclic Organic Compounds, Have Attracted Little Attention and Have Been Rarely Studied as Chiral Substrates by Means of 1H NMR Spectroscopy. in This Paper, Enantiomers of Thiohydantoin Derivatives, Representing Typical Five-Membered N,N-Heterocycles, Have Been Synthesized and Utilized for Assignment of Absolute Configuration and Analysis of Enantiomeric Excess. All Enantiomers Have Been Successfully Differentiated with the Assistance of Novel Tetraaza Macrocyclic Chiral Solvating Agents (TAMCSAs) by 1H NMR Spectroscopy. Surprisingly, Unprecedented Nonequivalent Chemical Shift Values (Up to 2.052 Ppm) of the NH Proton of Substrates Have Been Observed, a New …

How Generative Ai Models Such As Chatgpt Can Be (Mis)Used In Spc Practice, Education, And Research? An Exploratory Study, Fadel M. Megahed, Ying-Ju (Tessa) Chen, Joshua A. Ferris, Sven Knoth, L. Allison Jones-Farmer

Mathematics Faculty Publications

Generative Artificial Intelligence (AI) models such as OpenAI's ChatGPT have the potential to revolutionize Statistical Process Control (SPC) practice, learning, and research. However, these tools are in the early stages of development and can be easily misused or misunderstood. In this paper, we give an overview of the development of Generative AI. Specifically, we explore ChatGPT's ability to provide code, explain basic concepts, and create knowledge related to SPC practice, learning, and research. By investigating responses to structured prompts, we highlight the benefits and limitations of the results. Our study indicates that the current version of ChatGPT performs well for …

Cardiogpt: An Ecg Interpretation Generation Model, Guohua Fu, Jianwei Zheng, Islam Abudayyeh, Chizobam Ani, Cyril Rakovski, Louis Ehwerhemuepha, Hongxia Lu, Yongjuan Guo, Shenglin Liu, Huimin Chu, Bing Yang

Mathematics, Physics, and Computer Science Faculty Articles and Research

Numerous supervised learning models aimed at classifying 12-lead electrocardiograms into different groups have shown impressive performance by utilizing deep learning algorithms. However, few studies are dedicated to applying the Generative Pre-trained Transformer (GPT) model in interpreting electrocardiogram (ECG) using natural language. Thus, we are pioneering the exploration of this uncharted territory by employing the CardioGPT model to tackle this challenge. We used a dataset of ECGs (standard 10s, 12-channel format) from adult patients, with 60 distinct rhythms or conduction abnormalities annotated by board-certified, actively practicing cardiologists. The ECGs were collected from The First Affiliated Hospital of Ningbo University and Shanghai …

Advancing Single-Cell Proteomics Through Innovations In Liquid Chromatography And Mass Spectrometry, Kei Grant Isaac Webber

Theses and Dissertations

Traditional proteomics studies can measure many protein biomarkers simultaneously from a single patient-derived sample, promising the possibility of syndromic diagnoses of multiple diseases sharing common symptoms. However, precious cellular-level information is lost in conventional bulk-scale studies that measure tissues comprising many types of cells. As single cells are the building blocks of organisms and are easier to biopsy than traditional bulk samples, performing proteomics on a single-cell level would benefit clinicians and patients. Single-cell proteomics, combined with mass spectrometry imaging, can be used to analyze cells in their microenvironment, preserving spatial information. We have previously used laser-capture microdissection to isolate …

A Systematic Review: Mirror Neurons & Schizophrenia, Yashesvi Sharma, Surajit Dey

Annual Research Symposium

This research project establishes a link between Mirror Neuron System (MNS) activity and this information's implications in treating and understanding schizophrenia, specifically, schizophrenic patients with negative symptoms.

Exploring Practical Measures As An Approach For Measuring Elementary Students’ Attitudes Towards Computer Science, Umar Shehzad, Mimi M. Recker, Jody E. Clarke-Midura

Publications

This paper presents a novel approach for predicting the outcomes of elementary students’ participation in computer science (CS) instruction by using exit tickets, a type of practical measure, where students provide rapid feedback on their instructional experiences. Such feedback can help teachers to inform ongoing teaching and instructional practices. We fit a Structural Equation Model to examine whether students' perceptions of enjoyment, ease, and connections between mathematics and CS in an integrated lesson predicted their affective outcomes in self-efficacy, interest, and CS identity, collected in a pre- post- survey. We found that practical measures can validly measure student experiences.

Effects Of Heterogeneous Data Sets And Time-Lag Measurement Techniques On Cosmological Parameter Constraints From Mg Ii And C Iv Reverberation-Mapped Quasar Data, Shulei Cao, Michal Zajaček, Bożena Czerny, Swayamtrupta Panda, Bharat Ratra

Physics Faculty Publications and Presentations

Previously, we demonstrated that Mg II and C IV reverberation-mapped quasars (RM QSOs) are standardizable and that the cosmological parameters inferred using the broad-line region radius–luminosity (R–L) relation are consistent with those determined from better-established cosmological probes. With more data expected from ongoing and future spectroscopic and photometric surveys, it is imperative to examine how new QSO data sets of varied quality, with their own specific luminosity and time-delay distributions, can be best used to determine more restrictive cosmological parameter constraints. In this study, we test the effect of adding 25 OzDES Mg II RM QSOs as well …

Procedures For Rangeland Condition Assessment In The Pilbara And Southern Rangelands 2022, Department Of Primary Industries And Regional Development

Natural resources published reports

To define the procedures used in 2022 by the Department of Primary Industries and Regional Development (DPIRD) to complete rangeland condition assessment (RCA) in the Pilbara and southern rangelands region which has predominantly shrub-based pastures. For the rest of the pastoral estate, DPIRD uses the Procedures for RCA in the Kimberley which has grass pastures.

RCA is the process DPIRD uses to make systematic, lease level assessment of rangeland. Rangeland condition considers both the condition of pastures (as defined in the Pasture condition and management guide for the Pilbara rangelands or Southern rangelands pasture condition and management guides) and soils …

Let’S Move! Benefits Of Exercise Compared To Ssris (Escitalopram) For The Management Of Depression: Research From 2020 And Beyond, Brianna Droessler-Aschliman

Physician Assistant Scholarly Project Posters

• Purpose: Determine the effectiveness of exercise as either monotherapy or in combination with SSRIs (selective serotonin reuptake inhibitors) for the management of major depressive disorder.

• Studies gathered for this review came from the following databases: PubMed, SpringerLink, Academic Search Ultimate, Academic Search Complete, and CINAHL.

• Review of current research that was completed between the years 2020-2023 that consisted of either clinical trials, RCTs, or meta-analysis. • Upon completion of the literature review: exercise is equivocal to SSRIs as a treatment option. While this is a significant finding, the benefits of exercises are more consistent in those that …

Multi-Aspect Rule-Based Ai: Methods, Taxonomy, Challenges And Directions Towards Automation, Intelligence And Transparent Cybersecurity Modeling For Critical Infrastructures, Iqbal H. Sarker, Helge Janicke, Mohamed A. Ferrag, Alsharif Abuadbba

Research outputs 2022 to 2026

Critical infrastructure (CI) typically refers to the essential physical and virtual systems, assets, and services that are vital for the functioning and well-being of a society, economy, or nation. However, the rapid proliferation and dynamism of today's cyber threats in digital environments may disrupt CI functionalities, which would have a debilitating impact on public safety, economic stability, and national security. This has led to much interest in effective cybersecurity solutions regarding automation and intelligent decision-making, where AI-based modeling is potentially significant. In this paper, we take into account “Rule-based AI” rather than other black-box solutions since model transparency, i.e., human …

Towards Low-Resource Rumor Detection: Unified Contrastive Transfer With Propagation Structure, Hongzhan Lin, Jing Ma, Ruichao Yang, Zhiwei Yang, Mingfei Cheng

Research Collection School Of Computing and Information Systems

The truth is significantly hampered by massive rumors that spread along with breaking news or popular topics. Since there is sufficient corpus gathered from the same domain for model training, existing rumor detection algorithms show promising performance on yesterday's news. However, due to a lack of substantial training data and prior expert knowledge, they are poor at spotting rumors concerning unforeseen events, especially those propagated in different languages (i.e., low-resource regimes). In this paper, we propose a simple yet effective framework with unified contrastive transfer learning, to detect rumors by adapting the features learned from well-resourced rumor data to that …

Acav: A Framework For Automatic Causality Analysis In Autonomous Vehicle Accident Recordings, Huijia Sun, Christopher M. Poskitt, Yang Sun, Jun Sun, Yuqi Chen

Research Collection School Of Computing and Information Systems

The rapid progress of autonomous vehicles (AVs) has brought the prospect of a driverless future closer than ever. Recent fatalities, however, have emphasized the importance of safety validation through large-scale testing. Multiple approaches achieve this fully automatically using high-fidelity simulators, i.e., by generating diverse driving scenarios and evaluating autonomous driving systems (ADSs) against different test oracles. While effective at finding violations, these approaches do not identify the decisions and actions that caused them -- information that is critical for improving the safety of ADSs. To address this challenge, we propose ACAV, an automated framework designed to conduct causality analysis for …

Discovering Significant Topics From Legal Decisions With Selective Inference, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually interpreted to gain insights about significant topics, and case-topic weights which can be used to identify representative cases for each topic. We demonstrate the method on a new dataset of domain name disputes and a canonical dataset of European Court of Human Rights violation cases. Topic models based on latent semantic analysis as well as language …

Combating Financial Crimes With Unsupervised Learning Techniques: Clustering And Dimensionality Reduction For Anti-Money Laundering, Ahmed N. Bakry, Almohammady S. Alsharkawy, Mohamed S. Farag, Kamal R. Raslan

Al-Azhar Bulletin of Science

Anti-Money Laundering (AML) is a crucial task in ensuring the integrity of financial systems. One keychallenge in AML is identifying high-risk groups based on their behavior. Unsupervised learning, particularly clustering, is a promising solution for this task. However, the use of hundreds of features todescribe behavior results in a highdimensional dataset that negatively impacts clustering performance.In this paper, we investigate the effectiveness of combining clustering method agglomerative hierarchicalclustering with four dimensionality reduction techniques -Independent Component Analysis (ICA), andKernel Principal Component Analysis (KPCA), Singular Value Decomposition (SVD), Locality Preserving Projections (LPP)- to overcome the issue of high-dimensionality in AML data and …

Graph Neural Network Guided By Feature Selection And Centrality Measures For Node Classification On Homophilic And Heterophily Graphs, Asmaa M. Mahmoud, Heba F. Eid, Abeer S. Desuky, Hoda A. Ali

Al-Azhar Bulletin of Science

One of the most recent developments in the fields of deep learning and machine learning is Graph Neural Networks (GNNs). GNNs core task is the feature aggregation stage, which is carried out over the node's neighbours without taking into account whether the features are relevant or not. Additionally, the majority of these existing node representation techniques only consider the network's topology structure while completely ignoring the centrality information. In this paper, a new technique for explaining graph features depending on four different feature selection approaches and centrality measures in order to identify the important nodes and relevant node features is …

Moid Using New Sets Of Universal Functions, Ayman Homda, Hany R. Dwidar, Abdelaziz A. Bakry, M.N. Mohamad Ismail, Ahmed El-Raffie

Al-Azhar Bulletin of Science

In this paper, based on Goodyear's time transformation formula, we used a set of modified universal functions to construct the minimum distance function between any two celestial objects. We determined the distance between objects in space under a specific time constraint. We used the continued fractions method for quick convergence of the distance function. We used the inverse series to obtain a first initial guess to solve the convergence equation. Furthermore, the Lagrange multiplier method was used to determine the minimum distance between the two objects under the specified time constraint. We constructed an algorithm and applied it with the …

Environmental, Social, And Governance (Esg) And Artificial Intelligence In Finance: State-Of-The-Art And Research Takeaways, Trstan Lim

Research Collection School Of Computing and Information Systems

The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation focuses on three primary research questions: the main research themes concerning ESG and AI in finance, the evolution of research intensity and interest in these areas, and the application and evolution of AI techniques specifically in research studies within the ESG and AI in finance domain. Eight archetypical …