Physical Sciences and Mathematics Commons^™

Seasonal Seepage Fluid Flow And Pressure Detection Beneath Flood Protection Levees In The Lower Mississippi River Valley Using Non-Invasive Geophysical Methods, Daniel Locci

LSU Doctoral Dissertations

This study explores the use of shear-wave seismic reflection and electrical resistivity techniques to complement our understanding of seepage pore pressure variations and soil type estimation beneath earthen levees in the Mississippi River floodplain. The seasonal variations of water level in the river create changes in pore pressure in the adjacent aquifer, which can be detected using time-lapse shear-wave velocity analysis. The seismic reflection patterns during these pressure variations show changes in velocity that can be translated into changes in effective pressure, allowing us to distinguish between confined and leaky aquifers.

In addition, the integration of geophysical methods such as …

Physio-Psycho-Social Interaction Mechanism In Dyadic Health Of Young And Middle-Aged Stroke Survivors And Their Spousal Caregivers: A Longitudinal Observational Study Protocol, Bei-Lei Lin, Su-Yan Chen, Er-Feng Guo, Peng-Bo Zhang, Zhi-Wei Liu, Hui Li, Yong-Xia Mei

Faculty, Staff and Student Publications

Introduction: In recent years, stroke has become more common among young people. Stroke not only has a profound impact on patients' health but also incurs stress and health threats to their caregivers, especially spousal caregivers. Moreover, the health of stroke survivors and their caregivers is interdependent. To our knowledge, no study has explored dyadic health of young and middle-aged stroke survivors and their spousal caregivers from physiological, psychological and social perspectives. Therefore, this proposed study aims to explore the mechanism of how physiological, psychological and social factors affect dyadic health of young and middle-aged stroke survivors and their spousal caregivers. …

Quantitative Proteomic Screening Uncovers Candidate Diagnostic And Monitoring Serum Biomarkers Of Ankylosing Spondylitis, Reyna Chavez, Kamala Vanarsa, Chandra Mohan, John Reveille

Faculty, Staff and Student Publications

BACKGROUND: We sought to discover serum biomarkers of ankylosing spondylitis (AS) for diagnosis and monitoring disease activity.

METHODS: We studied biologic-treatment-naïve AS and healthy control (HC) patients' sera. Eighty samples matched by age, gender, and race (1:1:1 ratio) for AS patients with active disease, inactive disease, and HC were analyzed with SOMAscan™, an aptamer-based discovery platform. T-tests tests were performed for high/low-disease activity AS patients versus HCs (diagnosis) and high versus low disease activity (Monitoring) in a 2:1 and 1:1 ratio, respectively, to identify differentially expressed proteins (DEPs). We used the Cytoscape Molecular Complex Detection (MCODE) plugin to find clusters …

Characterizing The Development And Drivers Of 2021 Western Us Drought, Grace Affram, Wei Zhang, Lawrence Hipps, Cody Ratterman

Publications

Understanding the drivers of the major 2021 drought conditions across the Western U.S. (WUS) is important to develop future resilience and adaptation measures. While evapotranspiration (ET) tends to increase in a warming climate when water is available, areas with low precipitation would evaporate less water than expected, as seen in the 2021 drought. This study examines the relative roles of higher temperatures and lower precipitation, as well as anthropogenic forcing (e.g. increased greenhouse gases and land-use land-cover change) to the 2021 drought across the WUS. Using observations, the anomalously dry 2021 soil moisture is mainly tied to precipitation deficit, rather …

Forecasting Winners And Losers Of Climate Change: Insights From The Interactions Between Organisms And Their Microclimates, Michael Sears

Sustainability Seminar Series

Meaningful forecasts of the responses of organisms to climate require an explicit understanding of how organismal behavior and physiology are affected by environmental heterogeneity. Such predictions are complicated because physiology and behavior vary over different time scales, vary across different life stages, and do not operate in isolation of one another. In this talk, I review case studies from my lab to highlight progress that has been made along these fronts and provide generalizations that might be made to other systems, particularly in the context of predicting responses to climate change.

Corrosion Case Study On Automobile, Grace Ajayi, Xinran Pan, Geethu Sasikala, Marshall S. Yang

Chemistry Publications

No abstract provided.

A Language-Model-Based Chatbot That Considers The User's Personality Profile And Emotions To Support Caregivers Of People With Dementia, Yeganeh Nasiri

Theses and Dissertations

Chatbots are programs that mimic human conversation using Artificial Intelligence (AI). Recent advances in natural language pro- cessing pave the way for chatbots to generate more human-like responses. Therefore, chatbots are finding more complex tasks to perform, such as emotional support which requires both understanding emotions and the ability to properly respond to them. This work presents a chatbot capable of identifying the user's personality and creating responses based on that. During this process, emotion detection is being used to detect and react to users' emotions. The chatbot uses a dynamic knowledge graph to save information as the conversation goes …

Unsupervised Categorical Clustering On Labor Markets, Matthew James Steffen

Theses and Dissertations

During this "white collar recession,'' there is a flooded labor market of workers. For employers seeking to hire, there is a need to identify potential qualified candidates for each job. The current state of the art is LinkedIn Recruiting or elastic search on Resumes. The current state of the art lacks efficiency and scalability along with an intuitive ranking of candidates. We believe this can be fixed with multi-layer categorical clustering via modularity maximization. To test this, we gathered a dataset that is extensive and representative of the job market. Our data comes from PeopleDataLabs and LinkedIn and is sampled …

Ecological Stability Of Late Pleistocene-To-Holocene Lesotho, Southern Africa, Facilitated Human Upland Habitation, Robert Patalano, Charles Arthur, William Christopher Carleton, Sam Challis, Genevieve Dewar, Kasun Gayantha, Gerd Glexiner, Jana Ilgner, Mary Lucas, Sara Marzo, Rethabile Mokhachane, Kyra Pazan, Diana Spurite, Mike W. Morley, Adrian Parker, Peter Mitchell, Brian A. Stewart, Patrick Roberts

Biological and Biomedical Sciences Department Faculty Journal Articles

Investigation of Homo sapiens’ palaeogeographic expansion into African mountain environments are changing the understanding of our species’ adaptions to various extreme Pleistocene climates and habitats. Here, we present a vegetation and precipitation record from the Ha Makotoko rockshelter in western Lesotho, which extends from ~60,000 to 1,000 years ago. Stable carbon isotope ratios from plant wax biomarkers indicate a constant C3-dominated ecosystem up to about 5,000 years ago, followed by C4 grassland expansion due to increasing Holocene temperatures. Hydrogen isotope ratios indicate a drier, yet stable, Pleistocene and Early Holocene compared to a relatively wet Late Holocene. Although relatively …

Characterizing The Informativity Of Level Ii Book Data For High Frequency Trading, Logan B. Nielsen

Theses and Dissertations

High Frequency Trading (HFT) algorithms are automated feedback systems interacting with markets to maximize returns on investments. These systems have the potential to read different resolutions of market information at any given time, where Level I information is the minimal information about an equity--essentially its price--and Level II information is the full order book at that time for that equity. This paper presents a study of using Recurrent Neural Network (RNN) models to predict the spread of the DOW Industrial 30 index traded on NASDAQ, using Level I and Level II data as inputs. The results show that Level II …

Einstein-Rosen Bridge From The Minimal Length, Jonas R. Mureika, Kimet Jusufi, Emmanuel Moulay, Ahmed Farag Ali

Physics Faculty Works

We use a string T-duality corrected pair of regular black holes to construct an Einstein-Rosen (ER) bridge with the wormhole throat proportional to the zero-point (Planck) length. This may be a geometric realization of quantum entanglement for particle/antiparticle pairs. We point out that for an extreme mass configuration consisting of a black hole pair, one can have an ER bridge with a horizon area that coincides with the Bekenstein minimal area bound along with a wormhole mass proportional to the Planck mass. This could be related to gravitational self-completeness with quantum mechanical mass limits. We also discuss the ER bridge …

Membership Probabilities Of White Dwarfs In Open Star Clusters, Sarah Phillips

Honors Theses

This thesis explores the relationship between astronomical position data and star cluster membership. Our research project focuses on the mathematical probability of cluster membership for white dwarf stars (WDs), specifically membership candidates within the open cluster Messier 35. Through Gaussian analysis of proper motion data, we examine the membership probability of each candidate. Establishing cluster membership has broad applications and can allow further determination of a star’s characteristics including stellar age and evolution. Of particular interest are two WD member candidates for Messier 35: LAWDS 4, a DB WD with a helium-dominated atmosphere as opposed to the more common hydrogen-dominated …

Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed (Ir) Sites Colorado Dump – West Lot Construction Completion Report (Ccr), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

E6 Models In Light Of Precision MW Measurements, Vernon Barger, Cash Hauptmann, Peisi Huang, Wai-Yee Keung

Department of Physics and Astronomy: Faculty Publications

We propose a solution to the recent W mass measurement by embedding the Standard Model within E₆ models. The presence of a new U(1) group shifts the W boson mass at the tree level and introduces a new gauge boson Z' which has been searched for at collider experiments. In this article, we identify the parameter space that explains the new W mass measurement and is consistent with current experimental Z' searches. As U(1) extensions can be accommodated in supersymmetric models, we also consider the supersymmetric scenario of E₆ models, and show that a 125 GeV …

Multi-Modal Knowledge Graph Inference Via Media Convergence And Logic Rule, Feng Lin, Dongmei Li, Wenbin Zhang, Dongsheng Shi, Yuanzhou Jiao, Qianzhong Chen, Yiying Lin, Wentao Zhu

Michigan Tech Publications, Part 1

Media convergence works by processing information from different modalities and applying them to different domains. It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective. To address the issue, an inference method based on Media Convergence and Rule-guided Joint Inference model (MCRJI) has been proposed. The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction. First, a multi-headed self-attention approach …

Carborane-Containing Hydroxamate Mmp Ligands For The Treatment Of Tumors Using Boron Neutron Capture Therapy (Bnct): Efficacy Without Tumor Cell Entry, Sebastian Flieger, Mao Takagaki, Natsuko Kondo, Marlon Lutz Jr., Yash Gupta, Hiroki Ueda, Yoshinori Sakurai, Graham Moran, Prakasha Kempaiah, Narayan Hosmane, Minoru Suzuki, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

New carborane-bearing hydroxamate matrix metalloproteinase (MMP) ligands have been synthesized for boron neutron capture therapy (BNCT) with nanomolar potency against MMP-2, -9 and -13. New analogs are based on MMP inhibitor CGS-23023A, and two previously reported MMP ligands 1 (B1) and 2 (B2) were studied in vitro for BNCT activity. The boronated MMP ligands 1 and 2 showed high in vitro tumoricidal effects in an in vitro BNCT assay, exhibiting IC₅₀ values for 1 and 2 of 2.04 × 10⁻² mg/mL and 2.67 × 10⁻² mg/mL, respectively. The relative killing effect of 1 to L-boronophenylalanine (BPA) is …

Spectral Solar Irradiance And It's Effect On Earths Atmosphere, Bishal Kumar

University Departments

No abstract provided.

Studies Of Neutron Capture Reactions For Nucleosynthesis, Guruprsad .

University Departments

No abstract provided.

A Hybrid Mcdm Approach For Industrial Robots Selection For The Automotive Industry, Abduallah Gamal, Mona Mohamed

Neutrosophic Systems with Applications

The use of robots in various stages of the production process is now commonplace across practically all sectors of the economy. Additionally, even for present-day small and medium-sized businesses, this has developed into a very powerful need in recent years and continues to grow in importance. The selection of an industrial robot is a very complicated decision-making issue due to the fact that there are numerous aspects and criteria that are in conflict with one another, as almost all of the earlier research emphasized. In addition, the many sophisticated requirements that have been added to these robots by the makers …

Entropy In Non-Equilibrium Systems, Linton C. Fernanndies

University Departments

No abstract provided.

A Hybrid Mcdm Approach For Industrial Robots Selection For The Automotive Industry, Abduallah Gamal, Mona Mohamed

Neutrosophic Systems with Applications

The use of robots in various stages of the production process is now commonplace across practically all sectors of the economy. Additionally, even for present-day small and medium-sized businesses, this has developed into a very powerful need in recent years and continues to grow in importance. The selection of an industrial robot is a very complicated decision-making issue due to the fact that there are numerous aspects and criteria that are in conflict with one another, as almost all of the earlier research emphasized. In addition, the many sophisticated requirements that have been added to these robots by the makers …

Network Representation Theory In Materials Science And Global Value Chain Analysis, Mats C. Haneberg

Theses and Dissertations

This thesis is divided into two distinct chapters. In the first chapter, we apply network representation learning to the field of materials science in order to predict aluminum grain boundaries' properties and locate the most influential atoms and subgraphs within each grain boundary. We create fixed-length representations of the aluminum grain boundaries that successfully capture grain boundary structure and allow us to accurately predict grain boundary energy. We do this through two distinct methods. The first method we use is a graph convolutional neural network, a semi-supervised deep learning algorithm, and the second method is graph2vec, an unsupervised representation learning …

The Topology And Dynamics Of Surface Diffeomorphisms And Solenoid Embeddings, Xueming Hui

Theses and Dissertations

We study two topics on surface diffeomorphisms, their mapping classes and dynamics. For the mapping classes of a punctured disc, we study the $\ZxZ$ subgroups of the fundamental groups of the corresponding mapping tori. An application is the proof of the fact that a satellite knot with braid pattern is prime. For the mapping classes of the disc minus a Cantor set, we study a special type of reducible mapping class. This has direct application on the embeddings of solenoids in $\mathbb{S}^3$. We also give some examples of other types of mapping classes of the disc minus a Cantor set. …

Quantification Of Anion And Cation Uptake In Ice Ih Crystals, Tiara Sivells, Pranav Viswanathan, Jenée D. Cyran

Chemistry and Biochemistry Faculty Publications and Presentations

While ice has very low solubility for salts compared to water, small amounts of ions are doped into ice crystals. These small ion dopants can alter the fundamental physical and chemical properties of ice, such as its structure and electrical conductivity. Therefore, these results could have a direct impact on the chemical reactivity of ice and ice surfaces. Here, we examine the influence of the uptake of three salts—ammonium chloride (NH₄Cl), sodium chloride (NaCl), and ammonium sulfate [(NH₄)₂SO₄]—on ice Ih formation using capillary electrophoresis. Using both cation and anion modes, we observed …

Managing Cyber Defense As A Business Threat For Small And Medium Enterprises, Binh Quang Vo

Doctoral Dissertations and Projects

The U.S small and medium businesses (SMBs) are constantly attacked by cybercriminals. Alarmingly, the number of victimized SMBs is growing considerably every year. This results in the increasing loss of billions of dollars and risks to the national economy. The problem addressed was the rising number of cyberattacks critically harming SMBs resulting in revenue loss, damages to reputation, and business closure. The purpose of this research was to reveal the contemporary barriers and challenges that impact cybersecurity competencies of SMBs. This study used semi-structured interviews of participants who are currently working as cyber professionals in SMBs across industries. The goal …

Metric Ensembles Aid In Explainability: A Case Study With Wikipedia Data, Grant Forbes, R. Jordan Crouser

Computer Science: Faculty Publications

In recent years, as machine learning models have become larger and more complex, it has become both more difficult and more important to be able to explain and interpret the results of those models, both to prevent model errors and to inspire confidence for end users of the model. As such, there has been a significant and growing interest in explainability in recent years as a highly desirable trait for a model to have. Similarly, there has been much recent attention on ensemble methods, which aim to aggregate results from multiple (often simple) models or metrics in order to outperform …

Language Modeling Using Image Representations Of Natural Language, Seong Eun Cho

Theses and Dissertations

This thesis presents training of an end-to-end autoencoder model using the transformer, with an encoder that can encode sentences into fixed-length latent vectors and a decoder that can reconstruct the sentences using image representations. Encoding and decoding sentences to and from these image representations are central to the model design. This method allows new sentences to be generated by traversing the Euclidean space, which makes vector arithmetic possible using sentences. Machines excel in dealing with concrete numbers and calculations, but do not possess an innate infrastructure designed to help them understand abstract concepts like natural language. In order for a …

Convolutional Neural Networks Analysis Reveals Three Possible Sources Of Bronze Age Writings Between Greece And India, Shruti Daggumati, Peter Z. Revesz

School of Computing: Faculty Publications

This paper analyzes the relationships among eight ancient scripts from between Greece and India. We used convolutional neural networks combined with support vector machines to give a numerical rating of the similarity between pairs of signs (one sign from each of two different scripts). Two scripts that had a one-to-one matching of their signs were determined to be related. The result of the analysis is the finding of the following three groups, which are listed in chronological order: (1) Sumerian pictograms, the Indus Valley script, and the proto-Elamite script; (2) Cretan hieroglyphs and Linear B; and (3) the Phoenician, Greek, …

Unraveling The Nature Of Nano‑Diamonds And Silica In A Catheterized Tapered Artery: Highlights Into Hydrophilic Traits, Sara I. Abdelsalam, M.M. Bhatti

Basic Science Engineering

No abstract provided.

Effectiveness Of Water Hyacinth Compost And N, P, K, S Fertilizer On S-Available, S Uptake, Protein Content, And Yield Of Shallot In Inceptisols From Jatinangor, Emma Trinurani Sofyan, Fajar Akbar Gumelar, Anni Yuniarti, Benny Joy, Fiky Yulianto Wicaksono

Jurnal Kultivasi

. Water hyacinth (Eichhornia crassipes) is a source of organic matter that can be used as compost to improve the soil quality and productivity of shallots. Shallots are horticultural commodities that have various benefits. Inceptisol soils dominate Indonesia, with an area of 37.5% of Indonesia's land area but have low soil fertility. Soil fertility can be increased by optimal fertilization. This experiment aimed to determine the dose of water hyacinth compost and nitrogen (N), phosphor (P), potassium (K), sulfur (S) fertilizer which gave the best effect on increasing available S, S uptake, protein content, and yield of shallots. The experiment …