Digital Commons Network^™

Search For Extreme Mass Ratio Inspirals Using Particle Swarm Optimization And Reduced Dimensionality Likelihoods, Xiao-Bo Zou, Soumya Mohanty, Hong-Gang Luo, Yu-Xiao Liu

Physics & Astronomy Faculty Publications

Extreme-mass-ratio inspirals (EMRIs) are significant observational targets for spaceborne gravitational wave detectors, namely, LISA, Taiji, and Tianqin, which involve the inspiral of stellar-mass compact objects into massive black holes (MBHs) with a mass range of approximately 104 ∼107��⊙ . EMRIs are estimated to produce long-lived gravitational wave signals with more than 105 cycles before plunge, making them an ideal laboratory for exploring the strong-gravity properties of the spacetimes around the MBHs, stellar dynamics in galactic nuclei, and properties of the MBHs itself. However, the complexity of the waveform model, which involves the superposition of multiple harmonics, as well as the …

Study Of Hybrid Nanofluid Flow In A Stationary Cone-Disk System With Temperature-Dependent Fluid Properties, A. S. John, Mahanthesh Basavarajappa, G. Lorenzini

School of Mathematical & Statistical Sciences Faculty Publications

Cone-disk systems find frequent use such as conical diffusers, medical devices, various rheometric, and viscosimetry applications. In this study, we investigate the three-dimensional flow of a water-based Ag-MgO hybrid nanofluid in a static cone-disk system while considering temperature-dependent fluid properties. How the variable fluid properties affect the dynamics and heat transfer features is studied by Reynolds’s linearized model for variable viscosity and Chiam’s model for variable thermal conductivity. The single-phase nanofluid model is utilized to describe convective heat transfer in hybrid nanofluids, incorporating the experimental data. This model is developed as a coupled system of convective-diffusion equations, encompassing the conservation …

Key Library Resources: Resources With Spanish Content, Raquel Estrada, William Flores

Library Display Posters

Collection of resources that contain spanish content. Also included are local collections found in ScholarWorks that contain spanish-only resources.

Proving Their Mettle: Managerial Ability And Firm Performance In Trying Times, Barry Hettler, James Cordeiro, Arno Forst

School of Accountancy Faculty Publications

This study investigates the impact of trying economic times, i.e., periods of economic decline and uncertainty, on managerial ability. We find that trying economic times positively moderate the association between managerial ability and firm profitability. Consistent with these primary findings, we also find that the positive moderating role of economic decline and uncertainty on the ability-performance relationship is most salient in procyclical industries. Our results are robust across multiple measures of economically trying times and managerial ability. Further analyses indicate that in trying times more capable managers generate stronger performance through both improved asset turnover and profit margins.

Utrgv Commencement – Spring 2024, The University Of Texas Rio Grande Valley

UTRGV Commencement Programs

No abstract provided.

Toward A Coordinated Understanding Of Hydro-Biogeochemical Root Functions In Tropical Forests For Application In Vegetation Models, Daniela F. Cusack, Bradley O. Christoffersen, Chris M. Smith-Martin, Kelly M. Andersen, Amanda L. Cordeiro, Katrin Fleischer, S. Joseph Wright, Nathaly R. Guerrero-Ramírez, Laynara F. Lugli, Lindsay A. Mcculloch

School of Integrative Biological & Chemical Sciences Faculty Publications

Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest–climate feedbacks for these carbon-rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics …

Reevaluating The Origin Of Detectable Cataclysmic Variables In Globular Clusters: Testing The Importance Of Dynamics, Liliana Rivera Sandoval, Diogo Belloni, Miriam Ramos Arevalo

Physics & Astronomy Faculty Publications

Based on the current detectable cataclysmic variable (CV) population in Galactic globular clusters (GCs), we show that there is not a clear relation between the number of sources per unit of mass and the stellar encounter rate, the cluster mass, or the cluster central density. If any, only in the case of core-collapsed GCs could there be an anticorrelation with the stellar encounter rate. Our findings contrast with previous studies where clear positive correlations were identified. Our results suggest that correlations between faint X-ray sources, from which often conclusions for the CV population are drawn, and the GC parameters considered …

The Eliahou-Kervaire Resolution Over A Skew Polynomial Ring, Luigi Ferraro, Alexis Hardesty

School of Mathematical & Statistical Sciences Faculty Publications

In a 1987 paper, Eliahou and Kervaire constructed a minimal resolution of a class of monomial ideals in a polynomial ring, called stable ideals. As a consequence of their construction they deduced several homological properties of stable ideals. Furthermore they showed that this resolution admits an associative, graded commutative product that satisfies the Leibniz rule. In this paper we show that their construction can be extended to stable ideals in skew polynomial rings. As a consequence we show that the homological properties of stable ideals proved by Eliahou and Kervaire hold also for stable ideals in skew polynomial rings.

Balancing Act: Insights Into Telangana Farmers’ Perspectives On Intensive Vs. Sustainable Agriculture, Srinivas Katherasala, Ram Shepherd Bheenaveni

School of Social Work Faculty Publications

High-input agriculture presents several drawbacks that can adversely affect both environmental sustainability and human health. A primary concern is soil degradation, which results from the excessive use of chemical fertilizers and pesticides. These substances can deplete soil nutrients, impair crop growth, and ultimately render the land barren and unproductive. This study, therefore, aims to explore the perceptions and practices of farmers in the Kumuram Bheem Asifabad district of Telangana State, India. The research involved a sample of 382 farmers across six mandals within this district. A stratified random sampling method was utilized within a survey-descriptive research framework. Data collection incorporated …

The Inextricability Of Students’ Mathematical And Physical Reasoning In Quantum Mechanics Problems, Kaitlyn Stephens Serbin, Megan Wawro

School of Mathematical & Statistical Sciences Faculty Publications

Reasoning with mathematics plays an important role in university students’ learning throughout their courses in the scientific disciplines, such as physics. In addition to understanding mathematical concepts and procedures, physics students often must mathematize physical constructs in terms of their associated mathematical structures and interpret mathematical entities in terms of the physical context. In this study, we investigate physics students’ reasoning about mathematics in relation to physics content addressed in two quantum mechanics problems. Through qualitative analysis of interview data from twelve students, results show that 1) students use intricate, nonuniform problem-solving methods with reasoning that moves fluidly between structural …

Normalized Ground State Of A Mixed Dispersion Nonlinear Schrodinger Equation With Combined Power-Type Nonlinearities, Zhouji Ma, Xiaojun Chang, Zhaosheng Feng

School of Mathematical & Statistical Sciences Faculty Publications

We study the existence of normalized ground state solutions to a mixed dispersion fourth-order nonlinear Schrodinger equation with combined power-type nonlinearities. By analyzing the subadditivity of the ground state energy with respect to the prescribed mass, we employ a constrained minimization method to establish the existence of ground state that corresponds to a local minimum of the associated functional. Under certain conditions, by studying the monotonicity of ground state energy as the mass varies, we apply the constrained minimization arguments on the Nehari-Pohozaev manifold to prove the existence of normalized ground state solutions.

Clinical Significance Of Targeting Ribosome Biogenesis In Pancreatic Cancer Therapy, Mudassier Ahmad, Sahir Sultan Alvi, Haider Ahsan, Carlos Perez, Muhammad Bangash, Andrew Massey, Emmanuel Anning, Aun A. Bangash, Manu Sebastian, Manish Tripathi, Dae Joon Kim, Subhash Chauhan, Bilal B. Hafeez

Research Symposium

Pancreatic cancer (PanCa) is the third leading cause of cancer-related deaths in the United States with limited therapeutic options available. Gemcitabine (GEM), a deoxycytidine nucleoside analog is currently considered the most effective therapy for PanCa. However, it shows only a marginal survival benefit of six months. Aberrant ribosome biogenesis occurs in most tumor types. We observed that PanCa cells are addicted to ribosome biogenesis (RiBi), which supports their highly aggressive metastatic phenotypes. Thus, strategically targeting RiBi process could be one of the ideal strategies for the prevention and treatment of PanCa. In this study, we elucidated the molecular mechanisms of …

A Joint Fermi-Gbm And Swift-Bat Analysis Of Gravitational-Wave Candidates From The Third Gravitational-Wave Observing Run, C. Fletcher, J. Wood, Michael G. Benjamin, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Gaukhar Nurbek, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational-wave (GW) candidate events identified during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Using Fermi-GBM onboard triggers and subthreshold gamma-ray burst (GRB) candidates found in the Fermi-GBM ground analyses, the Targeted Search and the Untargeted Search, we investigate whether there are any coincident GRBs associated with the GWs. We also search the Swift-BAT rate data around the GW times to determine whether a GRB counterpart is present. No counterparts are found. Using both the Fermi-GBM Targeted Search …

At-Risk Freshmen Student Retention After Stem Intervention, Edna Orozco, George Padilla

Organization and School Leadership Faculty Publications

Background: Science, Technology, Engineering, and Mathematics (STEM) areas are one of the fastest-growing majors in the nation. Engineering is projected to add the second largest number of new jobs from 2016 to 2026 with 140,000 new jobs (Torpey, 2018).According to the National Center for Education Statistics despite all the research done throughout decades to improve the issue of retention in STEM areas about half of the students who pursue a degree in STEM will either leave or change majors.

Purpose: This study aimed to sample at-risk college freshmen students from the College of Engineering & Computer Science, to describe and …

The Invariantring Package For Macaulay2, Luigi Ferraro, Federico Galetto, Francesca Gandini, Hang Huang, Matthew Mastroeni, Xianglong Ni

School of Mathematical & Statistical Sciences Faculty Publications

We describe a significant update to the existing InvariantRing package for Macaulay2. In addition to expanding and improving the methods of the existing package for actions of finite groups, the updated package adds functionality for computing invariants of diagonal actions of tori and finite abelian groups, as well as invariants of arbitrary linearly reductive group actions. The implementation of the package has been completely overhauled with the aim of serving as a unified resource for invariant theory computations in Macaulay2.

The Rider (2024-03-25), Natalie Lapsley

The Rider Archives

Vol.9 No.24

New Ways To Improve Dispersibility Of Nanotubes: Approaching From The Formation Of Silicon Nanoparticles By High Energy Reactive Ball Milling (Herbm) In Polar Solvents, Julie P. Vanegas, Yolanda V. Gutierrez, Joaquin Rivera, Juan García Jr.

Research Symposium

Background: This research aims to synthesize stable silicon nanoparticles using different molar ratios of N-Cyclohexyl-2-pyrrolidone (CHP) and Silicon to demonstrate if there is any significance towards the production of effective nanotubes. To determine this, the synthesized nanoparticles will be characterized by scanning electron microscopy (SEM), UV visible absorption spectroscopy, and photoluminescence spectroscopy (PL).

Methods: 50 Mg of silicon wafer are added with differing ratios of ligand (CHP), 5mL of water, and 3 steel iron balls into a ball milling vial. Vials are then placed into a ball milling apparatus for 7 cycles or 3.5 hours. Once the cycles are complete, …

Mechanistic Investigation Of C—C Bond Activation Of Phosphaalkynes With Pt(0) Complexes, Roberto M. Escobar, Abdurrahman C. Ateşin, Christian Müller, William D. Jones, Tülay Ateşin

Research Symposium

Carbon–carbon (C–C) bond activation has gained increased attention as a direct method for the synthesis of pharmaceuticals. Due to the thermodynamic stability and kinetic inaccessibility of the C–C bonds, however, activation of C–C bonds by homogeneous transition-metal catalysts under mild homogeneous conditions is still a challenge. Most of the systems in which the activation occurs either have aromatization or relief of ring strain as the primary driving force. The activation of unstrained C–C bonds of phosphaalkynes does not have this advantage. This study employs Density Functional Theory (DFT) calculations to elucidate Pt(0)-mediated C–CP bond activation mechanisms in phosphaalkynes. Investigating the …

La1-Xsrxcoo3 Perovskite Nanomaterial: Synthesis, Characterization, And Its Biomedical Application, Adhira Tippur, Anyet Shohag, Luke Franco, Ahmed Touhami, Swati Mohan, Mohammed Uddin

Research Symposium

Early cancer detection is paramount for effective treatment and potential cures. This research explores the application of perovskite materials, specifically Sr2+-doped Lanthanum Cobaltite (La1-xSrxCoO3) nanomaterials, in cancer detection, with a focus on rats as an experimental model. The ferroelectric nature of these materials, synthesized through a combination of sol-gel and molten-salt processes, was examined at varying Sr2+ doping levels (1-20 wt%). Rigorous characterization, employing X-ray diffraction and scanning electron microscopy, confirmed the uniform morphology of nano cubes, laying the foundation for subsequent investigations. The magnetic properties of the perovskite nanoparticles were probed, suggesting their potential as a diagnostic tool for …

Ex-Vivo Hippocampus Segmentation Using Diffusion-Weighted Mri, Haoteng Tang, Siyuan Dai, Eric M. Zou, Guodong Liu, Ryan Ahearn, Ryan Krafty, Michel Modo, Liang Zhan

Computer Science Faculty Publications

The hippocampus is a crucial brain structure involved in memory formation, spatial navigation, emotional regulation, and learning. An accurate MRI image segmentation of the human hippocampus plays an important role in multiple neuro-imaging research and clinical practice, such as diagnosing neurological diseases and guiding surgical interventions. While most hippocampus segmentation studies focus on using T1-weighted or T2-weighted MRI scans, we explore the use of diffusion-weighted MRI (dMRI), which offers unique insights into the microstructural properties of the hippocampus. Particularly, we utilize various anisotropy measures derived from diffusion MRI (dMRI), including fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, for …

Development Of An Experiential Learning Lab Activity On Skeletal Muscle Physiology In Undergraduate Md Pre-Clerkship Curriculum, Meyer B. Maddox, Angela Martinez, Daniel Salinas, Kelsey Potter-Baker, Amin Shah

Research Symposium

Background: Experiential learning is an important part of the medical education curriculum. Due to the clinical relevance of skeletal muscle strength in evaluating patients’ complaints of muscle weakness or imbalance, skeletal muscle physiology is an important concept with extensive potential for experiential learning opportunities. Our goal was to establish an experiential learning skeletal muscle physiology lab activity that would improve undergraduate MD pre-clerkship students’ skill to collect muscle force measurements using a hand-held dynamometer (HHD) and understanding of core physiological concepts.

Methods: As part of the Musculoskeletal and Dermatology (MSKD) Module in the undergraduate MD pre-clerkship curriculum, we developed a …

Contribution Of 24-H Blood Pressure Variability To Dementia-Related Disorders In Hispanics, Nura Salhadar, Kristina Vatcheva, Silvia Mejia-Arango Dr., Luis J. Mena, Ney Alliey-Rodriguez, Carlos A. Chavez, Ciro A. Goana, Egle Silva, Gustavo Calmon, Rosa P. Mavarez, Joseph H. Lee, Joseph D. Terwilliger, Jesus D. Melgarejo, Gladys E. Maestre

Research Symposium

Introduction: As the number of people living with dementia is increasing at alarming rates worldwide, there is an urgent need to understand the physiopathology of dementia syndromes. Among the most important preventable risk factors, treatment of vascular risk factors such as high blood pressure (BP) decreases the risk of Alzheimer’s disease and related dementias (ADRD). Recent evidence suggests that examining BP variability provides additional physiopathological and predictive information above the mean BP level. However, studies examining the relationship between 24-h BP variability and ADRD are limited, and evidence of the association with dementia has not been documented yet. Therefore, we …

Mind-Iot: Machine Intelligence And Data-Mining For Iot Threats, Kwabena Aboagye-Otchere, Jorge Castillo

Informatics and Engineering Systems Faculty Publications

The use of electric motors drive numerous industries via robust mechanical and electromechanical systems. However, their ubiquitous presence across the industry makes them potential targets for cyber-attackers, raising serious privacy concerns. Prior studies have demonstrated the feasibility of accurately fingerprinting various devices using electromagnetic signals. Yet, the specialized equipment required for those methods remain complex and expensive. This study presents MIND-IoT, a novel approach that captures and analyzes the unintended magnetic emissions surrounding electric motors. Our method achieves precise fingerprinting of motors, and determines their operational parameters by leveraging low-cost IoT devices. By focusing solely on magnetic fields, MIND-IoT offers …

A Science Teacher’S Experiences When Fostering Intercultural Competence Among Students In Multilingual Classrooms: A Narrative Study, Uma Ganesan, Amanda R. Morales

Teaching and Learning Faculty Publications

Increased globalization of the world economy, growth in human migration, and rapid devel-opments in science and technology have required people to develop intercultural commu-nication skills. Teachers play a crucial role in developing intercultural competence among students in our globalized, multilingual classrooms. The need for fostering collaborative discourse among students with diverse cultural and linguistic repertoires and building in-tercultural competence among students is a common blind spot in Science, Technology, Engineering, and Mathematics teacher praxis. This can inhibit efforts to cultivate safe and supportive learning environments for all students and can ultimately threaten multilingual student success. As part of a larger …

Regularization By Deep Learning In Signal Processing, Carlos Ramirez Villamarin, Erwin Suazo, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we explore a new idea of using deep learning representations as a principle for regularization in inverse problems for digital signal processing. Specifically, we consider the standard variational formulation, where a composite function encodes a fidelity term that quantifies the proximity of the candidate solution to the observations (under a physical process), and a second regularization term that constrains the space of solutions according to some prior knowledge. In this work, we investigate deep learning representations as a means of fulfilling the role of this second (regularization) term. Several numerical examples are presented for signal restoration under …

Spatial Distribution And Movement Of Atlantic Tarpon (Megalops Atlanticus) In The Northern Gulf Of Mexico, Shane A. Stephens, Michael A. Dance, Michelle Zapp Sluis, Richard J. Kline, Matthew K. Streich, Gregory R. Stunz, Aaron J. Adams, R. J. David Wells, Jay R. Rooker

School of Earth, Environmental, & Marine Sciences Faculty Publications

Atlantic tarpon (Megalops atlanticus) are capable of long-distance migrations (hundreds of kilometers) but also exhibit resident behaviors in estuarine and coastal habitats. The aim of this study was to characterize the spatial distribution of juvenile tarpon and identify migration pathways of adult tarpon in the northern Gulf of Mexico. Spatial distribution of juvenile tarpon was investigated using gillnet data collected by Texas Parks and Wildlife Department (TPWD) over the past four decades. Generalized additive models (GAMs) indicated that salinity and water temperature played a significant role in tarpon presence, with tarpon occurrences peaking in the fall and increasing …

Assessing Gait Metrics For Early Parkinson's Disease Prediction: A Preliminary Analysis Of Underfit Models, Daniel Salinas, Gerardo Medellin, Katherine Bolado, Tomas Gomez, Kelsey Potter-Baker, Nawaz Khan Abdul Hack, Ramu Vadukapuram

Research Symposium

Background: Parkinson's Disease (PD) is characterized by both motor and non-motor symptoms, and its diagnosis primarily relies on clinical presentation. There is a growing need for diagnostic tools to identify the early signs of PD, particularly the initial motor impairments often manifested as gait abnormalities. Here we seek to present preliminary findings to address this need. Our study focuses on using Machine Learning techniques (ML) to predict the PD clinical stage most efficiently and accurately. Specifically, we have sought to evaluate how spatiotemporal characteristics and other locomotor performance variables obtained on a walkway system can be utilized to identify the …

Assessment Of Mucin 13 (Muc13) As An Imaging Target For Guiding Colorectal Cancer Treatment: A Pathway Towards Theranostic Development, Ryan P. Coll, Aiko Yamaguchi, Jianbo Wang, Xiaoxia Wen, Denise Hernandez, Subhash C. Chauhan, H. Charles Manning

Research Symposium

Background: A theranostic strategy combining diagnostic imaging and targeted therapy in a single regimen is proposed for improved management and treatment of colorectal cancer (CRC). Increased specificity in detection by the noninvasive imaging technique positron emission tomography (PET) can be achieved by radiolabeling antibodies (Abs) designed to target tumor-associated antigens with increased expression post-translational modifications present in cancer cells. In this study, an Ab designed to target the transmembrane glycoprotein mucin 13 (MUC13) was radiolabeled with the positron-emitting radionuclide zirconium-89 (⁸⁹Zr) for PET imaging of a xenograft mouse model of CRC. Specified uptake of this radioimmunoconjugate was observed …

Faculty Senate Minutes 2024-03-05, The University Of Texas Rio Grande Valley. Faculty Senate.

Faculty Senate Minutes

No abstract provided.

Alteration Of The Interferon Alpha Signaling Pathway Significantly Affects Alzheimer's Disease Pathology In App/Ps1 Mouse Model., Ranjit Kumar Das, Nirakar Sahoo, Chun Xu, Hansapani Rodrigo, Michael Paul Murphy, Upal Roy, Deepa Roy

Research Symposium

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive impairment, memory loss, and disturbances in behavior. The exact cause of the disease is unknown but there is evidence of molecular pathways alteration within the brain. Many molecular mechanisms have been studied for the progression of AD. Nonetheless, the contribution of the signal transducer and activator of transcription 1 (STAT1) and interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) genes have not been well established in AD pathology. This study aimed to investigate the contribution of STAT1 and IFIT3 in the BALB/C and APP/PS1 mouse models. We analyzed the STAT1 …