Physical Sciences and Mathematics Commons^™

Substitution Tilings With Transcendental Inflation Factor, Dirk Frettlöh, Alexey Garber, Neil Mañibo

School of Mathematical & Statistical Sciences Faculty Publications

For any λ>2, we construct a substitution on an infinite alphabet which gives rise to a substitution tiling with inflation factor λ. In particular, we obtain the first class of examples of substitutive systems with transcendental inflation factors. We also show that both the associated subshift and tiling dynamical systems are strictly ergodic, which is related to the quasicompactness of the underlying substitution operator.

Pedagogical Moves Related To Analogy That Support A Unified Understanding Of Eigentheory Concepts In A Quantum Mechanics Class, Kaitlyn Stephens Serbin, Megan Wawro

School of Mathematical & Statistical Sciences Faculty Publications

It is beneficial for quantum mechanics students to have a unified understanding of eigentheory concepts, so they can recognize the shared structure of mathematized phenomena from the different quantum mechanical systems of spin, energy, or position and recognize those as instantiations of the same overarching concept. Quantum mechanics instructors should, therefore, provide opportunities for their class community to develop a shared unified understanding of eigentheory concepts. One such opportunity can arise by engaging students in analogizing eigentheory concepts in one context with those from another context. We investigate the pedagogical moves related to analogies that can be used by a …

Evaluating Indoor Air Quality In Residential Environments: A Study Of Pm2.5 And Co2 Dynamics Using Low-Cost Sensors, Kabir Bahadur Shah, Dylan Kim, Sai Deepak Pinakana, Mkhitar A. Hobosyan, Armando Montes, Amit U. Raysoni

School of Earth, Environmental, & Marine Sciences Faculty Publications

Indoor air quality (IAQ) poses a significant public health concern, and exposures to high levels of fine particulate matter (PM2.5) and carbon dioxide (CO2) could have detrimental health impacts. This study focused on assessing the indoor air pollutants in a residential house located in the town of Mission, Hidalgo County, South Texas, USA. The PM2.5 and CO2 were monitored indoors: the kitchen and the bedroom. This investigation also aimed to elucidate the effects of household activities such as cooking and human occupancy on these pollutants. Low-cost sensors (LCSs) from TSI AirAssure™ were used in this study. They were deployed within …

Factors Influencing The Faunal Recolonization Of Restored Thornscrub Forest Habitats, Audrey J. Hicks, Jerald T. Garrett, Christopher A. Gabler

School of Earth, Environmental, & Marine Sciences Faculty Publications

Tamaulipan thornscrub forests (thornforests) have high ecological and economic values, yet over 90% of these forests have been lost, and they remain threatened, making them a conservation hotspot. For decades, federal, state, NGO, and corporate entities have been acquiring land and actively or passively restoring these forests, but results have been mixed and seldom monitored. This study characterized and quantified faunal communities of restored thornforest habitats in south Texas and examined the relationships between restored faunal communities and key site characteristics and environmental factors. We surveyed and analyzed mammal, bird, Lepidoptera, and herptile communities within 12 restored sites in the …

Integrable Semi-Discretization For A Modified Camassa-Holm Equation With Cubic Nonlinearity, Bao-Feng Feng, Heng-Chun Hu, Han-Han Sheng, Wei Yin, Guo-Fu Yu

School of Mathematical & Statistical Sciences Faculty Publications

In the present paper, an integrable semi-discretization of the modified Camassa-Holm (mCH) equation with cubic nonlinearity is presented. The key points of the construction are based on the discrete Kadomtsev-Petviashvili (KP) equation and appropriate definition of discrete reciprocal transformations. First, we demonstrate that these bilinear equations and their determinant solutions can be derived from the discrete KP equation through Miwa transformation and some reductions. Then, by scrutinizing the reduction process, we obtain a set of semi-discrete bilinear equations and their general soliton solutions in the Gram-type determinant form. Finally, we obtain an integrable semi-discrete analog of the mCH equation by …

Data Quality Based Intelligent Instrument Selection With Security Integration, Sergei Chuprov, Raman Zatsarenko, Leon Reznik, Igor Khokhlov

Computer Science Faculty Publications

We propose a novel Data Quality with Security (DQS) integrated instrumentation selection approach that facilitates aggregation of multi-modal data from heterogeneous sources. As our major contribution, we develop a framework that incorporates multiple levels of integration in finding the best DQS-based instrument selection: data fusion from multi-modal sensors embedded into heterogeneous platforms, using multiple quality and security metrics and knowledge integration. Our design addresses the security aspect in the instrumentation design, which is commonly overlooked in real applications, by aggregating it with other metrics into an integral DQS calculus. We develop DQS calculus that formalizes the problem of finding the …

Stability Of Optimal Spherical Codes, Károly J. Böröczky, Alexey Glazyrin

School of Mathematical & Statistical Sciences Faculty Publications

For many extremal configurations of points on a sphere, the linear programming approach can be used to show their optimality. In this paper we establish the general framework for showing stability of such configurations and use this framework to prove the stability of the two spherical codes formed by minimal vectors of the lattice E8 and of the Leech lattice.

Further Results On Vanishing Coefficients In The Series Expansion Of Lacunary Eta Quotients, Timothy Huber, James Mclaughlin, Dongxi Ye

School of Mathematical & Statistical Sciences Faculty Publications

In a previous paper the authors proved the existence of various pairs\break (A(q),B(q)) of lacunary eta quotients with identically vanishing coefficients. Further experiments indicated that the results in this previous paper were just the "tip of the iceberg". We provide a comprehensive description of what experiment suggests and employ a variety of methods to prove experimentally-derived results. The work is a template and atlas for the subsequent study of lacunary eta quotients. A broad range of proof strategies are applied to confirm the vanishing structure. These comprise a representative sample of techniques that may be used to study the remaining …

Interpretable Spatio-Temporal Embedding For Brain Structural-Effective Network With Ordinary Differential Equation, Haoteng Tang, Guodong Liu, Siyuan Dai, Kai Ye, Kun Zhao, Wenlu Wang, Carl Yang, Lifang He, Alex D. Leow, Paul Thompson

Computer Science Faculty Publications

The MRI-derived brain network serves as a pivotal instrument in elucidating both the structural and functional aspects of the brain, encompassing the ramifications of diseases and developmental processes. However, prevailing methodologies, often focusing on synchronous BOLD signals from functional MRI (fMRI), may not capture directional influences among brain regions and rarely tackle temporal functional dynamics. In this study, we first construct the brain-effective network via the dynamic causal model. Subsequently, we introduce an interpretable graph learning framework termed Spatio-Temporal Embedding ODE (STE-ODE). This framework incorporates specifically designed directed node embedding layers, aiming at capturing the dynamic inter-play between structural and …

A Multivariate Approach To Assessing Landscape Structure Effects On Wildlife Crossing Structure Use, Thomas J. Yamashita, Humberto L. Perotto-Baldivieso, David B. Wester, Kevin W. Ryer, Richard J. Kline, Michael E. Tewes, John H. Young Jr., Jason V. Lombardi

School of Earth, Environmental, & Marine Sciences Faculty Publications

Background

Complexity in landscape structure is often assessed using individual metrics related to ecological processes. However, this rarely incorporates important relationships among metrics and may miss landscape structure effects. Multivariate statistics provide techniques for assessing overall landscape structure effects. We assessed how multivariate statistics could be used to connect landscape structure with an ecological process [bobcat (Lynx rufus) wildlife crossing structure (WCS) use]. We tested how landscape structure at WCS sites compared to the surrounding landscape and how structure affected detections at WCS sites. Our study was conducted in Cameron County, Texas, USA where WCSs are in various …

Local Environmental Organizations And Long-Term Investor Value Appropriation, Chune Young Chung, Gia Han Doan, Kainan Wang

Finance Faculty Publications

Highlights

• We explore how external and internal firm factors influence the impact of local activism.
• Our results indicate a positive effect of local activism on LIVA.
• Firms tend to increase their environmental disclosures in response to local activism.
• Local activism effects are greater when long-term value is prioritized.
• The findings support the social movement theory.

Abstract

This study uses datasets representing local non-governmental organizations (NGOs) to examine how local environmental organizations enhance long-term investor value appropriation (LIVA). We explore how external and internal firm factors influence the impact of local activism. Our results indicate a positive effect of local activism …

Stable Isotope Analysis Of Antipatharian Diets From The Northwestern Gulf Of Mexico, Keir J. Macartney, Victoria Salinas, Zachary Rivera, David Hicks

School of Earth, Environmental, & Marine Sciences Faculty Publications

Antipatharians, or black corals, form a key component of the benthic fauna found throughout the Gulf of Mexico (GOM). In the northwestern GOM, they are a common member of the communities found on the natural relic coral—algal banks known as the South Texas Banks as well as on artificial reefs. They are known to provide important habitat for many ecologically and economically important species in the area but are relatively understudied. Here we present a study on their trophic ecology using stable isotope analysis of carbon and nitrogen from 2 species, Antipathes atlantica and Stichopathes luetkeni from a mesophotic artificial …

Computational And Experimental Data For Undoped And Er-Doped Lithium Tantalate Nanofluorescent Probes, Mkhitar A. Hobosyan, Andrea Pelayo Carvajal, Bhupendra B. Srivastava, Tamanna Zakia, Mohammed Jasim Uddin, Karen S. Martirosyan, Eric Rodriguez, Kofi Nketia Ackaah-Gyasi, Nicholas Dimakis

Physics & Astronomy Faculty Publications

The density functional theory (DFT) and experimental data presented in this paper refer to the research article “Computational and experimental study on undoped and Er-doped lithium tantalate nano fluorescent probes”. The DFT data contain electronic and optical properties for both LiTaO3 and LiTaO3:Er+3, with Er+3 occupying either Li or Ta sites at 4.167 mol. %. All these properties were calculated at the generalized gradient approximation (GGA) limit. Additionally, electronic information was calculated using the hybrid functional by Heyd, Scuseria, and Ernzerho (HSE06), which accurately predicts the location in energy for all Er-4f orbitals. We also include simulated X-ray near edge …

The P-Adic Schrödinger Equation And The Two-Slit Experiment In Quantum Mechanics, Wilson A. Zuniga-Galindo

School of Mathematical & Statistical Sciences Faculty Publications

p-Adic quantum mechanics is constructed from the Dirac-von Neumann axioms identifying quantum states with square-integrable functions on the N-dimensional p-adic space, Q_{p}^{N}. This choice is equivalent to the hypothesis of the discreteness of the space. The time is assumed to be a real variable. p-Adic quantum mechanics is the response to the question: what happens with the standard quantum mechanics if the space has a discrete nature? The time evolution of a quantum state is controlled by a nonlocal Schrödinger equation obtained from a p-adic heat equation by a temporal Wick rotation. This p-adic heat equation describes a particle performing …

On Helly Numbers For Crystals And Cut-And-Project Sets, Alexey Garber

School of Mathematical & Statistical Sciences Faculty Publications

We prove existence of Helly numbers for crystals and for cut-and-project sets with convex windows. Also we show that for a two-dimensional crystal consisting of 𝑘 copies of a single lattice the Helly number does not exceed 𝑘 + 6.

Testing The Reliability Of Chatgpt In Providing Spectral Information Of Organic Molecules, Ana Fraiman, Paola Barron, Brooke Dorsey, Sofia A. Delgado, Emanuel Sanchez

School of Mathematical & Statistical Sciences Faculty Publications

ChatGPT has emerged as a tool for predicting Hydrogen-1 Nuclear Magnetic Resonance (1HNMR), Infrared (IR), and Mass Spectrometry (MS) spectra. In order to rely on ChatGPT as a tool, a proof of concept for its application was essential. Having the ChatGPT outputs be validated by experimental data and databases (SDBS) has proven valuable for future uses. By inference, ChatGPT spectra output can be used to design problems without interference of copyright infringement of existing databases.

Search For Eccentric Black Hole Coalescences During The Third Observing Run Of Ligo And Virgo, A. G. Abac, R. Abbott, H. Abe, Teviet Creighton, Mario C. Diaz, Francisco Llamas Villarreal, Soma Mukherjee, Gaukhar Nurbek, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

Despite the growing number of binary black hole coalescences confidently observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include the effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that have already been identified with searches focusing on …

Quinoxaline 1,4-Di-N-Oxide Derivatives As New Antinocardial Agents, Isidro Palos, Alonzo Gonzalez-Gonzalez, Alma D. Paz-Gonzalez, José C. Espinoza-Hicks, Debasish Bandyopadhyay, Norma Paniagua-Castro, Marlene S. Galeana-Salazar, Jorge Ismael Castañeda-Sánchez, Julieta Luna-Herrera, Gildardo Rivera-Sanchez

School of Integrative Biological & Chemical Sciences Faculty Publications

Mycetoma is currently considered as a neglected tropical disease. The incidence of mycetoma is unknown but most of the worldwide cases are present in the “mycetoma belt” including countries like Mexico, India, Senegal, and others. The treatment of mycetoma depends on the etiological agent responsible for the case. Treatment success reaches 60 to 90%; however, common treatment has been reported to be ineffective in some cases, due in part to resistance to the prescribed antibiotics. Therefore, it is necessary to develop new therapeutic options. In the past two decades, quinoxaline derivatives have shown relevance as antibacterial agents. Therefore, in this …

A Garch-Midas Approach To Modelling Stock Returns, Ezekiel N.N. Nortey, Ruben Agbeli, Godwin Debrah, Theophilus Ansah-Narh, Edmund F. Agyemang

School of Mathematical & Statistical Sciences Faculty Publications

Measuring stock market volatility and its determinants is critical for stock market participants, as volatility spillover effects affect corporate performance. This study adopted a novel approach to analysing and implementing GARCH-MIDAS modelling methods. The classical GARCH as a benchmark and the univariate GARCH-MIDAS framework are the GARCH family models whose forecasting outcomes are examined. The outcome of GARCH-MIDAS analyses suggests that inflation, interest rate, exchange rate, and oil price are significant determinants of the volatility of the Johannesburg Stock Market All Share Index. While for Nigeria, the volatility reacts significantly to the exchange rate and oil price. Furthermore, inflation, exchange …

Predicting Students' Academic Performance Via Machine Learning Algorithms: An Empirical Review And Practical Application, Edmund F. Agyemang, Joseph A. Mensah, Obu-Amoah Ampomah, Louis Agyekum, Justice Akuoko-Frimpong, Amma Quansah, Oluwaferanmi M. Akinlosotu

School of Mathematical & Statistical Sciences Faculty Publications

Predicting academic outcomes is complex and influenced by factors like socioeconomic background, motivation, and learning style. Machine Learning (ML) algorithms have become increasingly important due to their ability to analyze large data volumes and identify prediction patterns. Results show ML’s success in predicting academic performance, though effectiveness varies by dataset, algorithm choice, and training features. There is no consensus on the most effective ML method for predicting student performance with broad applicability. Among the five algorithms evaluated in this study, the Random Forest Classifier emerged as the best model, achieving the highest G-Mean and accuracy of 0.9243 and 85.42% respectively. …

Collaborative Practices In Virtual Group Work On Dynamic Geometry Tasks, Younggon Bae, V. Rani Satyam, Zareen G. Aga

School of Mathematical & Statistical Sciences Faculty Publications

The goal of this study is to explore productive ways to engage students in groupwork using dynamic geometry tasks in online synchronous classroom environments. In particular, we aim to understand the social, mathematical, and technological aspects of student collaboration in virtual spaces. We analyzed how three online groups of students collaboratively worked on dynamic geometry tasks of exploring interactive kaleidoscope applets in Desmos and producing visual representations and written descriptions of geometric transformations used in the applets. The students shared their screens in Zoom as they shared their findings and discussed how to draw and write to represent the kaleidoscopes. …

The First Joint Observation By Kagra With Geo 600, N. Uchikata, R. Abbott, H. Abe, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Gaukhar Nurbek, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

KAGRA conducted its first joint observation with GEO 600 for two weeks in April, 2020. We performed two types of all-sky searches and two searches dedicated to gravitational wave signals associated with gamma-ray burst events observed during the run. We did not detect any gravitational wave signals, which was expected given the sensitivity of both detectors at that time. However, we did confirm that several search pipelines used in the LIGO-Virgo-KAGRA collaborations worked effectively on the KAGRA data. In this presentation we will report on the data quality of detectors and the search results.

A Call For Better Understanding Household Complexity In Environmental Social Science, Rebecca Nixon, Brooke Mcwherter, Anna Erwin, Jonathan Bauchet, Zhao Ma

School of Earth, Environmental, & Marine Sciences Faculty Publications

No abstract provided.

Search For Core Collapse Supernovae Signals In Ligo’S Third Observation Run Using A Network Of Gravitational Wave Detectors Integrated With A Multiclass Convolutional Neural Network, Shahrear Khan Faisal, Gaukhar Nurbek, Michael Benjamin, Bhawana Sedhai, Soma Mukherjee

Physics & Astronomy Faculty Publications

In the existing body of literature, numerous waveforms of core collapse supernovae (CCSN) have emerged from extensive simulations conducted in high-performance computing facilities globally. These waveforms exhibit distinct characteristics related to their explosion mechanisms, influenced by parameters such as progenitor mass, angular momentum, gravitational wave energy, peak frequency, duration, and equation of state. Core collapse supernovae stand out as highly anticipated sources in LIGO’s fourth observation (O4) run, prompting dedicated efforts to detect them. The integration of machine learning, specifically convolutional neural networks (CNN), has become a pivotal avenue for analysis. This study addresses a fundamental query: how can a …

Hierarchical Neural Networks, P-Adic Pdes, And Applications To Image Processing, Wilson A. Zuniga-Galindo, B. A. Zambrano-Luna, Baboucarr Dibba

School of Mathematical & Statistical Sciences Faculty Publications

The first goal of this article is to introduce a new type of p-adic reaction–diffusion cellular neural network with delay. We study the stability of these networks and provide numerical simulations of their responses. The second goal is to provide a quick review of the state of the art of p-adic cellular neural networks and their applications to image processing.

A Correspondence Between Deep Boltzmann Machines And P-Adic Statistical Field Theories, Wilson A. Zuniga-Galindo

School of Mathematical & Statistical Sciences Faculty Publications

There is a strong interest in studying the correspondence between Euclidean quantum fields and neural networks. This correspondence takes different forms depending on the type of networks considered. In this work, we study this correspondence in the case of deep Boltzmann machines (DBMs) having a tree-like topology. We use p-adic numbers to encode this type of topology. A p-adic continuous DBM is a statistical field theory (SFT) defined by an energy functional on the space of square-integrable functions defined on a p-adic N-dimensional ball. The energy functionals are non-local, meaning they depend on the interaction of all the neurons forming …

Revolutionizing Medical Education: Harnessing Ai To Cultivate Critical Thinking Skills, Alex Zuo, Anthony L. Alanis

Research Colloquium

Our study intends to integrate AI-enabled tools in medical education, including but not limited to adaptive learning systems, virtual patients, and AI-enhanced assessment methods, to develop and foster critical thinking and problem-solving skills with the engagement of medical students. It is expected that this provides for a good environment for both teachers and students through workshops, online resources, and collaborative academic projects. We also consider AI-generated images and open educational resources that could augment curricula and personalize the experience for learners. Medical educators use storytelling, including AI for data storytelling, to package complex clinical data in approachable yet revealing ways …

Editorial: Critical Praxis And The Social Imaginary For Sustainable Food Systems, Max Stephenson Jr., Kim Niewolny, Laura Zanotti, Anna Erwin

School of Earth, Environmental, & Marine Sciences Faculty Publications

No abstract provided.

Domain-Based Nucleic-Acid Minimum Free Energy: Algorithmic Hardness And Parameterized Bounds, Erik D. Demaine, Elize Grizzell, Jayson Lynch, Ahmed Shalaby, Timothy Gomez, Markus Hecher, Robert Schweller, Damien Woods

Computer Science Faculty Publications

Molecular programmers and nanostructure engineers use domain-level design to abstract away messy DNA/RNA sequence, chemical and geometric details. Such domain-level abstractions are enforced by sequence design principles and provide a key principle that allows scaling up of complex multistranded DNA/RNA programs and structures. Determining the most favoured secondary structure, or Minimum Free Energy (MFE), of a set of strands, is typically studied at the sequence level but has seen limited domain-level work. We analyse the computational complexity of MFE for multistranded systems in a simple setting were we allow only 1 or 2 domains per strand. On the one hand, …

Learners’ Mathematics Identity And Achievement: Where Does The Teacher Come In?, Luis M. Fernandez, Ursula Nguyen, Rebecca Callahan

School of Mathematical & Statistical Sciences Faculty Publications

In response to recent interest in K-12th students’ mathematics identity formation and its implications for achievement, the present study examines the relationship between learners’ mathematics identity and student achievement while simultaneously accounting for teacher-enacted instructional practices in mathematics. Drawing from HSLS:2009, a nationally representative dataset of 9th–12th students within the United States, we use multiple linear regression analyses to examine how teachers’ mathematical pedagogies and 9th grade students’ perceptions of teacher equity are associated, first, with students’ mathematics identity, and, subsequently, math achievement after accounting for students’ mathematics identity. Ultimately, results from our models reveal a statistically significant relationship between …