Physical Sciences and Mathematics Commons^™

Can Artificial Intelligence Models Provide Reliable Medical Counselling To Fertility Patients?, Idan Alcalay, Ariel Weissman, Hadas Ganer Herman, Avi Tsafrir, Matan Friedman, Eran Weiner, Raoul Orvieto, Nikolaos P. Polyzos, Michael H. Dahan, Alex Polyakov, Robert Fischer, Sandro C. Esteves, Baris Ata, Jason M. Franasiak, Yossi Mizrachi

Department of Obstetrics and Gynecology Faculty Papers

RESEARCH QUESTION: Can generative artificial intelligence (AI) models provide reliable counselling to fertility patients regarding real-world clinical questions?

DESIGN: In this cross-sectional study, 12 clinical questions were developed to reflect common, real-life dilemmas encountered during fertility workup and treatment. Responses to each question were generated by two experienced fertility specialists, and two AI models - ChatGPT and Gemini. Eight leading internationally recognized fertility experts, blinded to the source of each reply, independently rated all the responses on a scale from 1 (strongly disagree) to 10 (strongly agree). Ratings were compared across all four repliers using non-parametric statistical tests.

RESULTS: The …

Exploring Stunting In South Kalimantan Province Using R Programming-Based Data Visualization, Muhammad Hudaya, Wahyudin Nor, Mellani Yuliastina, Muhammad Nordiansyah

Kesmas

South Kalimantan Province continues to face the challenge of relatively high stunting prevalence despite being endowed with abundant coal resources that could serve as a source of funding for public health. Therefore, this study aimed to examine differences in stunting prevalence among cities, mining districts, and non-mining districts in South Kalimantan to raise stakeholder awareness of disparities across these regional types. This study was conducted between April and December 2024, using secondary data obtained from the Indonesian Ministry of Health and the South Kalimantan Provincial Government. R programming was used to process the data, generate visualizations, and perform analysis of …

Towards Age-Inclusive Human Computer Interaction: A Study Of Text Message Adoption By Seniors, Sam Takavarasha, Varaidzo Mapepa

African Conference on Information Systems and Technology

Since mobile phones are increasingly becoming livelihoods-enablers to people in developing economies, inclusive interaction design are critical. This research on the age inclusivity of feature phones was motivated by some observation that elderly users had challenges with adoption of text messaging. We, therefore, hypothesized that elderly people had challenges with texting ‘cash’, ‘cheque’ or ‘visa’ on a feature phone. The paper investigates if the required agility and interface ergonomics were age discriminatory inhibitors of the adoption of text messaging given the diminishing dexterity and cognitive skills of seniors. Using Sen’s (1999) ‘heterogeneity of capabilities’ theory and Davis et al (1989)’s …

Creepy, Invasive, And Exploitative Algorithms: A Cpm Analysis Of Users' Privacy Breakdowns And Recalibration Practices With Social Media Algorithms, Matthew J. A. Craig, Jeffrey T. Child

Human-Machine Communication

Social media content filtering algorithms can both provide desired personalized content and ads for users. However, sometimes these recommendations can resemble individual private information. How might users navigate these experiences to best manage their private information? The present exploratory study utilizes the rules- and systems-based framework of communication privacy management (CPM) theory to explore social media users’ experiences of privacy breakdowns with social media algorithms and investigates what users do in response to said breakdowns. These responses were refined using content analysis and divided into different categories of privacy breakdowns and recalibration strategies. Implications for future research surrounding human-machine communication …

Reconstruction Of Water Storage Variability In The Aral Sea Region, Nikita Murzintcev, Sahibjamal Nietullaeva, Timur Berdimbetov, Buddhi Pushpawela, Asiya Tureniyazova, Sherly Shelton, Bakbergen Aytmuratov, Khusen Gafforov, Kanat Parakhatov, Alimjan Erdashov, Abdul-Aziz Makhamatdinov, Timur Allamuratov

Plants, Soils and Climate Student Research

The Gravity Recovery and Climate Experiment (GRACE) mission, operational from 2002 to 2017, provided critical measurements of Earth's gravity field anomalies which have been extensively used to study groundwater and terrestrial water storage (TWS) dynamics. In this research, we utilize GRACE data to identify, model, and analyze potential climate parameters contributing to the reconstruction of TWS variability in the Aral Sea Basin region (ASB). We assess the impact of climate change and anthropogenic nature management on TWS change using a quantitative method. Our analysis reveals a significant decline in the TWS at a rate of 0.44 cm year^-1 during …

Spectrum Analysis Of Thermally Driven Curvature Inversion In Strained Graphene Ripples For Energy Conversion Applications Via Molecular Dynamics, James M. Mangum, Md R. Kabir, Tamzeed B. Amin, Syed M. Rahman, Ashaduzzaman, Paul M. Thibado

Physics Faculty Publications and Presentations

The extraordinary mechanical flexibility, high electrical conductivity, and nanoscale instability of freestanding graphene make it an excellent candidate for vibration energy harvesting. When freestanding graphene is stretched taut and subject to external forces, it will vibrate like a drum head. Its vibrations occur at a fundamental frequency along with higher-order harmonics. Alternatively, when freestanding graphene is compressed, it will arch slightly out of the plane or buckle under the load. Remaining flat under compression would be energetically too costly compared to simple bond rotations. Buckling up or down, also known as ripple formation, naturally creates a bistable situation. When the …

A Partial Resolution Of Hedden’S Conjecture On Satellite Homomorphisms, Randall Johanningsmeier , '24, Hillary Kim , '25, Allison N. Miller

Mathematics & Statistics Faculty Works

A pattern knot in a solid torus defines a self-map of the smooth knot concordance group. We prove that if the winding number of a pattern is even but not divisible by 8, then the corresponding map is not a homomorphism, thus partially establishing a conjecture of Hedden.

Sociohydrodynamics: Data-Driven Modeling Of Social Behavior, Daniel S. Seara, Jonathan Colen, Michel Fruchart, Yael Avni, David G. Martin, Vincenzo Vitelli

Data Science Faculty Publications

Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data are available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard …

Re: July 2025 Berkeley Pit Migratory Waterfowl Protection Monthly Report, Mark Thompson, Loren Burmeister

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Low Economic Level And The Risk Of Overweight Among Indonesian Junior And Senior High School Students, Ariyanto Nugroho, Purwo Setiyo Nugroho, Amarin Yudhana, Sri Sunarti

Kesmas

Overweight and obesity among Indonesian adolescents have emerged as a pressing public health issue, reflecting global trends. This study examines the relationship between economic status and overweight prevalence among junior and senior high school students in Indonesia, using secondary data from the Global School-based Health Survey (GSHS). This study analyzed data from 9,977 students aged 11–18 years through a cross-sectional design and binary logistic regression, adjusting for dietary habits, physical activity, and sedentary behavior. Overall, 14.7% of students were overweight; the prevalence was notably higher among low-income students (27.4%) compared to high-income groups (14.2%). Students from lower economic backgrounds were …

Understanding User Needs In Health Crisis Risk Monitoring Information System Development: A Lesson From Tasikmalaya District, Indonesia, Arief Tarmansyah Iman, Hari Kusnanto, Ariani Arista Putri Pertiwi

Kesmas

A health crisis risk monitoring information system needs to be developed, especially during the pre-disaster phase; therefore, understanding the needs of prospective users is crucial. This study aimed to investigate the needs of potential users regarding the development of this system. This study employed a qualitative, exploratory approach to gather user needs from stakeholders through interviews (n = 7) and one focus group discussion (n = 12). The data were audio-recorded, transcribed verbatim, and then thematically analyzed using qualitative content analysis. The need for information was related to disaster preparedness and its preferred format. The system should be targeted, multiplatform, …

Molecular Dynamics Simulations Of Liposomes: Structure, Dynamics, And Applications, Ehsan Khodadadi, Ehsaneh Khodadadi, Parth Chaturvedi, Mahmoud Moradi

Chemistry & Biochemistry Faculty Publications and Presentations

Liposomes are nanoscale, spherical vesicles composed of phospholipid bilayers, typically ranging from 50 to 200 nm in diameter. Their unique ability to encapsulate both hydrophilic and hydrophobic molecules makes them powerful nanocarriers for drug delivery, diagnostics, and vaccine formulations. Several FDA-approved formulations such as Doxil (R) (Baxter Healthcare Corporation, Deerfield, IL, USA), AmBisome (R) (Gilead Sciences, Inc., Foster City, CA, USA), and Onivyde (R) (Ipsen Biopharmaceuticals, Inc., Basking Ridge, NJ, USA) highlight their clinical significance. This review provides a comprehensive synthesis of how molecular dynamics (MD) simulations, particularly coarse-grained (CG) and atomistic approaches, advance our understanding of liposomal membranes. We …

Prediction-Powered Inference For Clinical Trials: Application To Linear Covariate Adjustment, Pierre-Emmanuel Poulet, Maylis Tran, Sophie Tezenas Du Montcel, Bruno Dubois, Stanley Durrleman, Bruno M. Jedynak

Mathematics and Statistics Faculty Publications and Presentations

Prediction-powered inference (PPI) (Angelopoulos et al., Science 382(6671):669-674, 2023) and its subsequent development called PPI++ (Angelopoulos et al., 2023) provide a novel approach to standard statistical estimation, leveraging machine learning systems, to enhance unlabeled data with predictions. We use this paradigm in clinical trials. The predictions are provided by disease progression models, providing prognostic scores for all the participants as a function of baseline covariates. The proposed method would empower clinical trials by providing untreated digital twins of the treated patients while remaining statistically valid. The potential implications of this new estimator of the treatment effect in a two-arm randomized …

Hurricane Katrina Archive: E-Books And E-Journals A To Z Bibliography 2020-2025, Lsu Health Sciences Center - New Orleans Libraries, Elizabeth H. Holt

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 43 electronic books and edited collections created on the topic of Hurricane Katrina by authors and others affiliated with LSU Health Sciences Center - New Orleans between September 2005 and August 2025.

Hurricane Katrina Archive: Faculty Publications Bibliography 2020-2025, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 10 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2020 and August 2025.

Hurricane Katrina Archive: Faculty Publications Bibliography 2015-2019, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 19 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2015 and December 2019.

Hurricane Katrina Archive: Libraries Catalog Bibliography, Lsu Health Sciences Center - New Orleans Libraries, Elizabeth H. Holt

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 15 books, videos, and edited collections created on the topic of Hurricane Katrina by authors and others affiliated with LSU Health Sciences Center - New Orleans between September 2005 and August 2025.

Hurricane Katrina Archive: Faculty Publications Bibliography 2010-2014, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 45 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2010 and December 2014.

Hurricane Katrina Archive: Faculty Publications Bibliography 2005-2009, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 91 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2005 and December 2009.

Approximation And Parameterized Algorithms For Covering With Disks Of Two Types Of Radii, Sayan Bandyapadhyay, Eli Mitchell

Computer Science Faculty Publications and Presentations

We study the Discrete Covering with Two Types of Radii problem motivated by its application in wireless networks. In this problem, the goal is to assign either small-range high frequency or large-range low frequency to each access point, maximizing the number of users in high-frequency regions while ensuring that each user is in the range of an access point. Unlike other weighted covering problems, our problem requires satisfying two simultaneous objectives, which calls for novel approaches that leverage the underlying geometry of the problem. In our work, we present two new algorithms: the first is a polynomial-time (2.5 + ϵ)-approximation, …

Enhancing Reliable And Energy-Efficient Uav Communications With Ris And Deep Reinforcement Learning, Wasim Ahmad, Umar Islam, Abdulkadhem A. Abdulkadhem, Babar Shah, Fernando Moreira, Ali Abbas

All Works

The rapid growth in wireless communication demands has led to a surge in research on technologies capable of enhancing communication reliability, coverage, and energy efficiency. Among these, uncrewed aerial vehicles (UAV) and reconfigurable intelligent surfaces (RIS) have emerged as promising solutions. Prior research on using deep reinforcement learning (DRL) to integrate RIS with UAV concentrated on enhancing signal quality and coverage, but it ignored the challenges caused by electromagnetic interference (EMI). This article introduces a novel framework addressing the challenges posed by EMI from Gallium nitride (GaN) power amplifiers in RIS-assisted UAV communication systems. By integrating DRL with quadrature phase …

Ddos Attack Detection In Edge-Iiot Digital Twin Environment Using Deep Learning Approach, Feras Al-Obeidat, Adnan Amin, Ahmed Shuhaiber, Inam Ul Haq

All Works

The industrial Internet of Things (IIoT) and digital twins are redefining how digital models and physical systems interact. IIoT connects physical intelligence, and digital twins virtually represent their physical counterparts. With the rapid growth of Edge-IIoT, it is crucial to create security and privacy regulations to prevent vulnerabilities and threats (i.e., distributed denial of service (DDoS)). DDoS attacks use botnets to overload the target system with requests. In this study, we introduce a novel approach for detecting DDoS attacks in an Edge-IIoT digital twin-based generated dataset. The proposed approach is designed to retain already learned knowledge and easily adapt to …

Symmetrically Threaded Superconducting Quantum Interference Devices As Next-Generation Kerr-Cat Qubits, Bibek Bhandari, Irwin Huang, Ahmed Hajr, Kagan Yanik, Bingcheng Qing, Ke Wang, David I. Santiago, Justin Dressel, Irfan Siddiqi, Andrew N. Jordan

Mathematics, Physics, and Computer Science Faculty Articles and Research

Kerr-cat qubits are bosonic qubits offering autonomous bit-flip protection, traditionally studied using driven superconducting nonlinear asymmetric inductive element (SNAIL) oscillators. Here, we theoretically explore an alternative circuit for Kerr-cat qubits based on symmetrically threaded superconducting quantum interference devices (SQUIDs). The symmetrically threaded SQUID (STS) architecture employs a simplified flux-pumped design that suppresses two-photon dissipation, a dominant loss mechanism in high-Kerr regimes, by engineering the drive Hamiltonian’s flux operator to generate only even-order harmonics. By fulfilling two critical criteria for practical Kerr-cat qubit operation, the STS emerges as an ideal platform: (1) a static Hamiltonian with diluted Kerr nonlinearity (achieved via …

A Dual-Model Machine Learning Framework For Predictive Maintenance Of Industrial Digital Press Components, Richmond Darko, Emmanuel Adabor

African Conference on Information Systems and Technology

This study presents a novel dual-model predictive maintenance framework designed to improve maintenance scheduling for components in industrial digital presses. The framework integrates two complementary approaches: a Threshold-Based Maintenance Approach (TBMA) for components operating within acceptable usage limits, and an Overdue Severity-Based Maintenance Approach (OSBMA) for those that have exceeded their expected lifespans or show signs of critical degradation. This study uses real-world operational data from a Konica Minolta C6000 press. It applies advanced machine learning models, including Gradient Boosting Machines and Random Forest for classification, and Generalized Additive Models (GAM) for Remaining Useful Life (RUL) prediction. The goal is …

The Integration Of Agile Methodologies In Devops Practices Within The Information Technology Industry, Ashley Hourigan, Ridewaan Hanslo

African Conference on Information Systems and Technology

The demand for rapid software delivery in the Information Technology (IT) industry has significantly intensified, emphasising the need for faster software products and service releases with enhanced features to meet customer expectations. Agile methodologies are replacing traditional approaches such as Waterfall, where flexibility, iterative development and adaptation to change are favoured over rigid planning and execution. DevOps, a subsequent evolution from Agile, emphasises collaborative efforts in development and operations teams, focusing on continuous integration and deployment to deliver resilient and high-quality software products and services. This study aims to critically assess both Agile and DevOps practices in the IT industry …

Mapping Food Justice: Urban Farms And The Examination Of Equitable Food Access, Aaron Avila, Mark Ayiah, Jake Stavely, Marc T. Sager, Maximilian K. Sherard, Anthony J. Petrosino

SMU Journal of Undergraduate Research

In this project, we worked alongside members from an urban farm in South Dallas to learn about issues related to food justice, urban farming, and food deserts. Using participatory design research methods, we created data visualizations showing how society can reduce inequities relating to food access produced in historically underserved neighborhoods. The research goals guiding this study are: a) to identify food deserts and urban farms in the Dallas-Fort Worth metropolitan region (DFW) and b) to determine which urban farms service the needs of these food deserts. To identify food deserts, we took two steps: First, we used open-access data …

A Modern Analytical Method To Forecast Cerebrovascular Diseases (Cd), And Heart Diseases (Hd) Using Multivariate Time Series Model Utilizing The Cdc Provisional Mortality Data, Aditya Chakraborty, Mohan Pant

Cardiovascular Research Symposium

Background: In this study, a new analytical approach was introduced to answer specific questions related to mortalities due to cerebrovascular diseases, heart diseases, and the association of these mortalities with twelve other causes of death (COD).

Methods: A multivariate time series forecasting model was developed utilizing each of the CODs by taking the weekly and yearly seasonality into account, and the mortality counts were forecasted using the most recent CDC weekly mortality count data. A new COD data matrix was structured for all CODs as a function of weeks by combining the observed and predicted values of the mortality counts. …

Cybersecurity And Intention To Use Mobile Banking Applications, Ishmael Chikoo, Salah Kabanda

African Conference on Information Systems and Technology

The adoption rate of mobile banking amongst consumers remains low, especially in developing countries where there is a knowledge gap in understanding why consumers do not engage in the frequent use of mobile banking applications. Given that most financial institutions see mobile banking as a strategy for their competitive advantage; it is important that they understand how best to address consumer’s fears brought about by cybersecurity threats. The purpose of this study is to investigate the perceived influence of cybersecurity on the user’s intentions to use mobile banking applications. Data collected from 90 participants was statistically analysed in Smart PLS …

Corrigendum To "Face-Magic Labelings Of Polygonal Graphs", Wai Chee Shiu, Richard M. Low, Andy K. Liu

Theory & Applications of Graphs

In this note, we correct a misstatement of a theorem.

2025 August 28 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.