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Melanaphis Sacchari/Sorghi Complex: Current Status, Challenges And Integrated Strategies For Managing The Invasive Sap-Feeding Insect Pest Of Sorghum, Alejandro Vasquez, Joseph Belsky, Neetu Khanal, Heena Puri, Devi Balakrishnan, Neelendra K. Joshi, Joe Louis, Glenn Studebaker, Rupesh Kariyat

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Biology)

Melanaphis sacchari (Zehntner;Hemiptera: Aphididae), sugarcane aphid (SCA), is an invasive phloem-feeder found worldwide with a wide host range of economically important plants including sorghum and sugarcane. Given its high reproductive capacity and ability to rapidly spread over long distances, SCA presents challenges for effective control, leading to substantial economic losses. Recent studies have identified two multiloci SCA genotypes specialized in feeding on sugarcane (MLL-D) and sorghum (MLL-F) in the USA, which raises concerns as the USA is the second largest sorghum-producing country. This has encouraged research towards identifying these two biotypes where some research has stated them as two species; …

Microplastics In Coastal And Marine Environments: A Critical Issue Of Plastic Pollution On Marine Organisms, Seafood Contaminations, And Human Health Implications, Rebecca Muñiz, Md. Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Plastic has quickly become one of the world's most prevalent environmental pollutants. Population growth has only amplified the demand, resulting in 430 million tons of plastic produced annually, with 11 million tons ending up in our oceans. Without intentional intervention, plastic waste in the oceans is expected to triple, posing severe risks for the aquatic ecosystems, animals, and humans dependent on these waters. As plastic accumulates in oceans and other water environments, the non-biodegradable particles break down into micro- and nano-plastics, invading coastal and marine organisms and causing considerable physiological and morphological damage. This is especially concerning for the millions …

Relaxation Maximum-Based Iteration Method For Solving The Generalized Absolute Value Equation, Ximing Fang, Zhidong Wang, Zhijun Qiao

School of Mathematical & Statistical Sciences Faculty Publications

The generalized absolute value equation (GAVE) has wide applications in scientific computing. Establishing a high performance computing method to solve the GAVE is a hot research topic in recent years. In this paper, with the aid of the maximum function, the GAVE is decomposed of two equations, and then we present the relaxation maximum-based (RM) iteration method. To see the feasibility of the method, we discuss the necessary and sufficient conditions for the GAVE to have a unique solution. Next, the convergence analysis of the RM iteration is discussed under some convergence conditions. Moreover, some numerical examples of low and …

The Improved New Intersection Theorem Revisited, Lars Winther, Luigi Ferraro

School of Mathematical & Statistical Sciences Faculty Publications

We prove a generalized version of Evans and Griffith’s improved new intersection theorem: Let I be an ideal in a local ring R. If a finite free R-complex, concentrated in nonnegative degrees, has I-torsion homology in positive degrees, and the homology in degree 0 has an I-torsion minimal generator, then the length of the complex is at least dimR−dimR/I. This improves the bound htI obtained by Avramov, Iyengar, and Neeman in 2018.

Effects Of Environmentally Relevant Concentrations Of Roundup On Oxidative-Nitrative Stress, Cellular Apoptosis, Prooxidant-Antioxidant Homeostasis, Renin And Cyp1a Expressions In Goldfish: Molecular Mechanisms Underlying Kidney Damage During Roundup Exposure, Md Imran Noor, Md Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Roundup is one of the most widely used glyphosate-based harmful herbicides in the United States as well as globally, which poses a severe risk for terrestrial and aquatic organisms. In order to identify the detrimental effects of Roundup exposure in aquatic organisms, we investigated the environmentally relevant concentrations of Roundup exposure (low dose: 0.5 μg/L and high dose: 5.0 μg/L for 2 weeks) on renin expression, oxidative-nitrative stress biomarkers (e.g., 2,4-dinitrophenol, DNP; and 3-nitrotyrosine protein, NTP), prooxidant-antioxidant enzymes expressions (e.g., superoxide dismutase, SOD; and catalase, CAT), cellular apoptosis, and cytochrome P450 1A (CYP1A) mRNA levels in the kidneys of goldfish …

Optimized Filtrations For Stormwater Quality Improvement By Porous Media–Biochar Applications: Column Experiments And Inverse Modeling, Sumiaya Amin Preota, Chu-Lin Cheng, Myung Hwangbo, Jongsun Kim

School of Earth, Environmental, & Marine Sciences Faculty Publications

Stormwater reuse plays a critical role under changing climates and increasing water demands. This study investigates the removal efficacy of lead (Pb2+) and ammonia (NH3) using sand and rice husk (RH) biochar for potential stormwater quality improvements and treatments. Column experiments combined with HYDRUS inverse modeling were conducted to optimize adsorption isotherms from breakthrough curves. Among linear and non-linear models, the Langmuir and Freundlich models performed better for sand and biochar, respectively. RH biochar showed much higher adsorption capacity of both Pb2+ (4.813 mg/g) and NH3 (6.188 mg/g). In contrast, sand showed a relatively limited adsorption capacity for Pb2+ (0.118 …

Exploring The “4-Trans” In Bi/Multilingual Teacher Education: Introduction To The Special Issue, Sandra I. Musanti, David Martinez-Prieto, Xiaodi Zhou

Bilingual and Literacy Studies Faculty Publications

In this introductory essay, the editors of the special issue on the 4-trans in bi/multilingual teacher education, highlight the contributions of one or more of the “4-trans” lenses—transnationalism, transculturalism, translanguaging, and transdisciplinarity—to explain, question, challenge, or propose new ways of understanding bi/multilingual teacher education. Eight articles that challenge monolithic perspectives of teacher education are presented.

Dialogic Foundations Of The “4-Trans” Framework: Towards A Comprehensive And Dynamic Understanding Of Multilingual Teacher Education, David Martinez-Prieto, Sandra I. Musanti, Xiaodi Zhou

Bilingual and Literacy Studies Faculty Publications

In this article, we develop the “4-trans” framework by reflecting on the way current multilingual teacher preparation scholarship has addressed translanguaging, transnationalism, transculturality, and transdisciplinarity either in compartmentalized or integrative manners. While current literature has addressed some “trans” intersections, we propose the enunciation of the “4-trans” as permeable and complementary principles in multilingual education that can serve to better examine the experiences and challenges of multilingual pre-service teachers. To amalgamate the “4-trans” to examine the development of multilingual pre-service teachers, this article describes the construction of a multidimensional framework based on a dialogic conception of social …

The Rider (2025-04-28), Rebeca Salinas

The Rider Archives

Vol. 10, No. 27

The Dialogue Dilemma: The Role Of Patient-Clinician Communication For Low-Income People Who Smoke And Manage Multiple Conditions, Monique T. Cano, Michael R. Lindstrom, Ricardo F. Muñoz

School of Mathematical & Statistical Sciences Faculty Publications

Introduction: Adults from low-income backgrounds who smoke face significant health disparities related to tobacco use, often at disproportionately high rates. These individuals are more likely to endure multiple mental and physical (MP) health conditions, which can negatively influence their self-rated health (SRH). The quality and effectiveness of patient-clinician communication (PCC) can influence how patients perceive their own health. Understanding how PCC influences SRH among low-income adults who smoke and suffer from multiple MP conditions is essential for clinical care as multimorbidity is on the rise. This study examines how PCC may influence the health perceptions of low-income adults who smoke …

Quantization For A Condensation System, Shivam Dubey, Mrinal Kanti Roychowdhury, Saurabh Verma

School of Mathematical & Statistical Sciences Faculty Publications

For a given r∈(0,+∞), the quantization dimension of order r, if it exists, denoted by Dr(μ), represents the rate at which the nth quantization error of order r approaches zero as the number of elements n in an optimal set of n-means for μ tends to infinity. If Dr(μ) does not exist, we define D−−r(μ) and ¯¯¯Dr(μ) as the lower and the upper quantization dimensions of μ of order r, respectively. In this paper, we investigate the quantization dimension of the condensation measure μ associated with a condensation system ({Sj}Nj=1, (pj)Nj=0,ν). We provide two examples: one where ν is an …

A Performance Comparison Between Two Speech-To-Asl-Gesture-Projection Translation Implementations, Alexandra Kashani Motlagh, Shikha Mehta, Ishfaq Ahmad, Addison Clark, Hansheng Lei

Informatics and Engineering Systems Faculty Publications

Millions of people with hearing disabilities use sign language for communication, creating a communication gap with those who are not fluent in ASL (American Sign Language). This paper aims to introduce an ASL interpreter system using a smart-glasses-based augmented reality system. We begin by introducing and comparing two models that translate spoken language into ASL poses. The first system translates spoken text to ASL Gloss, an intermediate representation, before generating ASL poses. The second system directly translates the text to ASL poses. Our analysis shows that using ASL Gloss as an intermediate step significantly improves the translation speed. We then …

Ai Meets Economics: Can Deep Learning Surpass Machine Learning And Traditional Statistical Models In Inflation Time Series Forecasting?, Ezekiel N.N. Nortey, Edmund F. Agyemang, Enoch Sakyi-Yeboah, Obu-Amoah Ampomah, Louis Agyekum

School of Mathematical & Statistical Sciences Faculty Publications

This study examined the forecasting ability of deep learning (DL) and machine learning (ML) models against benchmark traditional statistical models for the monthly inflation rates in the USA. The study compared various DL and ML models like transformers, linear regression, gradient boosting (GB), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost) with traditional baseline time-series models like autoregressive integrated moving averages (ARIMA) and exponential smoothing (ETS) with Holt-Winters seasonal method utilizing data sourced from the Federal Reserve Bank of St. Louis. The study consistently showed that all DL and ML models outperformed the traditional approaches. In particular, the Transformer (RMSE …

The Rider (2025-04-21), Rebeca Salinas

The Rider Archives

Vol. 10, No. 26

Trimming Five Generated Gorenstein Ideals, Luigi Ferraro, W. Frank Moore

School of Mathematical & Statistical Sciences Faculty Publications

Let (𝑅,𝔪,𝕜) be a regular local ring of dimension 3. Let I be a Gorenstein ideal of R of grade 3. It follows from a result of Buchsbaum and Eisenbud that there is a skew-symmetric matrix of odd size such that I is generated by the sub-maximal pfaffians of this matrix. Let J be the ideal obtained by multiplying some of the pfaffian generators of I by 𝔪; we say that J is a trimming of I. In a previous work, the first author and A. Hardesty constructed an explicit free resolution of 𝑅/𝐽 and computed a DG algebra …

Shaping Mathematics Identity: An Exploratory Study On Specifications Grading In Calculus I At A Hispanic-Serving Institution, Luis M. Fernandez, Kaitlyn Stephens Serbin, Cristina Villalobos, Shaghayegh Azadi Setayesh, Guillermo Garza

School of Mathematical & Statistical Sciences Faculty Publications

Calculus I courses play a pivotal role in shaping students' STEM pathways, making it essential to adopt pedagogies that foster both achievement and mathematics identity development, particularly among underserved groups such as Hispanic students. This study explores the impact of Specifications Grading, an alternative assessment method where students meet specific course learning objectives through multiple attempts, on students’ mathematics identity development. Through a comparative case study of two Calculus I students at a Hispanic-Serving Institution, one enrolled in a specification graded course and the other in a traditionally-graded course, we examine shifts in their self-perceptions of competence, interest, recognition in …

Search For Continuous Gravitational Waves From Known Pulsars In The First Part Of The Fourth Ligo-Virgo-Kagra Observing Run, A. G. Abac, R. Abbott, I. Abouelfettouh, F. Acernese, Teviet Creighton, Mario C. Diaz, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of general relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO–Virgo–KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering single-harmonic and dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the …

Data-Driven Survival Modeling For Breast Cancer Prognostics: A Comparative Study With Machine Learning And Traditional Survival Modeling Methods, Theophilus Gyedu Baidoo, Hansapani Rodrigo

School of Mathematical & Statistical Sciences Faculty Publications

Background This investigation delves into the potential application of data-driven survival modeling approaches for prognostic assessments of breast cancer survival. The primary objective is to evaluate and compare the ability of machine learning (ML) models and conventional survival analysis techniques, to identify consistent key predictors of breast cancer survival outcomes.

Methods This study employs data-driven survival modeling approaches to predict breast cancer survival, including survival-specific methods such as the Cox Proportional Hazards (CPH) model, Random Survival Forests (RSF), and Cox Proportional Deep Neural Networks (DeepSurv), as well as machine learning models like Random Forests (RF), XGBoost, Support Vector Machines (SVM) …

Detection And Parameter Estimation Of Supermassive Black Hole Ringdown Signals Using A Pulsar Timing Array, Xuan Tao, Yan Wang, Soumya D. Mohanty

Physics & Astronomy Faculty Publications

Gravitational wave (GW) searches using pulsar timing arrays (PTAs) are commonly assumed to be limited to a GW frequency of ≲4 ×10−7  Hz given by the Nyquist rate associated with the average observational cadence of 2 weeks for a single pulsar. However, by taking advantage of asynchronous observations of multiple pulsars, a PTA can detect GW signals at higher frequencies. This allows a sufficiently large PTA to detect and characterize the ringdown signals emitted following the merger of supermassive binary black holes (SMBBHs), leading to stringent tests of the no-hair theorem in the mass range of such systems. Such large-scale …

Ligo Detector Characterization In The First Half Of The Fourth Observing Run, S. Soni, B. K. Berger, D. Davis, F. Di Renzo, A. Effler, T. Ferreira, E. Goetz, Francisco Llamas Villarreal, Volker Quetschke, J. Glanzer

Physics & Astronomy Faculty Publications

Progress in gravitational-wave (GW) astronomy depends upon having sensitive detectors with good data quality. Since the end of the Laser Interferometer Gravitational-Wave Observatory-Virgo-KAGRA third Observing run in March 2020, detector-characterization efforts have lead to increased sensitivity of the detectors, swifter validation of GW candidates and improved tools used for data-quality products. In this article, we discuss these efforts in detail and their impact on our ability to detect and study GWs. These include the multiple instrumental investigations that led to reduction in transient noise, along with the work to improve software tools used to examine the detectors data-quality. We end …

On The Determinant Of Up On Mk(P,Χ), Xingyu Huang, Timothy J. Huber, Dongxi Ye

School of Mathematical & Statistical Sciences Faculty Publications

In this work, for p a prime, we compute the absolute value of the determinant of the UpUp-operator on the vector space Mk(p,χ)Mk(p,χ) of holomorphic modular forms of weight k and level Γ0(p)Γ0(p) with character χχ. As an implication, we confirm a number of conjectures of the second author.

Utilizing Machine Learning To Predict The Charge Storage Capability Of Lithium-Ion Battery Materials, Manoj Chhetri, Karen S. Martirosyan

Physics & Astronomy Faculty Publications

With the increasing demand for high-performance batteries in applications such as electric vehicles and portable electronics, accurately predicting the charge storage capacity of battery materials is crucial for developing more efficient and reliable energy storage systems. Machine Learning (ML) and data-driven approaches, plays a vital role in enhancing our understanding of Li-ion battery performance, guiding materials design, optimizing system efficiency, and accelerating innovation in energy storage technologies. In this study, an ML-based approach was applied to a dataset of 2345 rechargeable Li-ion battery materials, obtained from the Materials Project online portal, to predict gravimetric charge storage capacity ─ a key …

Three New 2+2 Quadruple Systems With Changing Inclination, Petr Zasche, Z. Henzl, M. Mašek, Jan Kára, H. Kučáková, J Merc, R. Uhlař

Physics & Astronomy Faculty Publications

We present a unique discovery of three new detected systems showing two different phenomena together. These are 2+2 quadruple stellar systems showing two eclipsing binaries as the inner pairs. And besides that, these systems were also found to exhibit the precession of the inner orbits causing the inclination changes manifesting themselves through the eclipse depth variations. We are not aware of any similar known system on the sky nowadays, hence our discovery is really unique. In particular these systems are: CzeV4315 = HD 228777 (periods 6.7391 and 0.91932 d, inclination change of pair B of about 1.4∘ yr−1); ASASSN-V J075203.23−323102.7 …

Living With Alzheimer’S: A Guide To How To Lower The Risk Of Memory Loss & Care For Those With Alzheimer’S, Mona Muzammil, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Despite the frequent characterization of Alzheimer's disease as a “loss of self,"" this enlightening book demonstrates unequivocally that a person's unique self persists throughout the course of the disease. The important message in Caring for People with Alzheimer’s is how much can be done in care settings to support a person's sense of identity and thereby enrich the lives of people experiencing the many losses associated with dementia. Drawing from a diverse body of research, this book brings together the recommendations of the best thinkers and practitioners in multiple disciplines to illustrate the meaning of self and the importance of …

Formas, Figuras Y Espacios: Los Fundamentos De La(S) Geometría(S), Melisa Vivanco

Philosophy Faculty Publications

The discussion regarding the origins of geometry examines the fundamental aspects and inception of geometry, drawing from the disciplines of cognitive science, mathematics, and philosophy. With a collection of 14 articles, various authors contribute historical, scientific, and mathematical perspectives, providing a thorough understanding of the principles and application of geometry. This critical essay offers a review and analysis, as well as detailed scrutiny, presenting both support and counterarguments to each of these theories.

Changes In Household Composition And Their Effects On The Academic Achievement Of Orphans And Vulnerable Children Affected By Hiv In Rural Zambia, Mei Tan, Nan Li, Ackim Mungo, Philip E. Thumac, Elena L. Grigorenko

Psychological Science Faculty Publications

The African kinship system facilitates the movement of children and adults between households to mitigate hardship, yet few studies have documented membership changes in rural African households over time and addressed the effects of these household dynamics on the developmental outcomes of children. We used a household inventory instrument to document the number of changes in household membership experienced by 93 households in rural Zambia between two timepoints (∼2 years apart). We then used multilevel models to evaluate the effects of migration and household change on the academic learning of the children affected by HIV residing in these households, positing …

Model-Predictive Optimal Control Of Ferrofluidic Microrobots In Three-Dimensional Space, E. Olga Skowronek, Luke Silas Baker, Reza Ahmed, Hamid Marvi

Mechanical Engineering Faculty Publications

Ferrofluid microrobots have emerged as promising tools for minimally invasive medical procedures. Their unique properties to navigate complex fluids and reach otherwise inaccessible regions of the human body have enabled new applications in targeted drug delivery, tissue engineering, and diagnostics. This paper proposes a model-predictive controller for the external magnetic manipulation of ferrofluid microrobots in three dimensions (3D). The internal optimization routine of the controller determines appropriate changes in the applied electromagnetic field to minimize the deviation between the actual and desired trajectories of the microrobot. A linear system governing locomotion is derived and used as the equality constraints of …

Solitons, Breathers And Rogue Waves Of The Yajima–Oikawa-Newell Long Wave–Short Wave System, Marcos Caso-Huerta, Bao-Feng Feng, Sara Lombardo, Ken-Ichi Maruno

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we consider the recently-introduced Yajima–Oikawa–Newell (YON) system describing the nonlinear resonant interaction between a long wave and a short wave. It extends and generalises the Yajima–Oikawa (YO) and the Newell (N) systems, which can be obtained from the YON system for special choices of the two non-rescalable, arbitrary parameters that it features. Remarkably, for any choice of these latter constants, the YON system is integrable, in the sense of possessing a Lax pair. New families of solutions, including the bright and dark multi-solitons, as well as the breathers and the higher-order rogue waves are systematically derived by …

Unraveling Early Onset Disparities And Determinants: An Analysis Of Colorectal Cancer Outcomes And Trends In Texas, Tyler Torres, Elias Arellano Villanueva, Yossef Alsabawi, Demba Fofana, Manish Tripathi

School of Medicine Publications

Introduction: Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the U.S., with disparities in incidence, survival, and age at diagnosis across racial, ethnic, and socioeconomic groups. The rising incidence of early-onset CRC (< 50 years) has amplified concerns regarding access to care, screening disparities, and outcomes, particularly among minorities. This study examines the impact of race, ethnicity, socioeconomic status (SES), and sex on CRC survival and age at diagnosis in Texas from 1995 to 2016.

Methods: This retrospective cohort study utilized Texas Cancer Registry (TCR) data, including 235,076 CRC cases diagnosed between 1995 and 2016. Kaplan-Meier analysis and log-rank tests assessed 10-year survival by race and ethnicity and time period (1995-2005 vs. 2006-2016). Kruskal-Wallis tests with Bonferroni correction were used to compare survival years between racial/ethnic groups within each period. Age at diagnosis was analyzed by race and …

Exploring Transfer Learning For Deep Learning Polyp Detection In Colonoscopy Images Using Yolov8, Fabian Vazquez Jr., Jose Angel Nuñez, Xiaoyan Fu, Pengfei Gu, Bin Fu

Computer Science Faculty Publications

Deep learning methods have demonstrated strong performance in object detection tasks; however, their ability to learn domain-specific applications with limited training data remains a significant challenge. Transfer learning techniques address this issue by leveraging knowledge from pre-training on related datasets, enabling faster and more efficient learning for new tasks. Finding the right dataset for pre-training can play a critical role in determining the success of transfer learning and overall model performance. In this paper, we investigate the impact of pre-training a YOLOv8n model on seven distinct datasets, evaluating their effectiveness when transferred to the task of polyp detection. We compare …