Digital Commons Network^™

Bifurcation Exploration Of Ion Acoustic Solitons Formation Of A Nonlinear Beta Fractional Kadomtsev-Petviashvili Burger Model In Plasma State, Mst. Razia Pervin, Alrazi Abdeljabbar, Fahad Sameer Alshammari, Mst. Shekha Khatun, Harun Or-Roshid

Mathematical Modelling and Numerical Simulation with Applications

This research presents an extensive investigation of Ion acoustic soliton dynamics governed by a Beta-fractional Kadomtsev-Petviashvili-Burgurs (KPB) model. By engaging the planar dynamical system scheme in aggregation with the extended $(\phi, \psi)$ expansion, Kudryashov expansion, and the NMKM analytic schemes, we create a broad class of exact nonlinear pattern wave solutions. The local stability edifice of the fractional plasma model is explored through bifurcation theory, enabling the far-reaching classification of all admissible phase diagrams. Conforming Ion acoustic wave structures allied with every detour alignment are systematically assembled. Owing to the fractional and dissipative appearances of the model, an all-embracing assortment …

Markov-Modulated Queueing Network For Mobile Traffic Aggregation With Threshold-Controlled Buffers, Anton A. Esin, Elmira Yu. Kalimulina

Mathematical Modelling and Numerical Simulation with Applications

We study the problem of data transmission from mobile platforms operating in high-speed transit between cellular base stations, under conditions of unstable and intermittent connectivity. Conventional queueing and connectivity models often fail to capture the combined effects of rapidly changing signal conditions, finite buffer capacity, and dynamic topology. We aim to develop a tractable yet expressive model that integrates stochastic link availability, queue dynamics, and buffer control. We propose a mathematical framework based on queues whose service intensities are modulated by a continuous-time Markov chain (CTMC) representing signal conditions along a high-speed trajectory. The core subsystem is a two-stage (aggregation …

Measuring Market Risk Through Entropic Var, Dragomir Nedeltchev, Tsvetelin Zaevski

Mathematical Modelling and Numerical Simulation with Applications

The article aims to measure the market risk beyond the basic risk measures like the Value-at-Risk (VaR) and the Expected Shortfall (ES). The Entropic Value-at-Risk is selected among the available measures based on its advantages -- it is the coherent upper bound of the VaR and ES. This risk measure is applied to the classical Black-Scholes model as well as to some more realistic ones, such as the exponential tempered stable model (the log-returns are presented by a tempered stable L\'evy process), the stochastic volatility model of Heston, its jump extension of Bates, and another stochastic volatility model but with …

A Hybrid Multi-Criteria Decision-Making Approach For Sustainable Forest Fire Monitoring Using Unmanned Aerial Vehicles, Mohamed Eassa, Ahmed Abdelhafeez, Ahmad M. Nagm

Neutrosophic Systems with Applications

Unmanned aerial vehicles (UAVs) have become an effective tool for forest fire monitoring. This study evaluates UAVs for forest fire management, addressing the challenges posed by ambiguous and uncertain factors. Single-valued neutrosophic sets (SVNSs) are employed to model complex uncertainties, as they incorporate three distinct membership values: false, true, and indeterminate. The evaluation of UAVs is a multifaceted task due to the variety of factors involved. To address this complexity, multi-criteria decision-making (MCDM) methods are used. Specifically, the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are integrated with SVNS to …

A Systematic Review Of Mathematical Interpretations Of The Weton Marriage Tradition Within Islamic Cultural Contexts, Ratna Damayanti, Surya Sari Faradiba

Jurnal Pendidikan Sains

This study is grounded in the limited integration of mathematics, culture, and religion within academic discussions of local traditions, particularly the weton marriage calculation practice. It aims to explore the mathematical concepts embedded in weton calculations and to analyse these practices from an Islamic law perspective within an interdisciplinary framework. The study employs a Systematic Literature Review (SLR) method following the six-stage PRISMA 2020 protocol, including the formulation of research questions, development of a search strategy, application of inclusion and exclusion criteria, study selection, quality assessment, and thematic synthesis. Data were collected from Google Scholar and Garuda using the keywords …

Preferences For Mathematics And Science Education Majors Among Senior High School Students In Bataan, Zydrick L. Avelino

Jurnal Pendidikan Sains

This study examines the factors influencing Senior High School students’ preferences for Bachelor of Secondary Education (BSEd) majors in Bagac and Morong, Bataan, with particular focus on the low interest in Mathematics and Science specializations despite increasing demand for STEM educators. Using a descriptive quantitative design, data were collected from 369 students through a structured survey and analyzed using frequency and percentage distributions. The results reveal a strong preference for non-STEM majors, with Social Studies (42.12%) and English (35.04%) dominating, while Science (15.43%) and Mathematics (7.395%) received significantly lower interest. Personal interest emerged as the primary determinant (58.8%), followed by …

Ai Adoption In Research Administration At Emerging Research Institutions, Dylan Ruediger, Ruby Macdougall, Stefanie Brachfield, Douglas R. Dechow, Jonathan Parker, Jana Remy

Library Articles and Research

"With funding from the National Science Foundation’s GRANTED program (grant #2437518), Ithaka S+R, Chapman University, and Montclair State University organized two workshops to help research administrators consider how to leverage AI to build research capacity at ERIs. Our first workshop, held at Montclair State in September 2025, brought together 31 participants from 13 academic and medical institutions in the New York/New Jersey/Pennsylvania region. Our second workshop, hosted by Chapman University on December 5, 2025, included 32 participants from 13 colleges and universities in Southern California. The approximately 2,600 ERIs in the United States receive a disproportionately small amount of federal …

Development Of Deep Fused Neural Architecture For Ancient Tamil Palm-Leaf Manuscript Recognition, Hariharan P Mr

Theses and Dissertations

Digitizing Tamil palm-leaf manuscripts is important for education, communication, and the preservation of cultural heritage. The complex structure of the Tamil script, the wide range of handwriting styles, and the degradation seen in ancient Tamil palm-leaf manuscripts make these texts very difficult to read and understand. Digital Image Processing (DIP), document analysis techniques, and traditional Optical Character Recognition (OCR) are unable to handle noise, background interference, faded ink, and limited labelled data, motivating the need for robust, effective Deep Learning (DL)- based solutions.

As a prerequisite to understanding and designing effective recognition systems for ancient manuscripts, this thesis first examines …

The Blurred Boundaries Of Care: A Qualitative Analysis Of Nurse-Doula Role Conflict, Curisa Mae Tucker Phd, Rn, Maria Mcclam, Kelly Russin Dnp, Rnc-Ob, Chse, Nansi Boghossian, Rachel Gulczinski, Lauren Workman

Faculty Publications

Introduction:

Methods:

Patterns Of Multimorbidity Among Low-Income Adults Who Smoke With Implications For Tailored Interventions: A Cluster Analysis Using A Mixture Of Bernoulli Model, Monique T. Cano, Michael R. Lindstrom, Oscar F. Rojas Perez, Ricardo F. Muñoz

School of Mathematical & Statistical Sciences Faculty Publications

Introduction: Smoking cigarettes remains a leading modifiable risk factor for preventable health conditions. In the United States, the health burden of smoking disproportionately impacts low-income individuals. Multimorbidity is common in this group, complicating treatment and worsening outcomes. Identifying multimorbidity clusters can support targeted, individualized interventions. This study aimed to identify multimorbidity clusters among individuals who smoke and experience economic hardship and provide clinical recommendations to enhance health outcomes.

Method: Individuals who smoke and experience economic hardship (N = 60) were recruited from the San Francisco Health Network (SFHN) and were assessed for physical and mental conditions. Cluster analysis was …

Enhancing Introductory Cybersecurity Learning: A Design-Based Research Case Study, Manny Niri Dr.

Journal of Cybersecurity Education, Research and Practice

This study employs a design-based research (DBR) framework to examine the impact of a comprehensive curriculum redesign in an introductory Foundations of Security module for undergraduate students in computing and cybersecurity at a UK public university between 2019 and 2025. The redesign aimed to enhance student learning, engagement, and critical thinking through the embodiment of evidence-based pedagogical strategies, including flipped classroom delivery, blended learning, gamified practical exercises, repeated low-stakes mock assessments, and structured problem-solving activities. Student feedback, assessment outcomes, attendance records, and faculty reflections were analysed to evaluate the effectiveness of the redesign. The results indicate substantial improvements in student …

The Core-Modulation Architecture (Cma): A Structural Overview Of A 14-Paper Research Program (Preprint), Griselda Poe

Publications and Research

This document provides a structural overview of the Core-Modulation Architecture (CMA), a 14-paper research program on cognition, communication, and AI interaction.

The series specifies the conditions under which cognition operates, terminates, fails, and generates structure. Rather than describing cognition by its contents (beliefs, emotions, decisions), it defines cognition through its underlying architecture: constraint-governed processing across layers with distinct termination conditions.

The framework introduces a layered model consisting of Core processing (constraint preservation and structural coherence) and Modulation (affective calibration and social interface adjustment), extended by a Prior layer as the source of constraints. Across the series, phenomena such as miscommunication, …

The Effects Of Affordability And Quality Of Care On Utilization Of Primary Healthcare Among Rural Residents In Twifo Ati-Morkwaa District, Ghana: A Qualitative Study, Peter Ansah Boakye, Francis Tei-Nartey, Gideon Owusu

Michigan Tech Publications

Objective: This qualitative study examines how affordability and quality of care influence the utilization of primary healthcare (PHC) services among rural residents in the Twifo Ati-Morkwaa District, Ghana. While Ghana has implemented policies such as CHPS and NHIS to improve access, subjective experiences of rural residents regarding total costs of care and perceived quality remain underexplored. Methods: We conducted a qualitative cross-sectional study between April and September 2024 using purposive and snowball sampling. Ten gender-segregated focus group discussions (FGDs; n = 90 residents) and six in-depth interviews (IDIs) with PHC providers were conducted. Data were collected in Twi, transcribed and …

Fabrication And Analysis Of Bi₂O₃/Si Heterojunction For Solar Cell Applications, Maher Khaleel Ibrahim, Assel Mustafa Abdul Majeed, Randa Kamel Husain, Jamal M. Rzaij

Al-Bahir

Bismuth oxide (Bi₂O₃) nanoparticles were synthesized via a green route and integrated into Bi₂O₃/Si heterojunction solar cells. Structural analysis confirmed the monoclinic α-Bi₂O₃ phase with a nanoscale crystallite size, while SEM revealed a uniform morphology. Optical studies showed a direct band gap suitable for absorbing visible light. Photoluminescence spectra exhibited dual emissions at 498 nm and 250 nm, attributed to defect states and quantum confinement, highlighting the dual role of Bi₂O₃ as both absorber and transparent window layer. Electrical characterization under dark conditions demonstrated rectifying diode behavior, confirming the formation of a junction. Capacitance–voltage analysis yielded a built-in potential of …

Classification Of Land Cover In Sentinel-2 Imagery Using Machine Learning Models, Ehsan Ali Al-Zubaidi, Mohammed Ridha Hammoodi, Ahmed Naser Alzurfi

Al-Bahir

Remote sensing data of medium resolution are commonly used to classify land cover, and machine learning (ML) models have taken on a central aspect in the necessary data analysis. Ordinarily, land cover is coded on a pixel basis on the basis of Digital Number (DN) values, which in turn are computed across several spectral bands. This paper is concerned with land cover mapping in Mosul, Iraq, based on satellite images captured by Sentinel-2. Two platforms featuring unsupervised classification algorithms were used, Google Earth Engine and ArcMap, making it possible to use K-means and X-means in Google Earth Engine and ISO …

When Ai Writes The Doctoral Thesis: Reclaiming The Oral Defence As A Learning Development Intervention, Valerie A. Storey

All Faculty and Staff Scholarship

Large language models have fundamentally challenged traditional methods of verifying doctoral competency as AI-generated text becomes increasingly difficult to distinguish from human scholarship. This paper argues that thesis committees and doctoral supervisors must reclaim the oral defence as a critical checkpoint for assessing authentic threshold crossing rather than a ceremonial rite of passage. Drawing on historical examples from medieval oral disputations through to the rise of written theses, this paper asserts the necessity of returning to rigorous oral assessment. Given the limitations of detection technologies and the growing use of AI in thesis writing, oral defences must move from confirmatory …

Precision Spectroscopy Of 2s-Ns Transitions In Atomic Hydrogen: A Determination Of The Proton Charge Radius, R. G. Bullis, W. L. Tavis, M. R. Weiss, Orellana O. Cisneros, A. J. Cheeseman, Ulrich D. Jentschura, D. C. Yost

Physics Faculty Research & Creative Works

We present absolute frequency measurements of 2S_1/2-nS_1/2 two-photon transitions with n=8, 9, and 10 in a cryogenic beam of atomic hydrogen. Each transition has been measured with a fractional uncertainty of ≈2.6x10^-12. Combining the results from this Letter and the 1S_1/2-2S_1/2 transition frequency, we extract a root-mean-square proton radius of rp=0.8433(31) fm and a Rydberg frequency of cR_∞=3 289 841 960 252.9(9.7) kHz. These are in good agreement with the CODATA 2022 recommended values.

Riemann-Hilbert Problems For A Class Of Planar Orthogonal Polynomials, Abril Arenas

USF Tampa Graduate Theses and Dissertations

Planar orthogonal polynomials of degree n are monic polynomials defined by the orthogonality relation,

∫cPn(z)Pm(z)e-V(z) dA(z) = hnδn,m.

where the integration is over the whole complex plane with Lebesgue area measure dA, and hn is a positive norming constant. In this thesis we consider the potential V: CR of the type,

V(z) = |z|2p-2Re Σm j=1 tjzj

we characterize the planar orthogonal polynomials using novel matrix Riemann-Hilbert problems. We pro-pose a Riemann-Hilbert problem of size 2px 2p when the maximal degree satisfies m ≤ p. For m = 2p, we propose a Riemann-Hilbert problem of size 3px 3p for the …

New Identities In The Character Table Of Symmetric Groups Involving Riordan Numbers, David J. Hemmer, Armin Straub, Karlee J. Westrem

Michigan Tech Publications

Amdeberhan recently proposed certain equalities between sums in the character table of symmetric groups. These equalities are between signed column sums in the character table, summing over the rows labeled by partitions in Ev(λ), where λ is a partition of n with r nonzero parts and Ev(λ) is a multiset containing 2r partitions of 2n. While we observe that these equalities are not true in general, we prove that they do hold in interesting special cases. These lead to new equalities between sums of degrees of irreducible characters for the symmetric group and a new combinatorial interpretation for the Riordan …

Interview With Orca Award Winner David Hage, Unl Chemistry; Drug-Protein Interactions, Mark Griep, David Hage

UNL ORCA Interview Series

Prof. David Hage was awarded the ORCA in 2018. He was born in La Crosse, Wisconsin, and earned a bachelor’s in chemistry at the University of Wisconsin in La Crosse. Next, he earned a doctorate from Iowa State University and did postdoctoral work at the Mayo Clinic in Rochester, Minnesota. In 1989, he joined UNL as an assistant professor of chemistry and quickly rose through the ranks. He has won many awards and, for the past 13 years, has been the James Hewet University Professor of Chemistry. Allow me to share some remarkable facts about Dave before we get into …

Curriculum For A Two Semester Calculus Course Specializing In Life Science And Data Science, Patrick Mcclain

LSU Master's Theses

Traditionally, introductory calculus has been designed for engineering and physics students, often leaving students majoring in data science or life sciences with a curriculum that lacks professional relevance and is overly reliant on problems that focus on computational fluency. This thesis proposes a two-semester sequence, called MATH 153X and MATH 154X, specifically tailored for the Louisiana State University (LSU) Dual Enrollment program and university-level data science and life sciences majors. By integrating modern computational tools—such as symbolic calculators and artificial intelligence (AI) tools—the proposed curriculum shifts the pedagogical focus from procedural symbolic manipulation toward conceptual literacy.

Through a series …

Towards Understanding Robust Neural Coding Through Representational Geometry, Zeyuan Ye

Arts & Sciences Graduate Student Theses and Dissertations

Neural activity is high-dimensional and variable, yet animals represent information robustly. This thesis studies the origins of such robustness through the lens of representational geometry and deep neural network modeling. From a geometric perspective, population responses concentrate near smooth manifolds embedded in a high-dimensional state space. To infer these manifolds from noisy data and quantify their geometric properties, we develop a statistical method based on Gaussian processes and kernel regression (GKR). Applying GKR to simultaneously recorded grid-cell population activity during open-field navigation, we show that increasing running speed expands a torus-like representational manifold and improves spatial decodability. Thus, despite faster …

Meteorological Monitoring With Real-Time Data Processing Using Uas, Htoo Poe Sar, Cal Coopmans, Sierra Young

Spring Runoff Conference

Background and Motivation 

• Agricultural water management requires information about crop water use and water consumption 
• Remote sensing methods are used to model and estimate environmental processes – but they require weather data 

Utah Prototype For Visualizing Vulnerabilities Downstream Of Dams, Courtney Flint, Michael Englert, Nicolas Holden

Spring Runoff Conference

The climate question 

• Overtopping = 1/3^rd of all dam failures (ASDSO) 
• Drought concerns and supply uncertainty motivate keeping reservoirs full 
• Overtopping likelier if extreme storm when reservoir full 
• Over much of the country the probability of the annual daily maximum rainfall > 100-year event and the preceding 30-day rainfall >10-year event are going up (Hwang & Lall 2024) 

Pong Revised: Network-Based Competitions Through Secure Socket Services, Noah T. Jennings, Destiny D. Hale, Jared D. Williams, Michael J. Lively-Scholz

Knowledge and Creativity Expo

We aim to provide a safe, thrilling, locally hosted, and educational multiplayer experience that can be quickly replicated in modern Capture The Flag (CTF) events.

Extending The Geometric Phase To Relativistic Spacetime, Sajid Raihan Akash

Department of Physics and Astronomy: Dissertations, Theses, and Student Research

The Berry phase [3] is traditionally understood as a geometric phase acquired during cyclic adiabatic evolution, often interpreted as the flux of an effective “magnetic field” through a solid angle in parameter space. In this thesis, we investigate situations in which a geometric phase arises even when no spatial solid angle is enclosed, revealing the limitations of the standard purely spatial interpretation. We first review the Berry phase for a spin-½ particle in a slowly varying magnetic field and analyze scenarios in which the system’s eigenstate is changed during the adiabatic evolution. We show that the resulting phase can be …

Discovery Of Quasi-Carbon Nanotube Structures In Tectonically Deformed Coals And Their Formation Mechanisms, Li Yunbo, Wang Rongqi, Song Dangyu, Wang Chengtao, Li Qiang, Yi Ke, Wang Yuanyuan, Pan Jienan

Coal Geology & Exploration

Objective Carbon nanotubes (CNTs) have attracted wide attention due to their unique structures and performance. However, their artificial synthesis requires stringent conditions, including high temperatures (700 ℃ to 2 300 ℃), stable carbon sources, and catalysts. Furthermore, these structures are rarely discovered in nature. As a carbon-rich medium, coals can form a variety of ordered carbon structures during their metamorphic and deformational processes, serving as an ideal carrier for exploring the formation mechanisms of natural CNTs.Methods Typical tectonically deformed coals from the Pingdingshan and Huaibei mining areas were investigated in this study. After demineralization and chloroform extraction, coal samples …

Spatiotemporal Variations And Their Influencing Factors For Vegetation Net Primary Productivity In The Shendong Coal Base, Yang Fei, Cui Kuankuan, Zhang Chengye, Li Jun, Dong Qiulin

Coal Geology & Exploration

Objective The Shendong coal base, located within the arid and semi-arid regions in western China, is identified as the region with the most pronounced contradiction between coal resource development and ecological conservation in the country. Analyzing the spatiotemporal variations in the ecosystem and their influencing factors at the base scale provides a necessary foundation for green mine construction while also offering critical support for regional sustainable development.Methods In this study, the vegetation net primary productivity (NPP) was selected as an indicator for the ecological evaluation of mining areas. By integrating data on terrain, weather and climate, socio-economy, and human …

Soil Microbial Biomass And Organic Carbon Fractions Under Different Natural Restoration Years In Arid Coal Mining Subsidence Areas In Xinjiang, China, Xiao Li, Bi Yinli, Wang Dongdong, Li Jianfeng, Gong Hanlin, Deng Aojuan, Hou Wensheng

Coal Geology & Exploration

Objective This study aims to elucidate the influence of the natural restoration process on changes in soil microbial biomass and organic carbon fractions in coal mining subsidence areas. This effort will provide a crucial scientific foundation for understanding the natural ecological restoration process and carbon accumulation dynamics in arid coal mining subsidence areas.Methods Arid coal mining subsidence areas in Xinjiang, China were investigated in this study. Using the space-for-time substitution approach, sample plots were selected from an unmined area and areas having undergone natural restoration for one, three, eight, and 12 years. Subsequently, systematic analyses were conducted on the …

Application Of A Generative Adversarial Network To Super-Resolution Reconstruction Of Fracture Images In Logging-While-Drilling Electrical Resistivity Imaging, Han Sen, Shen Chuanhai, Xu Chen, Tian Yimeng, Zhao Biao, Wang Ze, Liu Yongkang, Kang Zhengming

Coal Geology & Exploration

Objective Logging-while-drilling electrical resistivity imaging (LWD-ERI) enables the intuitive presentation of geobodies near wellbores in images, representing an important approach to the fine-scale evaluation of stratigraphic parameters while also providing significant geological guidance during the drilling of fractured reservoirs. However, this technique faces the challenge of low image resolution in real-time data processing due to its limited well-to-surface data transmission rates, exerting adverse impacts on the qualitative identification of wellbore fractures and the quantitative evaluation of their parameters. To address this issue, this study proposed a super-resolution image reconstruction method based on a generative adversarial network (GAN), aiming to achieve …