Digital Commons Network^™

Balancing Stability And Complexity In Boolean Models Of Biological Networks, Venkata Sai Narayana Bavisetty

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Compartmental Model For Periodic Animal Migration, Rhianna Yates, Leah Glasser, Elena Wheatley, Christopher Hay-Jahans

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Optimizing The Distribution Of Fruiting Agave On Bat-Friendly Tequila Plantations, Grace Gorreck, Clarissa Azurin, Lois Carpenter

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Spatial Strategies In Ants: Modeling Polydomy, Saya Zeleznik, Fred Adler

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Parameter Estimation And Simulation In Pollution-Induced Asthma Disease Model Using Physics-Informed Neural Networks, Aadi Gannavaram

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Predicting An Uncertain Future: Conservation Easements And The Difficulties Created By Speculative Valuations, Travis L. Strickler

Kentucky Law Journal

No abstract provided.

Startup Success Forecasting Through Machine Learning: A Comprehensive Analysis Of It Startups, Khaled Abdulla Alhassani

Thesis/ Dissertation Defenses

Lately, startups attracted significant attention from investors throughout the previous years. This raised several questions concerning startups and what they possibly define as them. It could refer to collective individuals who focus on innovative ideas with a reproducible and scalable business model; others refer to it as a newly established business. Nevertheless, all these definitions lead to a predictive question. Will these startups face success? This study explores startup success prediction methods, focusing on forecasting information technology startup (SIT) insights using Machine Learning (ML) models such as Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), K-Nearest Neighbor (k-NN), …

New Evidence Of Mid-Pleistocene Glaciations In The French Jura Mountains Using Debris Flow Deposits And U/Th Dating Of Speleothems (Verneau Karst Network), Margot Vivier, Stéphane Jaillet, Eglantine Husson, Edwige Pons Branchu, Jean-Baptiste Charlier

International Journal of Speleology

We redefine the extent of former glaciers in the northern Jura Mountains through the study of endokarst deposits. Sedimentary deposits (pebbly debris flows, laminated clays, and allochthonous limestone blocks) and chemical deposits (speleothems) were identified and studied using three complementary approaches: (i) detailed geomorphological mapping, (ii) petrographic analysis, and (iii) U/Th-dating. In addition, a surface geomorphological analysis made it possible to calculate the minimum erosion time required for the formation of the sinkhole linked to the underground study site. The study site is the Dolois Chamber, an underground site upstream of the Verneau karst network (Doubs Department, France). The combined …

An Analysis Of Large Language Model Hallucination And Creativity: Linear Representations And Causal Roles, Mckay Bowcut

Theses and Dissertations

Large language models (LLMs) show remarkable abilities in both factual and creative tasks, yet the problem of hallucination persists despite advances in training and post-training methods. Recent progress in model interpretability suggests that model behavior can be predicted and influenced by analyzing and manipulating internal activations. In this thesis, we address three questions: (1) Can we identify linear representations of hallucination and creativity in the model’s latent space? (2) Do these representations play a causal role in model behavior when manipulated? (3) Are creativity and hallucination causally intertwined? To answer these, we construct a novel dataset of factual, hallucinated, and …

Sound Practices In Human Resources: A Critical Analysis Of How Ai Applicant Screening Tools Are Used With Deaf Individuals In The Hospitality And Tourism Sector, Sherry L. Gaynor

USF Tampa Graduate Theses and Dissertations

This study explores the intersection of Career and Workforce Education, Deaf Education, and artificial intelligence (AI) technologies used in hiring practices. The purpose of this research is to identify potential barriers to equitable employment for Deaf and Hard-of-Hearing (DHH) individuals and to propose effective methods for evaluating and assessing AI and machine learning applications utilized in recruitment and selection processes. Although AI is increasingly embedded in human resource management (HRM), there remains a significant lack of research addressing its use with special populations. In particular, no prior studies have examined how voice recognition software, facial analysis, psychometric testing, and virtual …

Statistical Challenges And Simulation Results For Pilot Clinical Trials, Weiliang Cen

USF Tampa Graduate Theses and Dissertations

Background: The effect size estimated from a pilot trial is often an inaccurate reflection of the true effect size observed in a large trial, leading to either underestimation or overestimation. Published data suggest that effect sizes from large trials are typically smaller than those reported in their corresponding pilot trials. To address this discrepancy, conservative or discount adjustment methods are widely recommended to modify pilot trial effect sizes when calculating sample sizes, thereby maintaining adequate statistical power. This study aims to assess effect sizes from both pilot and large trials and to evaluate the performance of existing adjustment methods.

Methods: …

Infographic: Pisa Insights – Encouraging Mathematical Thinking, Dominique Russell

Teacher infographics

Each cycle of the global Programme for International Student Assessment (PISA) includes a teacher questionnaire. One questionnaire topic – encouraging mathematical thinking – can help foster critical thinking, enhance problem-solving skills and allow students to see the relevance and connectedness of mathematics in their lives.

From The Editors, Rully Karim Dr.

Journal of Project Management & Construction

The Journal of Project Management and Construction (JPMC) is a peer-reviewed publication dedicated to advancing the field of project management and construction, grounded in the principles outlined in the PMBOK 6th Edition. Our focus encompasses the ten knowledge areas essential to successful project management: Integration, Scope, Schedule, Cost, Quality, Resource, Communications, Risk, Procurement, and Stakeholder Management.

JPMC publishes original research papers written in English that provide deeper insights into these knowledge areas and contribute to the development of best practices in project management and construction. Submissions may include theoretical analyses, computational models, experimental observations, or a combination of both theoretical …

On Heat Engines Having Efficiencies That Degrade With Every Cycle That Are Nonetheless Reversible: The Wonders Of Hilbert Curves In The Pressure-Volume Plane, Daniel Graham

Chemistry: Faculty Publications and Other Works

Heat engines are cornerstones in classical thermodynamics, not to mention fixtures of everyday life. As everyone knows, real heat engines are rife with sources of irreversibility, and, in turn, have efficiencies that degrade over time. Here we chart a classical heat engine whose efficiency degrades with every cycle, but maintains perfect reversibility nonetheless. There are no paradoxes in play due to the inviolability of the thermodynamic laws. Rather the engine operates transparently according to Hilbert curves that fill the pressure-volume plane. The assembly of the curves is iterative and digital whereby no information is lost over every cycle.

Spatio-Temporal Characterization Of Trace Metals Across The West Florida Shelf And During The Decline Of The North Atlantic Spring Bloom, Delfina Paola Navarro-Estrada

USF Tampa Graduate Theses and Dissertations

Phytoplankton in the marine environment require the trace metals manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd) to catalyze cellular processes driving photosynthesis, including macronutrient (nitrogen, phosphorus, and carbon) acquisition, light harvesting, and protection from oxidative stress. The high biological demand for these elements, coupled with their low concentrations in the ocean, can limit primary production and shape community composition in marine ecosystems, highlighting the need to understand the drivers behind trace metal distributions and their interplay with phytoplankton growth across biogeochemical regimes. This dissertation characterizes the spatial and temporal distributions of dissolved …

Detecting Burned Vegetation Areas By Merging Spectral And Texture Features In A Resnet Deep Learning Architecture, Jiahui Fan, Yunjun Yao, Yajie Li, Xueyi Zhang, Jiquan Chen, Joshua B. Fisher, Xiaotong Zhang, Bo Jiang, Lu Liu, Zijing Xie, Luna Zhang, Fei Qiu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Timely and accurate detection of burned areas is crucial for assessing fire damage and contributing to ecosystem recovery efforts. In this study, we propose a framework for detecting fire-affected vegetation anomalies on the basis of a ResNet deep learning (DL) algorithm by merging spectral and textural features (ResNet-IST) and the vegetation abnormal spectral texture index (VASTI). To train the ResNet-IST, a vegetation anomaly dataset was constructed on high-resolution 30 m fire-affected remote sensing images selected from the Global Fire Atlas (GFA) to extract the spectral and textural features. We tested the model to detect fire-affected vegetation in ten study areas …

Enhancing It Security Management With An Advanced Intrusion Detection System Based On Machine Learning And Explainable Ai, Hanan Alzubaidi

Thesis/ Dissertation Defenses

The fast-changing landscape of cyber threats continues to challenge the development of strong and reliable security frameworks for IT management systems. Traditional defense tools, such as Intrusion Detection Systems (IDS), often struggle to keep up with today’s advanced and constantly evolving attack methods. This thesis explores these ongoing challenges and looks into how machine learning (ML) and explainable artificial intelligence (XAI) can be used to boost IDS performance.

The research outlines a smart, adaptive system that combines supervised learning for real-time threat detection, unsupervised models for anomaly analysis, and proactive defense strategies. The goal is to improve detection accuracy, cut …

Analysis Of An Effective Training Curriculum: Solutions Toincrease Participants' Interest In Training Teachingmaterials, Maulidya Husnul Khatimah, Yoto Yoto

Jurnal Pendidikan Sains

This research is important because it analyzes the curriculum as a primary tool for generating and maintaining participant interest. Curricula that are irrelevant, monotonous, or misaligned with participant needs are often the main causes of low motivation and participation. Furthermore, this research encourages the exploration and implementation of more innovative teaching methods and materials in training curricula. External pressure in the form of demands or instructions, rather than internal motivation, drives most training activities. This can reduce engagement and learning effectiveness. To overcome this, training institutions need to design programs that are relevant, flexible, and able to encourage participants' intrinsic …

Augmented Reality-Assisted E-Module On Temperature Andheat Content (Emarks), Tetri Sabrina, Ika Mustika Sari, Dedi Sasmita

Jurnal Pendidikan Sains

Temperature and heat content (calor) material in physics often involves concepts and phenomena that are difficult to observe directly or are abstract (such as energy transfer, particle movement, and changes in state). EMARKS (AR-based E-modules) are important because Augmented Reality (AR) allows the visualization of these abstract concepts in the form of interactive 3D models in the user's real environment. This helps students understand the concepts more concretely and easily. The development of E-modules is an innovation in learning media that is relevant to the demands of the digital era and the needs of modern students. The use of advanced …

The Effect Of Guided Inquiry Model With Deep Learningapproach On Student’S Hots In Elements, Compounds,And Mixtures At Junior High School, Friska Pakpahana, Retno Dwi Suyanti

Jurnal Pendidikan Sains

The current education curriculum places a strong emphasis on developing HOTS skills (such as analyzing, evaluating, and creating) to prepare students for the challenges of the 21st century. School learning often focuses on lower-level cognitive domains (memorizing and understanding). This research seeks to address this gap by offering a potentially effective learning model. The guided inquiry model positions students as active participants in learning, encouraging them to investigate, discover, and formulate concepts independently with teacher guidance. This strongly supports the development of critical thinking and problem-solving skills. Therefore, this study aims to analyze the effect of the guided inquiry model …

Development Of Problem-Based Learning Worksheet Toenhance Ecoliteracy: Human Impact On Ecosystem, Ulina M.S. Simangunsong, B. Manurung, Martina Asiati Napitupulu

Jurnal Pendidikan Sains

Ecoliteracy (ecological literacy) is an individual's ability to understand basic ecological principles and make environmentally responsible decisions. Improving ecoliteracy is a crucial foundation for realizing Education for Sustainable Development (ESD), which prepares students to become proactive citizens in protecting the environment. The problem-based learning model helps students learn on their own by using real-world environmental cases to get them to think critically and solve problems. Therefore, this research aims to determine the effectiveness of using problem-based learning worksheets to enhance the ecoliteracy of seventh-grade students. The development model used is 4-D. The research instruments include expert validation forms for subject, …

Development Of E-Lkpd Assisted By Phet Colorado Basedon Discovery Learning: Critical Thinking Skills On Lightmaterial At Junior High School, Flora Yani Saragih, Pintor Simamora

Jurnal Pendidikan Sains

Critical thinking is necessary for 21st-century pupils, but PISA data suggest that Indonesian students, especially junior high school students, lack it. The junior high science/physics light material is abstract and involves in-depth reasoning (reflection, refraction, and shadow generation). Without critical thinking, kids memorize formulas or notions without analyzing real phenomena. Discovery learning involves pupils discovering concepts via observation and experimentation. Critical thinking requires initiative, exploration, and reasoning, which these foster. Therefore, this study aims to develop E-LKPD based on Discovery Learning assisted by an interactive simulation of PhET Colorado to strengthen the critical thinking skills of grade VIII students on …

Guided Inquiry Learning Assisted By Crossword Puzzlemedia: Student Scientific Literacy And Critical Thinkingability For Middle School, Agis Putri Niswa, Mariati Purnama Simanjuntak, Ramlan Silaban, Fauziyah Harahap, Ridwan Abdullah Sani

Jurnal Pendidikan Sains

Scientific literacy and critical thinking skills are two fundamental competencies that students need in the 21st century. Scientific literacy is essential for students to understand and use scientific knowledge to make informed decisions, while critical thinking trains students to analyze information, evaluate arguments, and solve problems logically. Therefore, the intent of this study was to determine the effect of the guided inquiry learning model assisted by crossword puzzle media on students’ scientific literacy and critical thinking skills. The type of research used was quasi-experimental with a two-group pretest-posttest design. The sample consisted of two classes: class VII-8 as the control …

Computer Organization With Arm64, Seth D. Bergmann

OER Textbooks

This book is intended to be used for a first course in computer organization, or computer architecture. It assumes that all digital components can be constructed from fundamental logic gates.

The book begins with number representation schemes and assembly language for the ARM-64 architecture, including assembler directives and floating point instructions. It then describes the machine language instruction formats, and shows the student how to translate an assembly language program to machine language.

There is then an introduction to boolean algebra and digital logic, followed by a description of the memory hierarchy, including cache memory, RAM, and virtual memory.

The …

2025 November 6 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Interpretable Machine Learning For Cardiovascular Risk Prediction: Insights From Nhanes Dietary And Health Data, Md Ahiduzzaman, Md Nahid Hasan

Faculty Publications

Background: Cardiovascular diseases (CVD) are one of the leading global causes of death, which requires an accurate early prediction. This study aimed to develop transparent machine learning (ML) models using National Health and Nutrition Examination Survey (NHANES) data from 2017–2023 to predict CVD risk based on dietary and health factors.

Methods: We analyzed data from 12,382 adults (aged 18 and older) from NHANES 2017–2023, including 41 dietary, anthropometric, clinical, and demographic variables. Recursive Feature Elimination (RFE) was used to select an optimal subset of 30 predictors. To address substantial class imbalance in the outcome, we applied the Random Over-Sampling Examples …

Parameterizing Ion–Lipid Interactions From Local Clusters To Reproduce Experimental Bulk Properties Of Lipid Bilayers, W. Matthew Saunders

USF Tampa Graduate Theses and Dissertations

Phospholipids are the main component of cell membranes, providing a delimiting boundary for cells from their environments or from their organelles from the cytosol. Thiscompartmentalization allows cells to maintain quite different solutions within their cells and organelles, including different mixtures dissolved ions. Consequently, these membranes are constantly flanked by complex mixtures of salts at varied concentrations. To study membrane structure, one cannot neglect the contribution of the salts in the local solution. Ions perturb bilayer structure via specific interaction with the phospholipids, primarily with the headgroups. Experimental studies of these systems are somewhat at odds — scattering experiments with different …

Enhancing Turbulent Mixing And Microphysical Uniformity In A Tall Convection-Cloud Chamber Through Idealized Heterogeneity Of Boundaries, Lois Thomas, Fan Yang, Aaron Wang, Mikhail Ovchinnikov, Kyle Pressel, Raymond Shaw

Michigan Tech Publications

A large convection cloud chamber has been proposed for exploring aerosol–cloud–drizzle interactions under well‐controlled turbulent conditions. Recent theoretical and numerical studies suggest that ac on vection cloud chamber with two heated and two cooled sidewalls can significantly enhance the liquid water content and thus benefit drizzle initiation. However, a chamber with such a sidewall configuration develops stable stratification and extremely weak turbulence therein. In this study, we conduct large‐eddy simulations of a tall convection chamber with five different sidewall configurations consisting of alternating warm and cold patches. For each configuration, the total surface area of warm patches equals that of …

Thermal Properties Of Novel Materials, Wilarachchige D.C. Bhagya Gunatilleke

USF Tampa Graduate Theses and Dissertations

Thermal properties play an important role in various aspects of applications of technology startingfrom the materials property determinations to device performance improvements and their safety and stability. Measurements of the thermal properties of such materials of interest pose challenges due to the demands of these measurements for determination of intrinsic materials properties. The research included in this dissertation involved both synthesis of novel materials and their measurement of thermal properties. Solid-state materials synthesis involves various synthesis and processing techniques, while specific technological applications demand synthesis of defect-free single crystals. Such synthesis techniques were explored for the research included in this …

Site Specific Reliability-Targeted Snow Loads And Winter Wind Parameters Across The World, Brennan Bean, Nicholas Brimhall, Bikram Bhusal, Marc Maguire, Maha Moussa

Mathematics and Statistics Faculty Publications

This report presents a framework for estimating Reliability Targeted Snow Loads (RTSLs) and Winter Wind Parameters (WWPs) at locations outside the Conterminous United States (OCONUS). The methodology integrates ground-based in-situmeasurements with gridded global climate products to generate spatially continuous RTSL estimates for nearly any location in OCONUS. RTSLs are computed at qualifying in-situ stations, and predictive models relating gridded climate products to in-situRTSLs enable estimation at locations lacking direct measurements. This report describes the development of the in-situ annual maximum snow load database, the construction of global gridded climate summaries, the estimation of site-specific RTSLs and Service Targeted …