Physical Sciences and Mathematics Commons^™

Clea Labs For Planetary, Stellar, And Cosmological Astronomy Configured For 64-Bit Windows 11+ Machines, Itan Altamirano, Jack C. Straton

Physics Faculty Publications and Presentations

Project CLEA -- CONTEMPORARY LABORATORY EXPERIENCES IN ASTRONOMY -- develops laboratory exercises that illustrate modern astronomical techniques using digital data and color images.

These Labs were developed for 32-bit Windows machines but PSU student Itan Altamirano reconfigured installation programs to bypass steps that ask for DVDs and allowing these 32-bit programs to work on 64-bit Windows 11+ computers.

M3t, Mariia Khan, Jumana Abu-Khalaf, David Suter, Bodo Rosenhahn, Yue Qiu, Yuren Cong

Research Datasets

For embodied agents, such as robots, tracking objects in their surroundings through visual observation is essential — a task, referred to as Visual Object Tracking (VOT). For instance, during a rearrangement task, a robot may need to track objects, as part of the scene change understanding process, to accurately restore them to their original states. Classic Multiple Object Tracking (MOT) datasets typically focus on tracking moving, single-class object instances in a video from a fixed viewpoint, limiting their applicability to embodied AI tasks. In embodied AI tasks, objects belong to multiple classes, are often static, and are observed from continuously …

Embscu, Mariia Khan, Jumana Abu-Khalaf, David Suter, Bodo Rosenhahn, Yue Qiu, Yuren Cong

Research Datasets

This dataset was created for the evaluation of the EmbSCU method, suitable for solving the Scene Change Understanding (SCU) task. The SCU task involves predicting a changed location, describing a change, and generating language instructions for the robotic agent to revert a change. Current datasets, related to scene change understanding, can be divided into scene change detection (SCD) and image difference captioning (IDC) datasets. Unlike existing approaches, EmbSCU facilitates simultaneous change detection, description and language-based rearrangement instruction generation for the agent to revert changes. Although the EmbSCU dataset is simulated, it is highly complex, incorporating 104 unique indoor Ai2Thor rooms. …

Saom, Mariia Khan

Research Datasets

The SAOM dataset is created for the evaluation of the whole-object semantic segmentation in embodied AI indoor environments. The SAOM dataset is tailored for segmentation in dynamic embodied environments, focusing on interactable objects. It includes 54 object classes, all of which are either `pickupable’, `openable’, or `receptacles`. Unlike static-object datasets, the objects in SAOM can undergo transformations, such as being opened, closed, or moved.

Simulating Interventions To Improve Reproducibility In Scientific Publications, Ben G. Fitzpatrick

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Rubrics Informed By The Cognitive Theory Of Multimedia Learning That Support Research On Personalized Learning Paths, Sean A. Mochocki, Mark G. Reith, Jonathan Zemmer

AFIT Documents

Personalized Learning Paths (PLP)s are a popular area of research in E-Learning where sequences of Learning Materials (LM)s and activities are returned based on a learner profile, the LM metadata, and a knowledge structure that describes the relationship between the underlying topics. Unfortunately, PLP researchers tend to not use an empirically supported cognitive science framework for their research, instead relying on such unsupported theories as learning styles or developing their own ad hoc approaches. While many of these researchers present and solve challenging PLP problems using a variety of algorithmic approaches, the PLP community in general would benefit from a …

Raw Data For High Entropy Stabilized Platinum Diborides For Poison-Resistant Catalysis, Michael Yeung, Ting Wang

Chemistry Department Faculty Scholarship

Raw data for the publication High-Entropy-Stabilized Platinum Diborides for Poison-Resistant Catalysis including Powder X-ray Diffraction and Nuclear Magnetic Resonance data.

Abstract for publication:

Alloying and solid-solution formation is a powerful technique that enhances and adds properties through elemental mixing, but unfortunately, some elements simply cannot mix as their chemical nature prevents a thermodynamically stable structure. For example, the inherent nobility of platinum group metals does not favor bond formation and precludes their incorporation into higher (boron-rich) metal borides. Here, we demonstrate that when using five or more constituents, the higher mixing entropy will overcome these chemical limitations and form a …

Kentucky Geological Survey Landslide Inventory [2024], Matthew M. Crawford, Evelyn M. Bibbins, Hudson J. Koch

Research Data--KGS

The KGS landslide inventory provides the locations of known landslides and areas susceptible to debris flows. Various types of landslides are represented including slides, flows, rockfalls, and creep. The data are available as ArcGIS geodatabase feature classes. Landslide locations and associated attributes are compiled from Kentucky Geological Survey research, published maps, state and local government agencies, the public, and media reports. A confidence ranking system assigns a value to each feature. A description of the feature classes is here: https://kgs.uky.edu/kgsmap/helpfiles/landslide_help.shtm

The inventory viewed in a GIS with geology, soils, slope or other terrain-based data can serve as a basis for …

Supplementary Files For "Impact Of Snow Accumulation On Structural Integrity: Present And Future Perspectives", Kenneth Pomeyie, Brennan Bean

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Evaluating the impact of weight exerted by settled snow (i.e., snow load) on structures poses numerous statistical challenges, including missing data, biased distribution parameters, and the influence of climate change. This dissertation aims to address challenges related to the use both direct and indirect measurements of snow load (or equivalently, snow water equivalent), as well as the anticipated impact of climate change on future extreme snow loads. The first paper within this dissertation investigates short-term snow loads by comparing various techniques for estimating extreme values of short-term snow accumulations. Additionally, the first paper includes a comparative analysis of short-term and …

Supplementary Files For: Quantifying The Impact Of Rain-On-Snow Induced Flooding In The Western United States, Emma Watts, Brennan Bean

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Serious flooding can happen when rain falls on snow, which we call a rain-on-snow (ROS) event. Increasing our understanding of the behavior of floods resulting from ROS events can help us design better systems to manage flood water and prevent it from causing damage. This thesis explores how ROS events affect streamflow in the Western United States by examining the weather conditions that precede a streamflow surge. We classify stream surges as ROS or non-ROS induced based on these weather conditions, which helps us separate floods caused by ROS events from those caused by other factors. By comparing these different …

Kentucky Surficial Geologic Map Compilation Database (Version 1), Matthew Massey

Research Data--KGS

The Kentucky Geological Survey (KGS), a state-supported independent research center within the University of Kentucky, is committed to providing accurate and unbiased geologic information on natural resources, environmental issues, and natural hazards in Kentucky. While Kentucky boasts complete coverage by 1:24,000-scale geologic bedrock maps, surficial materials have been largely overlooked, except in regions with thick deposits obscuring the bedrock. Given the increasing trends in economic development and urbanization, detailed surficial geologic mapping has become crucial for supporting geotechnical planning, environmental management, and hazard assessment. In response, KGS has prioritized new, detailed surficial geologic mapping since 2004, specifically targeting areas anticipated …

Putting Gpt-4o To The Sword: A Comprehensive Evaluation Of Language, Vision, Speech, And Multimodal Proficiency, Sakib Shahriar, Brady D. Lund, Nishith Reddy Mannuru, Muhammad Arbab Arshad, Kadhim Hayawi, Ravi Varma Kumar Bevara, Aashrith Mannuru, Laiba Batool

All Works

As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and multimodal capabilities of GPT-4o. The study employs standardized exam questions, reasoning tasks, and translation assessments to assess the model’s language capability. Additionally, GPT-4o’s vision and speech capabilities are tested through image classification and object-recognition tasks, as well as accent classification. The multimodal evaluation assesses the model’s performance in integrating visual and linguistic data. Our findings reveal that GPT-4o demonstrates high accuracy and efficiency across multiple domains in language and reasoning …

Presence Of Pharmaceuticals And Personal Care Products In Sinkhole Lakes In West-Central Florida, Elzbieta Bialkowska-Jelinska

USF Tampa Graduate Theses and Dissertations

Pharmaceuticals and personal care products (PPCPs) are essential for human health, improving quality of life, and extending life expectancy. However, many of these chemicals have become significant environmental pollutants, particularly in lentic (lake) environments. One unintended source of PPCPs in natural environments is onsite wastewater treatment systems (OWTS), commonly known as septic tanks.

This study examines whether the seasonal variability of rainfall and soil saturation affects the assemblages and concentrations of PPCPs in a residential lake. The general premise of the dissertation was that with the onset of the wet season, PPCPs that had collected in the drainfields of the …

The Newgeneratortm Decentralized Wastewater Treatment System For Non-Sewered Sanitation: Technology Advancement Through Field Evaluation And Modeling, Hsiang-Yang Shyu

USF Tampa Graduate Theses and Dissertations

Non-sewered sanitation systems (NSSS) offer innovative solutions to sanitation challenges in areas lacking basic facilities, utilizing advanced treatment technologies for on-site water reuse. The NEWgenerator (NG), an advanced NSSS developed at the University of South Florida under the Bill & Melinda Gates Foundation’s Reinventing the Toilet Challenge, integrates an anaerobic membrane bioreactor (AnMBR), an ion exchange-based nutrient capture system (NCS), and an electrochlorinator for final disinfection. This study builds on previous field trials of the NG system, focusing on developing, evaluating, and optimizing its water reuse capabilities through field trials, system dynamics modeling, and advanced monitoring techniques.

In the first …

Assessing Users’ Attention Classification Accuracy From Eeg Data, Gil Olenscki Neto

USF Tampa Graduate Theses and Dissertations

Determining whether a person is attentive while performing a task is a key factor for understanding why they are achieving specific results. In addition, tracking these results is an important aspect to improving them. Quantified self is a field that consists of self-monitoring to gain a better understanding of your habits, health, and overall well-being. Examples of this method include tracking sleep patterns, daily steps, mood swings, and food intake.

This thesis aims to explore the potential of using an innovative self-quantification method that utilizes a mobile application that leverages alpha, beta, and theta waves to assess college students' attention …

Seed Mix Performance With Environmental Stressors And Invasion: Implications For Wetland Restoration, Maddie Houde, Karin Kettenring

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Seed-based revegetation is increasingly pursued in wetland restoration, but seed and seedling mortality is high and can be further limited by environmental stressors, like hydrology and salinity. The interactive effects of hydrology and salinity on native plants, especially in the presence of invasive plants, are less clear. In greenhouse and mesocosm experiments, we tested different hydrologic and salinity conditions on the growth of native seed mixes and Phragmites australis, a widespread wetland invader in North America. The greenhouse experiment tested two mixes (forb mix, graminoid mix), while mixes in the mesocosm experiment combined forbs and graminoids chosen for broad …

Artificial Intelligence Modeling Of Alzheimer's Disease And Environmental Science, Mohamed Abu Sheha

USF Tampa Graduate Theses and Dissertations

A data-driven statistical model operates as a mathematical illustration of a tangible issuefaced in reality, enabling the creation of predictions or decisions based on data. The process of utilizing probability and statistical principles in statistical models is essential for deriving meaningful conclusions from the data. The research conducted in this dissertation utilizes artificial intelligence (AI) models to integrate findings across health and environmental sci- ence.

The first research study in this dissertation, Alzheimer’s disease is a mental health issue and a brain aging dilemma that makes it difficult for older people to complete daily tasks without assistance. The physician uses …

Identification And Characterization Of Intrinsically Disordered Protein Regions, Guy Wayne Dayhoff Ii

USF Tampa Graduate Theses and Dissertations

This dissertation investigates protein intrinsic disorder and intrinsically disordered protein regions (IDPRs) through the development and application of advanced computational and experimental techniques. Chapter 1 provides an introduction to protein intrinsic disorder, outlining the historical context and fundamental concepts that highlight the importance of intrinsically disordered proteins (IDPs) and IDPRs in various biological processes. Chapter 2 focuses on the rapid prediction and analysis of protein intrinsic disorder. We introduce RIDAO (Rapid Intrinsic Disorder Analysis Online), a high-efficiency web-based tool that integrates multiple disorder predictors. RIDAO significantly outperforms existing predictors in computational efficiency, making it suitable for large-scale proteomic studies. We …

Resolving Antarctic Margin Paleoceanography For Two Different Timescales And Archives, Theresa M. King

USF Tampa Graduate Theses and Dissertations

Recent decades have seen increased rates of ice mass loss from Antarctic ice sheets, through thinning of many ice shelves around the periphery of the continent. The most vulnerable are the glacial systems that are marine-terminating and grounded below sea level, a characteristic that exposes these systems to sea level rise and warming oceans. Enhanced basal melting under the influence of warm ocean water masses can lead to thinning and retreat of glaciers, and ultimately to the acceleration of grounded ice loss. To contextualize current ice mass loss and contribute to accurate model projections for future retreat scenarios, it is …

Antarctic Atmosphere-Ocean-Ice Interactions During Past Warm Climates: An Ice-Proximal Perspective, Imogen Mireille Browne

USF Tampa Graduate Theses and Dissertations

Antarctica’s ice sheets contain 58 m of sea level equivalent ice and thus exert a fundamental control on global sea level on decadal to million-year timescales. Interactions between Antarctica’s ice sheets, regional atmospheric circulation, and the Southern Ocean influence ice sheet mass balance, sea ice formation, and deep water production, which regulate Earth’s climate. At present, Antarctica’s fringing ice shelves and outlet glaciers, particularly in West Antarctica, are losing mass as warm ocean waters move landward across the continental shelves, melting the underside of ice shelves and eroding glacial grounding lines. In East Antarctica, net ice mass gain is occurring …

Investigation Of The Use Of Recycled Concrete Aggregates In Porous Asphalt Mixture, Asad Elmagarhe

USF Tampa Graduate Theses and Dissertations

This study aims to address the national need for using recycled concrete in road pavements. This is especially important in the governmental and corporate sectors, where reducing the cost and carbon footprint of construction projects is a priority. The long-term goal is to meet the public demand for environmentally friendly infrastructure and minimize the harmful effects of waste disposal on humans and the environment.

The project focuses on using recycled concrete aggregate (RCA) in porous asphalt pavement to reduce stormwater runoff, a popular environmentally friendly road design. However, compared to regular dense asphalt mixtures, porous asphalt mixtures (PAM) are more …

Mathematical Modeling Of Tumor Response Dynamics To Predict Progression-Free Survival In Patients With Recurrent High-Grade Glioma, Daniel James Glazar

USF Tampa Graduate Theses and Dissertations

In this dissertation, I aim to develop a mathematical model describing tumor volume response dynamics to perform individual dynamic predictions of progression-free survival (PFS) on patients with recurrent high-grade glioma (rHGG).

Patients with rHGG have a dismal prognosis with median overall survival (OS) of <12 months and median PFS of <7 months. However, there is a wide heterogeneity in treatment responses. Therefore, to aid clinicians with making decisions to alter therapeutic protocol, I would like to predict patient-specific PFS.

To perform individual dynamic predictions, I employ the Claret tumor growth inhibition (TGI) model. I further develop this model by coupling it with two different survival models. Inter-patient heterogeneity is also taken into account through mixed effects, including covariate effects. Model PFS predictions were evaluated using receiver operating characteristic (ROC) curve analysis as well as Brier …

Stochastic Analytical Predictive Models For Life Sciences And Crop Production Process, Erasmus Tetteh-Bator

USF Tampa Graduate Theses and Dissertations

Analytical predictive modeling uses algorithm-based mathematical, probabilistic and statistical methods to anticipate future events by identifying patterns in past data. It is a technique for predicting outcomes and a key application of statistical analysis in real-world scenarios. Real data-driven predictive models in various fields, such as life sciences, economics,or production industry, help individuals and institutions make data-driven informed decisions, which is essential for business success, providing companies with a competitive edge.

One of every five adult deaths is caused by heart disease and one person dies every 33 from cardiovascular disease in the United States according to the Center for …

Optimizing Cybersecurity Operations Using Data-Driven Intelligence, Jalal Ghadermazi

USF Tampa Graduate Theses and Dissertations

Cybersecurity operations centers (CSOCs) play a crucial role in safeguarding organizations from cyber threats. CSOC operations are divided into two main areas: Intrusion detection systems (IDS) and security response team (SRT) operations. Machine learning (ML) and deep learning (DL) advancements have significantly improved IDSs. IDS can be either flow-based, suitable for offline analysis, or packet-based, which analyze traffic in real-time. However, packet-based IDS often treat packets independently, ignoring the sequential nature of network communication. Additionally, recent ML/DL approaches also struggle with capturing global and structural information and novel attack detection due to their reliance on labeled data. The SRT within …

Transforming Organizational Cyber Security With Artificial Intelligence And Data-Driven Optimization, Soumyadeep Hore

USF Tampa Graduate Theses and Dissertations

This dissertation presents a comprehensive framework for enhancing organizational cybersecurity through data-driven intelligence. The research integrates multiple methodologies to tackle challenges in network intrusion detection and vulnerability management within cybersecurity operations centers (CSOCs). First, the research investigates vulnerability prioritization and mitigation techniques currently employed by CSOCs. To further streamline the vulnerability prioritization and mitigation process a machine learning (ML)-based Vulnerability Priority Scoring System (VPSS) is introduced, significantly improving the prioritization and mitigation of context-sensitive vulnerabilities. The VPSS outperforms traditional methods, reducing the cumulative vulnerability exposure score by up to 30% by considering both organizational context and vulnerability severity. Next, the …

Supplementary Files For "Using Digitized Building And Weather Records To Improve The Accuracy Of Ground To Roof Snow Load Ratio Estimations", Gideon Parry, Brennan Bean

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Reliability targeted snow loads (RTLs) measure the weight in accumulated snow (i.e. snow load) that a roof is required to support to ensure the probability of failure is suf- ficiently low. This calculation has historically relied upon a probability distribution that characterizes the ratio between the annual maximum ground snow load to the annual max- imum roof snow load, a quantity referred to as Gr. The best available data for estimating Gr comes from Canadian case studies from the 1950s and 1960s. However, much of the data was never digitized, with only approximations of data being made available in scanned …

An Analysis Of (Hu)Manid Using The Usf Donated Skeletal Collection: Estimating Sex And Ancestry For Edentulous Individuals, Natalie S. Wise

USF Tampa Graduate Theses and Dissertations

The Human Mandible Identification program, (hu)MANid©, enables anthropologists to estimate the sex and ancestry of unidentified skeletal remains from metric and morphoscopic variables from the mandible. The program is suitable for a variety of anthropological contexts, including forensic casework and bioarchaeological or paleoanthropological analyses. The purpose of this research project is to test the accuracy and applicability of the (hu)MANid program on edentulous mandibles. While the authors of (hu)MANid warn against data collection for edentulous mandibles, there are many circumstances in applied forensic casework where the unidentified person is edentulous. Edentulous individuals experience alveolar resorption, which is the loss of …

Painting A New Perspective On Ordovician Echinoderm Diversity Patterns, Ohav Barak Harris

USF Tampa Graduate Theses and Dissertations

The Ordovician Period was a time of great biotic and environmental change, encompassing two important biotic events: the Great Ordovician Biodiversification Event (GOBE) and the Late Ordovician Mass Extinction (LOME). The GOBE occurred during the Middle Ordovician and was a period of rapid diversity increase for marine invertebrate groups, as lower-level taxonomic groups like families and genera came into the forefront. The Ordovician ends with the LOME, an extinction event that is thought to have occurred in two phases: an initial glaciation followed by a subsequent warming. Approximately 85% of marine species went extinct during the LOME, making it the …

Evaluation Of Reduced Graphene Oxide For Advanced Thermal Management In Microwave Electronics Packaging, Utkarsh Misra

USF Tampa Graduate Theses and Dissertations

The continuous push towards making electronic devices smaller and denser, largely driven by the demand for higher power capabilities, has led to a critical need for innovative and comprehensive methods for managing the heat these devices generate. Traditional cooling solutions for electronics often rely on methods such as copper-based layers or channels to distribute and dispel heat. However, these conventional methods and materials are becoming increasingly insufficient, especially for Radio Frequency (RF) and millimeter-wave electronics. These components are becoming ever more compact while requiring more power, thus presenting unique challenges for thermal management in their packaging.

In this thesis we …

Quantification And Diversity Of A Ubiquitous Ssdna Phage Group (Gokushovirinae) In The Red Sea Through The Polony Technique, Natalie A. Sawaya

USF Tampa Graduate Theses and Dissertations

With average concentrations of 107 virus-like particles per milliliter of seawater, viruses comprise the second largest biomass in the ocean, where they are a driving force of microbial evolution and constitute important roles in Earth’s biogeochemical cycles. Bacteriophage (phage), viruses that infect bacteria, are of particular importance in the marine ecosystem as they impact the efficiency of the microbial loop, which recycles carbon in surface waters, counteracting vertical export through the biological pump. Although double-stranded DNA phage have been researched extensively, single-stranded DNA (ssDNA) phage remain understudied, mostly due to methodological limitations.

The incorporation of rolling circle amplification (RCA) into …