Physical Sciences and Mathematics Commons^™

Testing The Molecular Cloud Paradigm For Ultra-High-Energy Gamma Ray Emission From The Direction Of Snr G106.3+2.7, R. Alfaro, C. Alvarez, J. C. Arteaga-Velázquez, D. Avila Rojas, H. A. Ayala Solares, R. Babu, E. Belmont-Moreno, A. Bernal, K. S. Caballero-Mora, T. Capistrán, A. Carramiñana, S. Casanova, U. Cotti, J. Cotzomi, S. Coutiño De León, E. De La Fuente, C. De León, D. Depaoli, P. Desiati, N. Di Lalla, R. Diaz Hernandez, B. L. Dingus, M. A. Duvernois, K. Engel, T. Ergin, C. Espinoza, K. L. Fan, K. Fang, N. Fraija, S. Fraija, J. A. Garcia-Gonzalez, F. Garfias, M. M. Gonzalez, J. A. Goodman, S. Groetsch, J. P. Harding, S. Hernandez-Cadena, I. Herzog, J. Hinton, D. Huang, F. Hueyotl-Zahuantitla, T. B. Humensky, P. Huntemeyer, S. Kaufman, D. Kieda, W. H. Lee, J. Lee, H. Leon Vargas, J. T. Linnemann, A. L. Longinotti, G. Luis-Raya, K. Malone, O. Martinez, J. Martinez-Castro, J. A. Matthews, P. Miranda-Romagnoli, J. A. Montes, E. Moreno, M. Mostafa, M. Najafi, L. Nellen, M. U. Nisa, L. Olivera-Nieto, N. Omodei, Y. Perez Araujo, E. G. Perez-Perez, C. D. Rho, D. Rosa-Gonzalezz, H. Salazar, D. Salazar-Gallegos, A. Sandoval, M. Schneider, J. Serna-Franco, A. J. Smith, Y. Son, R. W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, E. Varela, L. Villasenor, Xiaojie Wang, Z. Wang, I. J. Watson, E. Willox, S. Yu, S. Yun-Carcamo, H. Zhou

Physics Faculty Research & Creative Works

Context. Supernova remnants (SNRs) are believed to be capable of accelerating cosmic rays (CRs) to PeV energies. SNR G106.3+2.7 is a prime PeVatron candidate. It is formed by a head region, where the pulsar J2229+6114 and its boomerang-shaped pulsar wind nebula are located, and a tail region containing SN ejecta. The lack of observed gamma ray emission from the two regions of this SNR has made it difficult to assess which region would be responsible for the PeV CRs. Aims. We aim to characterize the very-high-energy (VHE, 0.1-100 TeV) gamma ray emission from SNR G106.3+2.7 by determining the morphology and …

Search For Joint Multimessenger Signals From Potential Galactic Cosmic-Ray Accelerators With Hawc And Icecube, R. Alfaro, C. Alvarez, J. C. Arteaga-Velázquez, D. Avila Rojas, H. A. Ayala Solares, R. Babu, E. Belmont-Moreno, K. S. Caballero-Mora, T. Capistrán, A. Carramiñana, S. Casanova, U. Cotti, J. Cotzomi, S. Coutiño De León, E. De La Fuente, D. Depaoli, N. Di Lalla, R. Diaz Hernandez, J. C. Diaz-Velez, K. Engel, T. Ergin, K. L. Fan, K. Fang, N. Fraija, S. Fraija, J. A. Garcia-Gonzalez, F. Garfias, M. M. Gonzalez, J. A. Goodman, S. Groetsch, J. P. Harding, S. Hernandez-Cadena, I. Herzog, D. Huang, F. Hueyotl-Zahuantitla, P. Huntemeyer, I. Iriarte, S. Kaufman, J. Lee, H. Leon Vargas, G. Luis-Raya, K. Malone, J. Martinez-Castro, J. A. Matthews, P. Miranda-Romagnoli, J. A.. Montes, E. Moreno, M. Mostafa, L. Nellen, M. U. Nisa, N. Omodei, M. Osorio, Y. Perez Araujo, E. G. Perez-Perez, C. D. Rho, D. Rosa-Gonzalez, H. Salazar, D. Salazar-Gallegos, A. Sandoval, M. Schneider, J. Serna-Franco, A. J. Smith, Y. Son, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, Xiaojie Wang, I. J. Watson, K. Whitaker, E. Willox, H. Wu, S. Yu, S. Yun-Carcamo, H. Zhou

Physics Faculty Research & Creative Works

The origin of high-energy galactic cosmic rays is yet to be understood, but some galactic cosmic-ray accelerators can accelerate cosmic rays up to PeV energies. The high-energy cosmic rays are expected to interact with the surrounding material or radiation, resulting in the production of gamma-rays and neutrinos. To optimize for the detection of such associated production of gamma-rays and neutrinos for a given source morphology and spectrum, a multimessenger analysis that combines gamma-rays and neutrinos is required. In this study, we use the MultiMission Maximum Likelihood framework with IceCube Maximum Likelihood Analysis software and HAWC Accelerated Likelihood to search for …

Some Similarity Measures On Generalized Interval-Valued Intuitionistic Fuzzy Soft Expert Sets And Their Applications In Medical Diagnosis, Afshan Qayyum, Noreen Mushtaq, Tanzeela Shaheen, Wajid Ali, Florentin Smarandache

Neutrosophic Systems with Applications

In recent years, the application of fuzzy sets has gained significant attraction in various fields, including medical diagnosis, due to their ability to manage uncertainties and imprecise information. This paper focuses on the comparative analysis of similarity measures within the realm of Generalized Interval-Valued Intuitionistic Fuzzy Soft Expert Sets (GIVIFSESs) and explores their application in the domain of medical diagnosis. Most of the important topics in fuzzy set theory are the similarity measures between the generalizations of fuzzy set theory. Similarity measures are a crucial tool which was used in data science. In this process, we measure how much the …

Left, Then Right Internal Carotid Artery Dissection: A Case Report, Jeffrey M. Kalczynski, John Douds, Michael E. Silverman

SKMC Student Presentations and Publications

INTRODUCTION: We present a unique case of a patient who presented to the emergency department with stroke-like symptoms found to have a spontaneous, left-sided internal carotid artery dissection (ICAD).

CASE REPORT: The patient was treated successfully with thrombectomy and subsequently developed contralateral symptoms caused by a right-sided ICAD. This was managed with a second contra-lateral thrombectomy. The patient's course was complicated by persistent and mild hypotension, postulated to be secondary to bilateral carotid baroreceptor trauma from the dissections.

CONCLUSION: This case highlights the importance of close neurological monitoring for patients, preferably in a neurologic critical care setting, during and after …

Enhancing Post Silicon Visibility Using Language Modelling Techniques, Nathaniel Joseph Fender

USF Tampa Graduate Theses and Dissertations

The debugging phase is a critical time in the development of a new system on chip product. Specifically, the post-silicon validation phase is one of the most important, as it allows engineers to test the behavior of a device in a real world setting. However, the issue of noisy or incomplete data is a frequent issue when attempting to debug an SoC design during this step. This thesis examines the utility of utilizing machine learning models for the purpose of repairing missing data in a system trace. We trained various models using the transformer architecture to identify missing data in …

Predicting Human Chess Moves With Large Language Models, Benjamin Kreiger

USF Tampa Graduate Theses and Dissertations

As artificial intelligence (AI) surpasses human performance in more tasks, the interest in leveraging and collaborating with this technology for greater productivity continues to grow. However, the black-box nature of current AI can make it difficult to interpret and unsuitable to perform tasks that are more complex and require human intuition. This has led to the pursuit of AI systems that can model individual behavior. Chess offers an ideal environment to explore this task due to its complexity, structure, and the abundance of data containing unique human decision-making examples. Given that a chess game can be fully represented with text, …

Targeted Study Of The Effect Of Yeast Strain On Volatile Compounds Produced In Sorghum Beer, Drew Budner, Joseph Carr, Brett Serafini, Samantha Tucker, Elisabeth Dieckman-Meyer, Lindsey Bell, Katherine A. Thompson-Witrick

Chemistry

An increase in the consumer demand and the availability of gluten-free products has led to several brewers investigating brewing with grains other than barley. The primary grain of choice has been sorghum. These new gluten-free beers have a unique flavor and aroma, which previous research has shown is the result of differences in concentration for key chemical compounds, including ethyl butyrate, butyl acetate, isoamyl acetate, ethyl caproate, hexyl acetate, 1-octanol, nonanal, ethyl octanoate, and ethyl decanoate. This study focused looked at the influence different strains of yeast had on the concentration of these key compounds. Beer was brewed using either …

Neutrosophic Logic-Based Crop Yield Prediction And Risk Assessment Using Least Squares Regression, M. Srikanth, R.N.V. Jagan Mohan, M. Chandra Naik

Neutrosophic Systems with Applications

Agriculture faces significant challenges due to climate change and unpredictable environmental factors, which impact crop yields and threaten food security. This study proposes a novel approach to crop yield prediction and risk assessment using neutrosophic logic and least squares regression. By integrating these methods, we aim to improve accuracy in predicting crop losses under uncertain conditions. The model classifies crops based on profitability and environmental risks, utilizing the independence test to evaluate the relationships between crop attributes. Our approach leverages deep learning techniques, such as restricted Boltzmann machines (RBM), to enhance the analysis of crop data and provide farmers with …

Noncontact Diffuse Reflectance Spectroscopy Of Synovial Fluid Samples For Rapid Identification Of Infections, Erin E. Drewke, Robert L. Brand, Caroline G. Geels, Hanna K. Jensen, Kevin Wong, Jarret D. Sanders, Narasimhan Rajaram

Biomedical Engineering Faculty Publications and Presentations

Severe joint infections, such as septic arthritis, require rapid diagnostic testing of the synovial fluid aspirated from joints level so that a surgical team can be assembled quickly. We present a diffuse reflectance spectroscopy (DRS) system for noncontact determination of infection. Using a light-tight syringe holder and fiber optic probe, diffusely reflected light from 475 to 655 nm was acquired from 18 patient samples through the wall of a syringe in a noncontact and sterile manner. We determined the reflectance ratios at two different wavelengths—R ₄₉₀/R ₆₀₀ and R ₅₈₀/R ₆₀₀ and found statistically significant …

Please Understand My Disability: An Analysis Of Youtubers’ Discourse On Disability Challenges, Shuo Niu

Computer Science

Video-sharing platforms offer a unique avenue for people with disabilities (PWDs) to highlight their experiences, including the challenges and accessibility barriers they face. While creators with disabilities effectively use these platforms to share their life struggles and advocate for societal changes, the scope of research exploring the nature of the discourse activities related to disability challenges remains limited. Our study addresses this gap by conducting a comprehensive qualitative content analysis of 468 videos posted by YouTubers with a range of disabilities, including vision, speech, mobility, hearing, and cognitive and neural impairments. Our findings reveal a predominant discussion on stigma and …

Toward A Responsible Future: Recommendations For Ai-Enabled Clinical Decision Support, Steven Labkoff, Bilikis Oladimeji, Joseph Kannry, Anthony Solomonides, Russell Leftwich, Eileen Koski, Amanda L Joseph, Monica Lopez-Gonzalez, Lee A Fleisher, Kimberly Nolen, Sayon Dutta, Deborah R Levy, Amy Price, Paul J Barr, Jonathan D Hron, Baihan Lin, Gyana Srivastava, Nuria Pastor, Unai Sanchez Luque, Tien Thi Thuy Bui, Reva Singh, Tayler Williams, Mark G Weiner, Tristan Naumann, Dean F Sittig, Gretchen Purcell Jackson, Yuri Quintana

Faculty, Staff and Student Publications

BACKGROUND: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging.

OBJECTIVES: This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients.

MATERIALS AND METHODS: In May …

Learning Problems Related To Stochastic Differential Equations, Jinpu Zhou

LSU Doctoral Dissertations

Stochastic differential equations (SDEs) are essential for modeling systems influenced by both deterministic dynamics and random fluctuations, with applications in a wide variety of disciplines. This thesis develops a Bayesian framework for nonparametric learning in SDEs, addressing key challenges in inference, particularly when dealing with complex systems and incomplete data. The thesis begins by establishing a theoretical foundation in optimization over Hilbert spaces, including a generalized representer theorem to address infinite-dimensional optimization problems encountered in nonparametric inference. Building on this, we introduce a Bayesian framework with shrinkage priors to learn drift functions from high-frequency data. Bayesian approach incorporates low-cost sparse …

Digital India, Rajendra Srivastava, Vijay Shankar S, Aman Rajeev Kulkarni

Asian Management Insights

At the heart of India’s ongoing digital transformation lies a ‘perfect storm’ of pivotal elements: a robust telecom industry, groundbreaking digital technologies, an evolving payments ecosystem, and widespread smartphone adoption. Together, these elements have redefined connectivity, communication, and financial transactions, positioning India as a leader in the digital age.

The Path To Greening Our Future, Havovi Joshi

Asian Management Insights

More than half of humanity currently lives in urban areas, and the United Nations predicts that figure will reach 70 percent by 2050. Cities worldwide already generate a significant amount of solid waste annually, adding to vexing issues that the global community is trying to address–demand for transportation, air pollution, access to public open spaces, urban sprawl, and general sustainability challenges. Throw in global warming and the copious greenhouse gas (GHG) emissions borne of construction activities, and the challenge of creating the necessary urban infrastructure to cope comes into sharp focus.

Why Isn’T Formula 1 Going Electric?, Terry Van Gevelt

Asian Management Insights

Electric vehicles are not the only sustainable automotive option.

1. While electric vehicles (EVs) are marketed as ‘zero-emission’, their overall environmental impact and battery production all contribute to their lifecycle emissions. In fact, their widespread adoption needs significant infrastructural changes like installing new charging networks and upgrading power grids, which come with substantial environmental and financial costs.

2. Considering a diverse array of energy alternatives, including synthetic e-fuels, could offer Singapore a that is tailored to the specific needs and infrastructural realities of the country and region.

Getting On Board With Incentivising Esg, Shai Ganu

Asian Management Insights

What gets rewarded gets measured and done. Shai Ganu, Managing Director and Global Leader of the Executive Compensation and Board Advisory business at WTW, discusses the increasing adoption of Environmental, Social, and Governance (ESG) metrics in structuring executive compensation. He explores how incorporating ESG goals into incentive plans drives accountability and aligns leadership performance with long-term sustainability objectives.

A Finite-Horizon Approach To Active Level Set Estimation, Phillip Kearns, Bruno Jedynak, John Lipor

Mathematics and Statistics Faculty Publications and Presentations

We consider the problem of active learning for level set estimation (LSE), where the goal is to localize all regions where a function of interest lies above/below a given threshold as quickly as possible. We present a finitehorizon search procedure to perform LSE in one dimension while optimally balancing both the final estimation error and the distance traveled during active learning for a fixed number of samples. A tuning parameter is used to trade off between the estimation accuracy and distance traveled. We show that the resulting optimization problem can be solved in closed form and that the resulting policy …

Characterization Of Aromatic Stationary Phases For Uses In High Performance Liquid Chromatography, Anastasia Davis

Honors Theses

High Performance Liquid Chromatography (HPLC) is an analytical chemist technique used to separate a sample into its components to characterize and study a specific molecule or compound. Traditionally, High-Performance Liquid Chromatography in different industries, such as the environmental and pharmaceutical fields, uses stationary phases that are already well characterized, such as the C18 stationary phase for separation. However, aromatic stationary phases have recently been produced, which have phenyl groups bonded to the interior surface of the column. Still, they have not been well characterized because of how modern they are. This project characterized several aromatic stationary phases (Biphenyl, pentafluorophenyl, and …

Collectively Advancing Deep Learning For Animal Detection In Drone Imagery: Successes, Challenges, And Research Gaps, Daniel Axford, Ferdous Sohel, Mathew A. Vanderklift, Amanda J. Hodgson

Research outputs 2022 to 2026

Drones have emerged as a powerful tool in animal detection, significantly advancing wildlife monitoring, conservation, and management by capturing high-resolution, real-time imagery over areas often inaccessible or challenging for human observers to reach. However, manual analysis of drone imagery for animal detection is labour-intensive and time-consuming. The application of deep learning methods, particularly convolutional neural networks, in automating animal detection from drone imagery has the potential to revolutionise wildlife monitoring, conservation, and management protocols. This review provides a comprehensive overview of the increasing use and prospects of deep learning in animal detection using drone imagery. It explores successful applications of …

Exploring The Family Well-Being Of Dual-Coast Guard Marriages In The Philippines, Marie Shermaine Andrade

World Maritime University Dissertations

No abstract provided.

Building Stronger Maritime Governance In Belize : A Collaborative And Organizational Approach, Jasmine Deneen Bellini

World Maritime University Dissertations

No abstract provided.

Human Capital Development : Bridging The Skills Gap In The Maritime Administration Of Namibia, Agnes Matheus

World Maritime University Dissertations

No abstract provided.

Analysis Of The Impact Of Mass On The International Regulatory Framework In The Example Of Unclos Terminology : Issues, Legal Challenges, Possible Solutions, Akbar Akbarov

World Maritime University Dissertations

No abstract provided.

Acci̇Dental Oi̇L Polluti̇On From Tankers İN The Caspi̇An Sea : Problem Causes And Lessons Learned, Emin Sadirov

World Maritime University Dissertations

No abstract provided.

Understanding Cybersecurity Perception In The Maritime Sector Of Nigeria : A Comparative Analysis, Lawal Mohammed Abdulrasaq

World Maritime University Dissertations

No abstract provided.

A Prominent Future Fuel : Methanol & Risk Assessment Of Methanol Fuel System Of Tanker As A Case Study, Jaeho Jin

World Maritime University Dissertations

No abstract provided.

Assessment Of The Impact Of Marine Pollution In Maputo Port, Mozambique, Lina Maria Elias Vasco

World Maritime University Dissertations

No abstract provided.

A Study On The Risk Assessment Of Japanese Domestic Passenger Vessel Accident, Miki Yanagisawa

World Maritime University Dissertations

No abstract provided.

Evaluation Of Port Reception Facilities And Ship-Generated Solid Waste Management : A Case Study Of Apapa Port, Nigeria., Abdullahi Gambasha Barau

World Maritime University Dissertations

No abstract provided.

Against The Substitutive Approach To Ai In Healthcare, Rand Hirmiz

Research Collection School of Social Sciences

Paul Bloom has famously argued against the need for empathy in clinicians, while Sally Dalton-Brown has argued that AI need not be capable of empathy to be a good carer. In this paper, the capacity for AI to substitute for human clinicians is assessed from a bioethical perspective, primarily through the evaluation of the arguments put forth by Dalton-Brown and Bloom concerning empathy in healthcare. In opposition to both Bloom and Dalton-Brown, this paper argues that (1) empathy is essential to providing good care or deep care (that is, care that goes beyond the mere fulfilment of medical tasks), (2) …