Physical Sciences and Mathematics Commons^™

Forecasting Remission Time Of A Treatment Method For Leukemia As An Application To Statistical Inference Approach, Mahmoud Mansour, Rashad El-Sagheer, Ahmed Galal Attia, Beha S. El-Desouky Prof.

Basic Science Engineering

In this paper, Weibull-Linear Exponential distribution (WLED) has been investigated whether being it is a well-fit distribution to a clinical real data. These data represent the duration of remission achieved by a certain drug used in the treatment of leukemia for a group of patients. The statistical inference approach is used to estimate the parameters of the WLED through the set of the fitted data. The estimated parameters are utilized to evaluate the survival and hazard functions and hence assessing the treatment method through forecasting the duration of remission times of patients. A two-sample prediction approach has been applied to …

From The Organismal To Biosphere Levels: Environmental Impacts On The Amphibian Microbiota, Obed Hernandez-Gomez, Jessica Hua

Natural Sciences and Mathematics | Faculty Scholarship

This review summarizes the role of environmental factors on amphibian microbiotas at the organismal, population, community, ecosystem, and biosphere levels. At the organismal-level, tissue source, disease status, and experimental manipulations were the strongest predictors of variation in amphibian microbiotas. At the population-level, habitat quality, disease status, and ancestry were commonly documented as drivers of microbiota turnover. At the community-level, studies focused on how species’ niche influence microbiota structure and function. At the ecosystem-level, abiotic and biotic reservoirs were important contributors to microbiota structure. At the biosphere-level, databases, sample banks, and semi-natural experiments were commonly used to describe microbiota assembly mechanisms …

Success (Studying Underlying Characteristics Of Computing And Engineering Student Success) Survey: Non-Cognitive And Affective Profiles In Engineering And Computing Students At Utep (2018-2022), Sanga Kim, Christian Teran Lopez, Andres Segura, Gabriel Miki

Departmental Technical Reports (CS)

No abstract provided.

Extreme Differentiation Along Multiple Liquid Lines Of Descent In Strongly Peralkaline Magma Series At Pantelleria (Italy), John C. White, Ray Macdonald, Bogusław Bagiński, Katarzyna M. Liszewska

EKU Faculty and Staff Scholarship

The liquid line of descent from trachyte to pantellerite is controlled primarily by fractional crystallization of alkali feldspar, with whole rock compositions following a fractionation path along the ‘thermal valley’ in the peralkaline haplogranite system Qz-Ab-Or-Ac-Ns and terminating at a minimum on the feldspar-quartz cotectic. Although whole-rock compositions for different pantelleritic suites follow nearly identical paths in a Qz-Ab-Or projection that terminate near the experimental minimum (Qz40.5Or34.5Ab25 at 100 MPa, projected from Ac-Ns), matrix glass from samples with near-minimum compositions record extreme differentiation and form a ‘cotectic delta’ beyond the terminus of the ‘thermal valley’. Although each glass trend shows …

A Quantum Approach To Language Modeling, Constantijn Van Der Poel

Dissertations, Theses, and Capstone Projects

This dissertation consists of six chapters. . . Chapter 1: We introduce language modeling, outline the software used for this thesis, and discuss related work. Chapter 2: We will unpack the transition from classical to quantum probabilities, as well as motivate their use in building a model to understand language-like datasets. Chapter 3: We motivate the Motzkin dataset, the models we will be investigating, as well as the necessary algorithms to do calculations with them. Chapter 4: We investigate our models’ sensitivity to various hyperparameters. Chapter 5: We compare the performance and robustness of the models. Chapter 6: We conclude …

Inducible Nitric Oxide Synthase Embedded In Alginate/Polyethyleneimine Hydrogel As A New Platform To Explore No-Driven Modulation Of Biological Function, Shaimaa Maher, Lauren A. Smith, Celine A. El-Khoury, Haitham F. Kalil, Khalid Sossey-Alaoui, Mekki Bayachou

Chemistry Faculty Publications

Nitric oxide (NO), a small free radical molecule, turned out to be pervasive in biology and was shown to have a substantial influence on a range of biological activities, including cell growth and apoptosis. This molecule is involved in signaling and affects a number of physiologic functions. In recent decades, several processes related to cancer, such as angiogenesis, programmed cell death, infiltration, cell cycle progression, and metastasis, have been linked with nitric oxide. In addition, other parallel work showed that NO also has the potential to operate as an anti-cancer agent. As a result, it has gained attention in cancer-related …

First-Principles Calculations On The Electronic Structure, Mechanical, Vibrational, And Thermal Properties Of The Ca₃Bin Antiperovskite Alloy, Reem Maher Mohamad

Theses

Antiperovskites are the counterparts of perovskites. They have diverse properties that make them physically rich and technologically relevant. In the recent years, the alkaline earth based antiperovskites, especially the ones with small semiconductor bandgap, have captured tremendous attention due to their properties which make them efficient to be used in optoelectronic and thermoelectric applications. In this thesis, we are shading light on the alkaline antiperovskite 𝐶𝑎₃𝐵𝑖𝑁 due to its narrow bandgap. Thus, it can be considered as a promising candidate for thermoelectric and optoelectronic applications. Specifically, it is used to harvest waste thermal energy into electricity at low …

Sustainability Hub Newsletter - February 2023, Jacqueline Jergensen, Neyda Gilman, Jennifer Embree

Library Sustainability Resources

This issue of the Sustainability Hub Newsletter shares tips on what seeds you can start planting indoors and inspiration on which plants to grow this season! Keep reading to learn about planting by the moon, new resources, and important announcements!

Remote Internal Wave Forcing Of Regional Ocean Simulations Near The U.S. West Coast, Oladeji Q. Siyanbola, Maarten C. Buijsman, Audrey Delpech, Lionel Renault, Roy Barkan, Jay F. Shriver, Brian K. Arbic, James C. Mcwilliams

Faculty Publications

Low mode internal waves are able to propagate across ocean basins and modulate ocean dynamics thousands of kilometers away from their generation sites. In this study, the impact of remotely generated internal waves on the internal wave energetics near the U.S. West Coast is investigated with realistically forced regional ocean simulations. At the open boundaries, we impose high-frequency oceanic state variables obtained from a global ocean simulation with realistic atmospheric and astronomical tidal forcing. We use the Discrete Fourier Transform (DFT) technique in separating ingoing and outgoing internal tide energy fluxes at the open boundaries in order to quantify internal …

Prediction Of Wilms’ Tumor Susceptibility To Preoperative Chemotherapy Using A Novel Computer-Aided Prediction System, Israa Sharaby, Ahmed Alksas, Ahmed Nashat, Hossam Magdy Balaha, Mohamed Shehata, Mallorie Gayhart, Ali Mahmoud, Mohammed Ghazal, Ashraf Khalil, Rasha T. Abouelkheir, Ahmed Elmahdy, Ahmed Abdelhalim, Ahmed Mosbah, Ayman El-Baz

All Works

Wilms’ tumor, the most prevalent renal tumor in children, is known for its aggressive prognosis and recurrence. Treatment of Wilms’ tumor is multimodal, including surgery, chemotherapy, and occasionally, radiation therapy. Preoperative chemotherapy is used routinely in European studies and in select indications in North American trials. The objective of this study was to build a novel computer-aided prediction system for preoperative chemotherapy response in Wilms’ tumors. A total of 63 patients (age range: 6 months–14 years) were included in this study, after receiving their guardians’ informed consent. We incorporated contrast-enhanced computed tomography imaging to extract the texture, shape, and functionality-based …

Intelligent Health Care And Diseases Management System: Multi-Day-Ahead Predictions Of Covid-19, Ahed Abugabah, Farah Shahid

All Works

The rapidly growing number of COVID-19 infected and death cases has had a catastrophic worldwide impact. As a case study, the total number of death cases in Algeria is over two thousand people (increased with time), which drives us to search its possible trend for early warning and control. In this paper, the proposed model for making a time-series forecast for daily and total infected cases, death cases, and recovered cases for the countrywide Algeria COVID-19 dataset is a two-layer dropout gated recurrent unit (TDGRU). Four performance parameters were used to assess the model’s performance: mean absolute error (MAE), root …

The Impact Of Objectively Recorded Smartphone Usage And Emotional Intelligence On Problematic Internet Usage, Sameha Alshakhsi, Khansa Chemnad, Mohamed Basel Almourad, Majid Altuwairiqi, John Mcalaney, Raian Ali

All Works

This study examined the effects of gender, age, objective smartphone usage data, and Emotional Intelligence (EI) on Problematic Internet Use (PIU) and its components (obsession, neglect, and control disorder). The study relied on objective data of smartphone usage as a representative of technology use collected by a monitoring application of smartphone usage. PIU and EI were measured through the Problematic Internet Usage Questionnaire short form (PIUQ-SF-6) and Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), respectively. The current cross-sectional study was carried out with 268 participants (Female: 61.6%, ages from 15 to 64) from ten different countries. The analysis was performed using …

Carla+: An Evolution Of The Carla Simulator For Complex Environment Using A Probabilistic Graphical Model, Sumbal Malik, Manzoor Ahmed Khan, Aadam, Hesham El-Sayed, Farkhund Iqbal, Jalal Khan, Obaid Ullah

All Works

In an urban and uncontrolled environment, the presence of mixed traffic of autonomous vehicles, classical vehicles, vulnerable road users, e.g., pedestrians, and unprecedented dynamic events makes it challenging for the classical autonomous vehicle to navigate the traffic safely. Therefore, the realization of collaborative autonomous driving has the potential to improve road safety and traffic efficiency. However, an obvious challenge in this regard is how to define, model, and simulate the environment that captures the dynamics of a complex and urban environment. Therefore, in this research, we first define the dynamics of the envisioned environment, where we capture the dynamics relevant …

Augmenting Ccam Infrastructure For Creating Smart Roads And Enabling Autonomous Driving, M. Jalal Khan, Manzoor Ahmed Khan, Obaid Ullah, Sumbal Malik, Farkhund Iqbal, Hesham El-Sayed, Sherzod Turaev

All Works

Autonomous vehicles and smart roads are not new concepts and the undergoing development to empower the vehicles for higher levels of automation has achieved initial milestones. However, the transportation industry and relevant research communities still require making considerable efforts to create smart and intelligent roads for autonomous driving. To achieve the results of such efforts, the CCAM infrastructure is a game changer and plays a key role in achieving higher levels of autonomous driving. In this paper, we present a smart infrastructure and autonomous driving capabilities enhanced by CCAM infrastructure. Meaning thereby, we lay down the technical requirements of the …

An Enhanced Cloud-Native Deep Learning Pipeline For The Classification Of Network Traffic, Ahmed Sobhy Elkenawy

Theses and Dissertations

In a rapidly changing world, the way of solving real-world problems has changed to leverage the power of the advancements in multiple fields. Cloud-native computing approaches can be utilized with deep learning techniques to provide solutions in several important areas. For instance, with the emergence of the pandemic, much dependence on modern technologies came out as a replacement for face-to-face interaction. Deep learning can reach a high level of accuracy, which makes it very effective in the support of modern services and technologies. However, there are some challenging issues because deep learning requires many large-scale experiments, which demand a lot …

An Evaluation Of Avian Influenza Virus Whole-Genome Sequencing Approaches Using Nanopore Technology, Hon S. Ip, Sarah Uhm, Mary Lea Killian, Mia K. Torchetti

United States Department of Agriculture Wildlife Services: Staff Publications

As exemplified by the global response to the SARS-CoV-2 pandemic, whole-genome sequencing played an important role in monitoring the evolution of novel viral variants and provided guidance on potential antiviral treatments. The recent rapid and extensive introduction and spread of highly pathogenic avian influenza virus in Europe, North America, and elsewhere raises the need for similarly rapid sequencing to aid in appropriate response and mitigation activities. To facilitate this objective, we investigate a next-generation sequencing platform that uses a portable nanopore sequencing device to generate and present data in real time. This platform offers the potential to extend in-house sequencing …

Chiral Photocurrent In A Quasi-1d Tis3 (001) Phototransistor, Simeon J. Gilbert, Mingxing Li, Jia-Shiang Chen, Hemian Yi, Alexey Lipatov, Jose Avila, Alexander Sinitskii, Maria C. Asensio, Peter A. Dowben, Andrew J. Yost

Department of Physics and Astronomy: Faculty Publications

The presence of in-plane chiral effects, hence spin–orbit coupling, is evident in the changes in the photocurrent produced in a TiS₃(001) field-effect phototransistor with left versus right circularly polarized light. The direction of the photocurrent is protected by the presence of strong spin–orbit coupling and the anisotropy of the band structure as indicated in NanoARPES measurements. Dark electronic transport measurements indicate that TiS₃ is n-type and has an electron mobility in the range of 1–6 cm²V⁻¹s⁻¹. I–V measurements under laser illumination indicate the photocurrent exhibits a bias directionality dependence, reminiscent of …

Exact Parallel Waves In General Relativity, Cian Roche, Amir Babak Aazami, Carla Cederbaum

Mathematics

We conduct a review of the basic definitions and the principal results in the study of wavelike spacetimes, that is spacetimes whose metric models massless radiation moving at the speed of light, focusing in particular on those geometries with parallel rays. In particular, we motivate and connect their various definitions, outline their coordinate descriptions and present some classical results in their study in a language more accessible to modern readers, including the existence of “null coordinates” and the construction of Penrose limits. We also present a thorough summary of recent work on causality in pp-waves, and describe progress in addressing …

A Stronger Strong Schottky Lemma For Euclidean Buildings, Michael E. Ferguson

Dissertations, Theses, and Capstone Projects

We provide a criterion for two hyperbolic isometries of a Euclidean building to generate a free group of rank two. In particular, we extend the application of a Strong Schottky Lemma to buildings given by Alperin, Farb and Noskov. We then use this extension to obtain an infinite family of matrices that generate a free group of rank two. In doing so, we also introduce an algorithm that terminates in finite time if the lemma is applicable for pairs of certain kinds of matrices acting on the Euclidean building for the special linear group over certain discretely valued fields.

Analyzing Relationships With Machine Learning, Oscar Ko

Dissertations, Theses, and Capstone Projects

Procedurally, this project aims to take a dataset, analyze it, and offer insights to the audience in an easy-to-digest format. Conceptually, this project will seek to explore questions like: “Do couples that meet through online dating or dating apps have higher or lower quality relationships?”, “Can any features in this dataset help predict how a subject would rate their relationship quality?”, and “What other insights can I derive from using machine learning for exploratory analysis?” The intended audience for this project is anyone interested in romantic relationships or machine learning.

The dataset is from a Stanford University survey, “How Couples …

Scalable And Globally Optimal Generalized L1 K-Center Clustering Via Constraint Generation In Mixed Integer Linear Programming, Aravinth Chembu, Scott Sanner, Hassan Khurran, Akshat Kumar

Research Collection School Of Computing and Information Systems

The k-center clustering algorithm, introduced over 35 years ago, is known to be robust to class imbalance prevalent in many clustering problems and has various applications such as data summarization, document clustering, and facility location determination. Unfortunately, existing k-center algorithms provide highly suboptimal solutions that can limit their practical application, reproducibility, and clustering quality. In this paper, we provide a novel scalable and globally optimal solution to a popular variant of the k-center problem known as generalized L_1 k-center clustering that uses L_1 distance and allows the selection of arbitrary vectors as cluster centers. We show that this clustering objective …

Translation Of: Familles De Surfaces Isoparamétriques Dans Les Espaces À Courbure Constante, Annali Di Mat. 17 (1938), 177–191, By Élie Cartan., Thomas E. Cecil

Mathematics and Computer Science Department Faculty Scholarship

English title: Families of isoparametric surfaces in spaces of constant curvature

This is an English translation of the article "Familles de surfaces isoparamétriques dans les espaces à courbure constante" which was originally published in Annali di Matematica 17, 177–191 (1938), by Élie Cartan.

A note from Thomas E. Cecil, translator: This is an unofficial translation of the original paper which was written in French. All references should be made to the original paper.

Mathematics Subject Classification Numbers: 53C40, 53C42, 53B25

Poster: Userland Containers For Mobile Systems, Isaac Ahlgren, Victor Rakotondranoro, Yasin N. Silva, Eric Chan-Tin, George K. Thiruvathukal, Neil Klingensmith

Computer Science: Faculty Publications and Other Works

Mobile platforms are not rising to their potential as ubiquitous computers, in large part because of the constraints we impose on their apps in the name of security. Mobile operating systems have long struggled with the challenge of isolating untrusted apps. In pursuit of a secure runtime environment, Android and iOS isolate apps inside a gulag of platform-imposed programming languages and runtime libraries, leaving few design decisions to the application developers. These thick layers of custom software eschew app portability and maintainability, as development teams must continually tweak their apps to support modifications to the OS's runtime libraries. Nonstandard and …

Towards Machine Learning-Based Fpga Backend Flow: Challenges And Opportunities, Imran Taj, Umer Farooq

All Works

Field-Programmable Gate Array (FPGA) is at the core of System on Chip (SoC) design across various Industry 5.0 digital systems—healthcare devices, farming equipment, autonomous vehicles and aerospace gear to name a few. Given that pre-silicon verification using Computer Aided Design (CAD) accounts for about 70% of the time and money spent on the design of modern digital systems, this paper summarizes the machine learning (ML)-oriented efforts in different FPGA CAD design steps. With the recent breakthrough of machine learning, FPGA CAD tasks—high-level synthesis (HLS), logic synthesis, placement and routing—are seeing a renewed interest in their respective decision-making steps. We focus …

Direct Air Capture, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about direct air capture (DAC), a carbon capture technology that will reduce and remove carbon dioxide from the atmosphere. DAC supports environmental sustainability, North Dakota’s economy, and boosts the energy industry.

City Of Tampa Tree Canopy And Urban Forest Analysis 2021, Shawn M. Landry, Andrew K. Koeser, Rebecca Zarger, Kira Rib, Allyson Salisbury, Robert J. Northrop, Michael G. Andreu, Allison Bednar, Zach Freeman

School of Geosciences Faculty and Staff Publications

This report summarizes the fourth tree canopy and urban forest analysis conducted for the City of Tampa and represents the year 2021. The City of Tampa tree ordinance (Ord. No. 2006-74, § 9, 3-23-06) requires an assessment of the tree canopy and urban forest every five years (beginning in 20061). In an effort to reduce concerns over bias, this work has been conducted by a collaborative team from the University of South Florida and the University of Florida following established USDA Forest Service protocols.

This report provides detailed information about the current size, composition, health, and distribution of Tampa’s urban …

Pore Connectivity Influences Mass Transport In Natural Rocks: Pore Structure, Gas Diffusion And Batch Sorption Studies, Qinhong Hu

Earth & Environmental Sciences Datasets

The Excel file contains supplementary dataset, in various sheets, for a manuscript entitled "Pore connectivity influences mass transport in natural rocks: Pore structure, gas diffusion and batch sorption studies" The Word file of "Data Dictonary" briefly explained the data in each sheet of the Excel file, from different measurements as detailed in the manuscript. Authors: Xiaoqing Yuan, Qinhong Hu (maxhu@uta.edu), Xiang Lin, Chen Zhao, Qiming Wang, Yukio Tachi, Yuta Fukatsu, Shoichiro Hamamoto, Marja Siitari-Kauppia, and Xiaodong Li

Road Accessibility From County Seat Under Flooding: Middle Peninsula, Northern Neck, Southside, Molly Mitchell, Jessica Hendricks, Daniel Schatt, Marcia Berman

Data

The impacts of recurrent flooding on roadways present challenging social and economic considerations for all coastal jurisdictions. Maintenance, public and private accessibility, evacuation routes, and emergency services are just a few of the common themes local governments are beginning to address for low-lying roadways currently known to flood. The project implements a protocol developed by CCRM to analyze the level at which road flooding may impact communities and their ability to reach key locations at periodic intervals; through the year 2100 in coastal Virginia. Using a network analysis, road accessibility is evaluated at different levels of flooding (at 0.1 meter …

Engineering A Microbiosphere To Clean Up The Ocean – Inspiration From The Plastisphere, Khulood A. Alnahdi, Laila W. Alali, Mezna K. Suwaidan, M. Kalim Akhtar

All Works

Plastic is a ubiquitous material that has become an essential part of our lives. More than one hundred million tons of plastic has accumulated in the world’s oceans as a result of poor waste management. This plastic waste gradually fragments into smaller pieces known as microplastics and nanoplastics. These small plastic particles can cause significant damage to marine ecosystems, and negatively impact human health. According to a recent review of international patents, the majority of ocean-cleaning inventions are limited to microplastics larger than 20 μm. Furthermore, such technologies are ineffective for nanoplastics, which measure less than 1000 nm, or even …

Naming Venus: An Exploration Of Goddesses, Heroines, And Famous Women, Kavya Beheraj

Dissertations, Theses, and Capstone Projects

Humans have been observing and romanticizing Venus for more than 5,000 years. However, mapping its surface has nearly always been impossible, since the planet is shrouded in thick clouds. A breakthrough came just fifty years ago with the invention of radar imaging, leading to the discovery (and naming) of hundreds of new features in a relatively short length of time.

The rapid naming of Venus is a case study on the impact of planetary nomenclature — the process of naming features on other worlds. While the act of naming streamlines communication and humanizes alien landscapes, it is subject to bias, …