Digital Commons Network^™

Deep Learning-Based Cad System For Predicting The Covid-19 X-Ray Images, Aqeel R. Talib, Hana’ M. Ali

Karbala International Journal of Modern Science

According to World Health Organization data, Coronavirus (COVID-19) has infected about 660, 378, 145 patients around the world. It is nonetheless difficult for physicians to detect COVID-19 infections out of CT or X-ray radiographs. Thus, several computer-aided diagnosis (CAD) systems based on deep learning and radiographs were developed to detect COVID-19 infections. However, the majority of approaches considered small datasets, which is ineligible to provide diverse COVID-19 radiographs. This work utilizes a massive number of X-ray radiographs, and compared standard CNN, DenseNet-121, and GoogLeNet for isolating COVID-19 infections out from normal and other pneumonia radiographs. The dataset in this work …

Systematic Design And Data-Driven Evaluation Of Social Determinants Of Health Ontology (Sdoho), Yifang Dang, Fang Li, Xinyue Hu, Vipina K Keloth, Meng Zhang, Sunyang Fu, Muhammad F Amith, J Wilfred Fan, Jingcheng Du, Evan Yu, Hongfang Liu, Xiaoqian Jiang, Hua Xu, Cui Tao

Faculty, Staff and Student Publications

Objective: Social determinants of health (SDoH) play critical roles in health outcomes and well-being. Understanding the interplay of SDoH and health outcomes is critical to reducing healthcare inequalities and transforming a "sick care" system into a "health-promoting" system. To address the SDOH terminology gap and better embed relevant elements in advanced biomedical informatics, we propose an SDoH ontology (SDoHO), which represents fundamental SDoH factors and their relationships in a standardized and measurable way.

Material and methods: Drawing on the content of existing ontologies relevant to certain aspects of SDoH, we used a top-down approach to formally model classes, relationships, and …

Federated Generalized Linear Mixed Models For Collaborative Genome-Wide Association Studies, Wentao Li, Han Chen, Xiaoqian Jiang, Arif Harmanci

Faculty, Staff and Student Publications

Federated association testing is a powerful approach to conduct large-scale association studies where sites share intermediate statistics through a central server. There are, however, several standing challenges. Confounding factors like population stratification should be carefully modeled across sites. In addition, it is crucial to consider disease etiology using flexible models to prevent biases. Privacy protections for participants pose another significant challenge. Here, we propose distributed Mixed Effects Genome-wide Association study (

A Lifecycle Framework Illustrates Eight Stages Necessary For Realizing The Benefits Of Patient-Centered Clinical Decision Support, Dean F Sittig, Aziz Boxwala, Adam Wright, Courtney Zott, Priyanka Desai, Rina Dhopeshwarkar, James Swiger, Edwin A Lomotan, Angela Dobes, Prashila Dullabh

Faculty, Staff and Student Publications

The design, development, implementation, use, and evaluation of high-quality, patient-centered clinical decision support (PC CDS) is necessary if we are to achieve the quintuple aim in healthcare. We developed a PC CDS lifecycle framework to promote a common understanding and language for communication among researchers, patients, clinicians, and policymakers. The framework puts the patient, and/or their caregiver at the center and illustrates how they are involved in all the following stages: Computable Clinical Knowledge, Patient-specific Inference, Information Delivery, Clinical Decision, Patient Behaviors, Health Outcomes, Aggregate Data, and patient-centered outcomes research (PCOR) Evidence. Using this idealized framework reminds key stakeholders that …

Additive Effects Of Cyclic Peptide [R4w4] When Added Alongside Azithromycin And Rifampicin Against Mycobacterium Avium Infection, Melissa Kelley, Kayvan Sasaninia, Arbi Abnousian, Ali Badaoui, James Owens, Abrianna Beever, Nala Kachour, Rakesh Kumar Tiwari, Vishwanath Venketaraman

Pharmacy Faculty Articles and Research

Mycobacterium avium (M. avium), a type of nontuberculous mycobacteria (NTM), poses a risk for pulmonary infections and disseminated infections in immunocompromised individuals. Conventional treatment consists of a 12-month regimen of the first-line antibiotics rifampicin and azithromycin. However, the treatment duration and low antibiotic tolerability present challenges in the treatment of M. avium infection. Furthermore, the emergence of multidrug-resistant mycobacterium strains prompts a need for novel treatments against M. avium infection. This study aims to test the efficacy of a novel antimicrobial peptide, cyclic [R4W4], alongside the first-line antibiotics azithromycin and rifampicin in reducing M. avium survival. Colony-forming unit (CFU) …

Multi-Agent Deep Reinforcement Learning For Radiation Localization, Benjamin Scott Totten

Dissertations and Theses

For the safety of both equipment and human life, it is important to identify the location of orphaned radioactive material as quickly and accurately as possible. There are many factors that make radiation localization a challenging task, such as low gamma radiation signal strength and the need to search in unknown environments without prior information. The inverse-square relationship between the intensity of radiation and the source location, the probabilistic nature of nuclear decay and gamma ray detection, and the pervasive presence of naturally occurring environmental radiation complicates localization tasks. The presence of obstructions in complex environments can further attenuate the …

The Synthesis And Optimization Of Conductive Carbons From Renewable Resources For Supercapacitor Applications, Iris Denmark

Theses and Dissertations

The use of fossil fuels has played a pivotal role in the evolution of energy storage devices and the generation of electricity. With that, we have now entered an era in which we have become primarily dependent on these non-renewable resources which have become increasingly scarce overtime. This has driven us toward a pertinent demand for alternative sources of energy. There are various forms of alternative energy in which biomass is the most used. Carbon is becoming the most commonly used material for energy applications due to its versatility and bioavailability, including that which is sourced from biomass. Herein is …

Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites – Field Sampling Plan (Fsp) Ur 43 – Area Near Missoula Gulch Ball Field, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Phosphorus Sorption And Kinetics Across The Sediment-Water Interface Of Utah Lake, A Shallow Eutrophic Lake, Forrest Fielding Stretch Jarvis Jarvis

Theses and Dissertations

Internal sediment phosphorus (P) cycling may regulate harmful algal blooms (HABs) in shallow eutrophic lakes. Utah Lake frequently experiences HABs despite its high alkalinity and P-rich sediment. Phosphorus cycling between the lakebed and the water column is dependent upon stable P-sorption with organic matter (OM) and mineral species, which can vary with substrate availability, P-concentrations, temperature, redox, pH, and microbial activity. A full biogeochemical analysis of the water and sediment across seven sites shows Utah Lake to be spatially well-mixed in terms of composition and sorption, with few exceptions. Sediment P-concentrations (avg. 677 mg-P kg-1) primarily correlate with redox-sensitive iron …

2023 Convocation, Katie Berger, Evan M. Glazer, Maggie Dimarco '24, Jen Soriano '93, Angela Rowley, Lily Zhang

Convocation

No abstract provided.

A Proposed Artificial Intelligence Model For Android-Malware Detection, Fatma Taher, Omar Al Fandi, Mousa Al Kfairy, Hussam Al Hamadi, Saed Alrabaee

All Works

There are a variety of reasons why smartphones have grown so pervasive in our daily lives. While their benefits are undeniable, Android users must be vigilant against malicious apps. The goal of this study was to develop a broad framework for detecting Android malware using multiple deep learning classifiers; this framework was given the name DroidMDetection. To provide precise, dynamic, Android malware detection and clustering of different families of malware, the framework makes use of unique methodologies built based on deep learning and natural language processing (NLP) techniques. When compared to other similar works, DroidMDetection (1) uses API calls and …

Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites – Field Sampling Plan (Fsp) Ur 42 – Area Near Walkerville Playground, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Don't Fear The Artificial Intelligence: A Systematic Review Of Machine Learning For Prostate Cancer Detection In Pathology, Aaryn Frewing, Alexander B. Gibson, Richard Robertson, Paul Urie, Dennis Della Corte

Faculty Publications

The adoption of whole slide image (WSI) scanners in clinical practice was accelerated by US Food and Drug Administration approval in 2017, which allowed primary pathologic diagnoses to be made on scanned images. Images in the digital domain allow the application of pathology artificial intelligence (AI), including clinical decision support with algorithms performing specific diagnoses.1,2 These algorithms, if trained properly, could go beyond the ability of human observation to detect and quantify features that are not recognizable by human perception.1,3,4

Developing Electronic Clinical Quality Measures To Assess The Cancer Diagnostic Process, Daniel R Murphy, Andrew J Zimolzak, Divvy K Upadhyay, Li Wei, Preeti Jolly, Alexis Offner, Dean F Sittig, Saritha Korukonda, Riyaa Murugaesh Rekha, Hardeep Singh

Faculty, Staff and Student Publications

OBJECTIVE: Measures of diagnostic performance in cancer are underdeveloped. Electronic clinical quality measures (eCQMs) to assess quality of cancer diagnosis could help quantify and improve diagnostic performance.

MATERIALS AND METHODS: We developed 2 eCQMs to assess diagnostic evaluation of red-flag clinical findings for colorectal (CRC; based on abnormal stool-based cancer screening tests or labs suggestive of iron deficiency anemia) and lung (abnormal chest imaging) cancer. The 2 eCQMs quantified rates of red-flag follow-up in CRC and lung cancer using electronic health record data repositories at 2 large healthcare systems. Each measure used clinical data to identify abnormal results, evidence of …

Functional Polymer Nanocomposites With Increased Anticorrosion Properties And Wear Resistance For Water Transport, Andriy Buketov, Oleksandr Sapronov, Kostyantyn Klevtsov, Boksun Kim

School of Engineering, Computing and Mathematics

Corrosive destruction and hydroabrasive wear is a serious problem in the operation of machine parts and water transport mechanisms. It is promising to develop new composite materials with improved properties to increase the reliability of transport vehicles. In this regard, the use of new polymer-based materials, which are characterized by improved anticorrosion properties and wear resistance, is promising. In this work, therefore, for the formation of multifunctional protective coatings, epoxy dian oligomer brand ED-20, polyethylene polyamine (PEPA) hardener, a mixture of nanodispersed compounds with a dispersion of 30–90 nm, fillers Agocel S-2000 and Waltrop with a dispersion of 8–12 μm, …

Effects Of 3 Weeks Yogic Breathing Techniques On Sub-Maximal Running Responses, Christie L. Clifton, Lauren Killen, Matt Green, Eric O'Neal, Jonathan C. Swain, Christopher Frisbie

International Journal of Exercise Science

International Journal of Exercise Science 16(4): 1066-1076, 2023. This study investigated the influence of yoga breathing techniques (YBT) on physiological and perceptual responses during sub-maximal treadmill running. Runners (n = 21) of various fitness (VO2max 48.4 ± 9.5 ml/kg/min) were assigned to Yoga (YG) or control (CT) group before completing pre/post treadmill trials where velocity was self-selected to produce an RPE 4 and RPE 7 (10 min each). YG (n =11) practiced three styles of YBT (30 min/day, 6 days/wk) for 3 consecutive wks. Self-selected running velocity for YG improved significantly at both prescribed RPE 4 (pre 157.63 ± 26.20 …

A Nonstandard Finite Difference Numerical Solution For The Equal-Width Wave Equation, H. A. Elagamy, Z. F. Abushaeer, Galal I. El-Baghdady

Mansoura Engineering Journal

This study aims to develop an unconditionally stable numerical scheme for the equalwidth wave equation. An unconventional finite difference discretization is employed to accomplish this. The John von Neumann methodology is used to examine the stability of the suggested method, and the suggested scheme's precision is established. Numerical results with comparisons are shown to demonstrate the viability of the suggested approach for the equal-width wave equation.

Reinforcement Learning Approach To Stochastic Vehicle Routing Problem With Correlated Demands, Zangir Iklassov, Ikboljon Sobirov, Ruben Solozabal, Martin Takac

Machine Learning Faculty Publications

We present a novel end-to-end framework for solving the Vehicle Routing Problem with stochastic demands (VRPSD) using Reinforcement Learning (RL). Our formulation incorporates the correlation between stochastic demands through other observable stochastic variables, thereby offering an experimental demonstration of the theoretical premise that non-i.i.d. stochastic demands provide opportunities for improved routing solutions. Our approach bridges the gap in the application of RL to VRPSD and consists of a parameterized stochastic policy optimized using a policy gradient algorithm to generate a sequence of actions that form the solution. Our model outperforms previous state-of-the-art metaheuristics and demonstrates robustness to changes in the …

Designed For Better Control: Using Kinematic And Dynamic Metrics To Optimize Robot Manipulator Design, John R. Morrell

Theses and Dissertations

In the field of control theory, optimal performance is generally defined as the best possible controlled performance given a static, unchangeable plant system. However, principled design of the underlying system can make designing effective controllers easier and dramatically improve the final control performance beyond what any finely tuned controller could achieve alone. This work develops performance metrics for serial robot arms which help guide the design and optimization of the structure of the arm to achieve greater final performance. First, a kinematic (motion-based) metric called the Actuator Independence Metric (AIM) measures the uniqueness of the movement capabilities of the different …

Ruthenium Olefin Metathesis Catalysts Featuring Chelating Benzylidene-Triazole Ligands, Allegra L. Liberman-Martin

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In this issue of Chem Catalysis, Shi and co-workers describe the synthesis and olefin metathesis activity of ruthenium complexes with chelating benzylidene-triazole ligands. Catalyst decomposition is slow at up to 80°C, which enables challenging catalytic reactions, including cross-metathesis of trans-alkenes and macrocycle synthesis by dynamic covalent chemistry.

Improved Boreal Vegetation Mapping Using Imaging Spectroscopy To Aid Wildfire Management, Interior Alaska, Anushree Badola

Geosciences

Wildfires are a natural and essential part of Alaska ecosystems, but excessive wildfires pose a risk to the ecosystem's health and diversity, as well as to human life and property. To manage wildfires effectively, vegetation/fuel maps play a critical role in identifying high-risk areas and allocating resources for prevention, suppression, and recovery efforts. Furthermore, vegetation/fuel maps are an important input for fire behavior models, along with weather and topography data. By predicting fire behavior, such as spread rate, intensity, and direction, fuel models allow fire managers to make informed decisions about wildfire suppression, management, and prevention. Traditionally used vegetation/fuel maps …

A Reinterpretation Of Nanuqsaurus Hoglundi (Tyrannosauridae) From The Late Cretaceous Prince Creek Formation, Northern Alaska, Zackary R. Perry

Geosciences

The Late Cretaceous (late Campanian, ca. 72.8 Ma) Prince Creek Formation on the North Slope of Alaska is well-known for preserving the highest latitude dinosaur fauna in either hemisphere. Within this diverse dinosaurian fauna, a single tyrannosaurid theropod has been described: Nanuqsaurus hoglundi. Little work has been devoted to the taxon since 2014, when it was initially described based on three fragmentary cranial bones. Notably, it was characterized as a "diminutive" taxon, thought to have been substantially smaller than related Late Cretaceous tyrannosaurid species. New cranial and postcranial material attributable to the taxon collected by and housed at the University …

Characterization Of Geohazards Via Seismic And Acoustic Waves, Liam Toney

Geosciences

Earth processes, such as large landslides and volcanic eruptions, occur globally and can be hazardous to life and property. Geophysics -- the quantitative study of Earth processes and properties -- is used to monitor and rapidly respond to these geohazards. In particular, seismoacoustics, which is the joint study of seismic waves in the solid Earth and acoustic waves in Earth's atmosphere, has been proven effective for a variety of geophysical monitoring tasks. Typically, the acoustic waves studied are infrasonic: They have frequencies less than 20 hertz, which is below the threshold of human hearing. In this dissertation, we use seismic …

Applying Information Theory To Gamera Simulations Of Jupiter-Like Magnetospheres, Blake Mino

Physics

Magnetospheres are poorly understood, largely due to lack of significant amounts of in-situ data and the complexity of the systems. Accurate numerical magnetohydrodynamic (MHD) magnetosphere simulation codes can bolster this lack of observational data. In this thesis, we explore applying mutual information theory techniques to a global-scale Jovian-like magnetosphere simulation provided by the Grid Agnostic MHD for Extended Research Applications (GAMERA) code. The mutual information between two variables is a measure of their dependency and is even capable of detecting nonlinear relationships, unlike traditional linear correlation calculations. Time shifted mutual information is a useful metric for identifying possible causal relationships …

Design, Calibration, And Experiments To Improve The Feasibility Of Student-Built Magnetometers For Heliophysics Research, Austin David Cohen

Physics

Dynamic interactions between the solar wind and the Earth's magnetosphere can create strong geomagnetic field disturbances and trigger geomagnetically induced currents. Geomagnetically induced currents may cause damage to infrastructure such as damage to high-voltage power transformers and increased corrosion of pipelines. Ground observations of geomagnetic fields are widely used for geomagnetically induced current studies; however, there is insufficient information on the spatial extent of the localized geomagnetically induced current events due to a lack of spatial coverage. The Space Weather UnderGround is an education and outreach program, first initiated by Dr. Charles Smith at the University of New Hampshire and …

Graph-Based Learning Networks For Automatic Pigment Mapping Of Historical Artifacts, Bei Cao

Theses

Hyperspectral image classification can be a difficult task due to a lack of ground-truth labels and spectral variability. For hyperspectral images (HSIs) of historical artifacts, which are generally man-made objects, this is generally a significant challenge. Aiming to differentiate subtle spectral differences between varied pigments, we introduce graph- based learning networks and a powerful learning pipeline for realizing automatic pigment mapping on the maps. First, we develop a Graph Modularity clustering method for pro- ducing trustworthy ground-truth map for pigment classification task. We analyze the influence of graph structure on the Graph Neural Networks and propose Spatial-Spectral Graph Convolutional Network …

A Feasibility Study Of A Wearable Health Monitoring Device Powered By Thermoelectric Generators, Sarah Schneider

Masters Theses

Implementation of thermoelectric generators (TEGs) as a power source for embedded systems has increased with the push toward alternative and renewable energy sources. Thermoelectric generators produce electrical energy from thermal energy through the Seebeck effect. The Seebeck effect is a phenomenon seen when a temperature difference at a joint of two different metals generates a DC current and electromotive force [1]. This has made TEGs desirable for embedded system applications because it would allow for extended wireless operation. TEGs are based on solid-state technology which means they do not consist of any moving parts which reduces wear and tear with …

Measuring Microparticle Adhesion Via High-Speed Rotor, Jacob C. Fearnley

Theses and Dissertations

Much is known about the atomic/molecular theories that govern adhesion as well as the macroscopic aspects and properties of adhesion. However, adhesion in the microparticle regime is poorly characterized. We report on experiments that use centrifugal force to remove polystyrene (PS) particles from the surface of a high-speed titanium rotor operated in vacuum. This unique rotor can apply forces far greater than other centrifugal force methods or related techniques using atomic force spectroscopy. The mode of attachment, whether particles were located on the windward side versus leeward side of the spinning rotor, time spent in vacuum prior to experiments, and …

Detailed Characterization Of Material Deformation, Alexander J. Farnsworth

Theses and Dissertations

This dissertation presents a comprehensive exploration of material deformation at the atomic level, investigating key findings and contributions through three fundamental methods: Sum Frequency Generation Spectroscopy (SFG), X-ray Diffraction (XRD), and Electron Backscatter Diffraction (EBSD). The research commences by uncovering the material dependency of nonresonant responses in both SFG and Second Harmonic Generation (SHG) signals. This redefinition of the nonresonant component as an information-rich carrier, rather than mere background noise, leads to novel insights into the potential applications of SFG. The study then delves further into the influence of mechanical stress on materials, establishing a connection between dislocation density on …

An 11,600-Year Reconstruction Of Vegetation Communities, Moisture Availability, And Land Use Changes At Lake Khargal, Northern Mongolia, Joshua A. Barna

Geosciences

The regional response of vegetation to global atmospheric circulation patterns and human influence throughout the Holocene is recorded by environmental proxies in sediment cores from Lake Khargal in northern Mongolia. Pollen, spores, total organic carbon, and grain size analysis indicate that conditions in the watershed were moderately humid at ~11500 cal yr B.P. The vegetation community surrounding Lake Khargal consists of mainly of Artemisia (sage), Poaceae (grass), and Betula (birch) with a modest amount of extra-local Pinus (pine) from nearby boreal forests. Fluctuations in the ratios of these and other taxa show that aridity increased after ~10000 cal yr B.P., …