Physical Sciences and Mathematics Commons^™

Effect Of Duration Of 120 °C Baking On The Performance On Superconducting Radio Frequency Niobium Cavities, B. D. Khanal, P. Dhakal

Physics Faculty Publications

Over the last decade much attention was given in increasing the quality factor of superconducting radio frequency (SRF) cavities by impurity doping. Prior to the era of doping, the final cavity processing technique to achieve the high accelerating gradient includes the "in situ" low temperature baking of SRF cavities at temperature ~ 120 °C for several hours. Here, we present the results of a series of measurements on 1.3 GHz TESLA shape single-cell cavities with successive low temperature baking at 120 °C up to 96 hours. The experimental data were analyzed with available theory of superconductivity to elucidate the effect …

An Update To C12-21-004: Semi-Inclusive Deep Inelastic Scattering Measurements Of A = 3 Nuclei With Clas12 In Hall B, D. Gaskell, D. W. Higinbotham, C. Keith, C. Keppel, J. Maxwell, A. Tadepalli, D. Meekins, D. Nguyen, S. Stepanyan, H. Szumila-Vance, A. Denniston, O. Hen, J. Kahlbow, T. Kutz, J. R. Pybus, E. P. Segarra, C. Ayerbe-Gayoso, H. Bhatt, B. Devkota, J. Dunne, D. Dutta, L. El Fassi, A. Karki, M. Amarian, C. Fogler, F. Hauenstein, C. Hyde, G. Gavalian, L. B. Weinstein, S. Li, R. Cruz Torres, J. Rittenhouse West, Z. G. Xiao, Y. Wang, J. H. Xu, Z. H. Ye, Y. P. Zhang, K. Griffioen, P. Bosted, A. Bianconi, G. Costantini, M. Leali, S. Migliorati, L. Venturelli, V. Mascagna, A. Boyer, F. Benmokhtar, A. Gadsby, A. Parker, L. Baashen, B. Raue, W. J. Briscoe, S. Ratliff, A. Schmidt, E. Seroka, P. Sharp, P. G. Solazzo, I. I. Strakovsky, K. Adhikari, G. Niculescu, K.-T. Brinkmann, S. Diehl, A. Kripko, Sheren Alsalmi, Tyler J. Hague, A. Beck, S. Beck, E. Cohen, I. Korover, G. Johansson, C. Neuburger, E. Piasetzky, Michael Nycz, R. Capobianco, T. Haywars, F.-X. Girod, K. Joo, A. Kim, V. Klimenko, R. Santos, U. Shrestha, P. Simmerling, J. Richard, N. Trotta, B. Mckinnon, W. Brooks

Physics Faculty Publications

We propose to measure precision ratios of charged pion electroproduction in 10.6 GeV Semi-Inclusive Deep Inelastic Scattering from ²D, ³He and ³H targets in CLAS12 over a wide range of xB to test the flavor dependence of the EMC effect in the valence quark region. This trio of targets minimizes hadron attenuation effects while maximizing nuclear asymmetry and takes advantage of the tritium target that will be developed for the approved quasi-elastic experiment E12-20-005 [1]. The experiment will focus on z = En/v ≥ 0.3 to maximize the connection between the struck quark and the detected π±. Double ratios of …

Social Media Analytics And Information Privacy Decisions: Impact Of User Intimate Knowledge And Co-Ownership Perceptions, Bradley Alukwe Wangia

CCAC Theses and Dissertations

Social media analytics has been recognized as a distinct research field in the analytics subdomain that is developed by processing social media content to generate important business knowledge. Understanding the factors that influence privacy decisions around its use is important as it is often perceived to be opaque and mismanaged. Social media users have been reported to have low intimate knowledge and co-ownership perception of social media analytics and its information privacy decisions. This deficiency leads them to perceive privacy violations if firms make privacy decisions that conflict with their expectations. Such perceived privacy violations often lead to business disruptions …

A Validity-Based Approach For Feature Selection In Intrusion Detection Systems, Eljilani Hmouda

CCAC Theses and Dissertations

Intrusion detection systems are tools that detect and remedy the presence of malicious activities. Intrusion detection systems face many challenges in terms of accurate analysis and evaluation. One such challenge is the involvement of many features during analysis, which leads to high data volume and ultimately excessive computational overhead. This research surrounds the development of a new intrusion detection system by employing an entropy-based measure called v-measure to select significant features and reduce dimensionality. After the development of the intrusion detection system, this feature reduction technique was tested on public datasets by applying machine learning classifiers such as Decision Tree, …

Information Systems Security Countermeasures: An Assessment Of Older Workers In Indonesian Small And Medium-Sized Businesses, Hari Samudra Roosman

CCAC Theses and Dissertations

Information Systems (IS) misuse can result in cyberattacks such as denial-of-service, phishing, malware, and business email compromise. The study of factors that contribute to the misuse of IS resources is well-documented and empirical research has supported the value of approaches that can be used to deter IS misuse among employees; however, age and cultural nuances exist. Research focusing on older workers and how they can help to deter IS misuse among employees and support cybersecurity countermeasures within developing countries is in its nascent stages. The goal of this study was two-fold. The first goal was to assess what older workers …

Diagnosis Of Errors In Stalled Inter-Organizational Workflow Processes, Mudassar Habib Ghazi

CCAC Theses and Dissertations

Fault-tolerant inter-organizational workflow processes help participant organizations efficiently complete their business activities and operations without extended delays. The stalling of inter-organizational workflow processes is a common hurdle that causes organizations immense losses and operational difficulties. The complexity of software requirements, incapability of workflow systems to properly handle exceptions, and inadequate process modeling are the leading causes of errors in the workflow processes.

The dissertation effort is essentially about diagnosing errors in stalled inter-organizational workflow processes. The goals and objectives of this dissertation were achieved by designing a fault-tolerant software architecture of workflow system’s components/modules (i.e., workflow process designer, workflow engine, …

A Universal Cybersecurity Competency Framework For Organizational Users, Patricia A. Baker

CCAC Theses and Dissertations

The global reliance on the Internet to facilitate organizational operations necessitates further investments in organizational information security. Such investments hold the potential for protecting information assets from cybercriminals. To assist organizations with their information security, The National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework (NCWF) was created. The framework referenced the cybersecurity work, knowledge, and skills required to competently complete the tasks that strengthen their information security. Organizational users’ limited cybersecurity competency contributes to the financial and information losses suffered by organizations year after year. While most organizational users may be able to respond positively to a cybersecurity threat, …

Guest Editorial: Introduction To Aoir 2021 Papers On Emerging Ethical Practices And Platform Challenges, Michael Zimmer

Computer Science Faculty Research and Publications

No abstract provided.

Development Of A Chromatographic Method To Authenticate Aspirin Brands, Megan Guetzloff

Electronic Theses and Dissertations

Counterfeit pharmaceuticals pose a threat to society that can include inaccurate amounts of the active pharmaceutical ingredient (API), no API, or containing off-target compounds. For example, there are many recent examples of counterfeit pharmaceuticals containing potentially lethal doses (> 2 mg) of fentanyl (i.e., a synthetic opioid). Current measures to combat illicit pharmaceuticals (e.g., unique packaging and product serialization) have merit, however with evolved technologies, counterfeiters can relatively easily simulate these measures and continue to distribute illicit pharmaceuticals. The only accurate way to definitively determine that a suspected counterfeit is, in fact, counterfeit is advanced chemical analysis. However, current methods …

Application Of Artificial Intelligence And Machine Learning For Hiv Prevention Interventions, John Schneider

Faculty, Staff and Student Publications

In 2019, the US Government announced its goal to end the HIV epidemic within 10 years, mirroring the initiatives set forth by UNAIDS. Public health prevention interventions are a crucial part of this ambitious goal. However, numerous challenges to this goal exist, including improving HIV awareness, increasing early HIV infection detection, ensuring rapid treatment, optimising resource distribution, and providing efficient prevention services for vulnerable populations. Artificial intelligence has had a pivotal role in revolutionising health care and has shown great potential in developing effective HIV prevention intervention strategies. Although artificial intelligence has been used in a few HIV prevention intervention …

Reconstructability Analysis: Discrete Multivariate Modeling, Martin Zwick

Complex Systems Faculty Publications and Presentations

An introduction to Reconstructability Analysis for the Discrete Multivariate Modeling course and for other purposes.

Phenotype-Genotype Analysis Of Caucasian Patients With High Risk Of Osteoarthritis, Xiaobo Zhou

Faculty, Staff and Student Publications

Background: Osteoarthritis (OA) is a common cause of disability and pain around the world. Epidemiologic studies of family history have revealed evidence of genetic influence on OA. Although many efforts have been devoted to exploring genetic biomarkers, the mechanism behind this complex disease remains unclear. The identified genetic risk variants only explain a small proportion of the disease phenotype. Traditional genome-wide association study (GWAS) focuses on radiographic evidence of OA and excludes sex chromosome information in the analysis. However, gender differences in OA are multifactorial, with a higher frequency in women, indicating that the chromosome X plays an essential role …

Automated Identification Of Missing Is-A Relations In The Human Phenotype Ontology, Hua Xu, Licong Cui

Faculty, Staff and Student Publications

Auditing the Human Phenotype Ontology (HPO) is necessary to provide accurate terminology for its use in clinical research. We investigate an approach leveraging the lexical features of concepts in HPO to identify missing IS-A relations among HPO concepts. We first model the names of HPO concepts as sets of words in lower case. Then, we generate two types of concept-pairs which have at least a single common word: (1) Linked concept-pairs generated from concept-pairs having an IS-A relation; (2) Unlinked concept-pairs generated from concept-pairs without an IS- A relation. Concept-pairs generate Derived Term Pairs (DTPs) emphasizing unique lexical information of …

Cost Of Care For Asylum Seekers And Refugees Entering The United States: The Case Of Volunteer Medical Providers In El Paso, Texas, Celia E Gonzalez, Leopold Gemoets

Faculty, Staff and Student Publications

BACKGROUND: Between October 2018, and February 2020, the United States saw an unprecedented increase in the number of asylum seekers and refugees arriving unexpectedly at international crossings along the US-Mexico Border. Many of these migrants needed proper medical attention, and consequently created significant pressure on local health systems. In El Paso, Texas, volunteer clinicians, collaborating closely with religious organizations and non-governmental organizations, provided outpatient medical care for the new arrivals; the county hospital provided in-patient care at local tax payers' expense. The objective of this study was to estimate costs of healthcare services offered by these volunteers in order to …

Electron Transfer Dynamics And Electrocatalytic Oxygen Evolution Activities Of The Co3o4 Nanoparticles Attached To Indium Tin Oxide By Self-Assembled Monolayers, Jinlian Wang, Shuling Liu, Chao Wang

Faculty, Staff and Student Publications

The Co3O4 nanoparticle-modified indium tin oxide-coated glass slide (ITO) electrodes are successfully prepared using dicarboxylic acid as the self-assembled monolayer through a surface esterification reaction. The ITO-SAM-Co3O4 (SAM = dicarboxylic acid) are active to electrochemically catalyze oxygen evolution reaction (OER) in acid. The most active assembly, with Co loading at 3.31 × 10-8 mol cm-2, exhibits 374 mV onset overpotential and 497 mV overpotential to reach 1 mA cm-2 OER current in 0.1 M HClO4. The electron transfer rate constant (k) is acquired using Laviron's approach, and the results show that k is not affected by the carbon …

A Nomogram For Predicting Upper Urinary Tract Damage Risk In Children With Neurogenic Bladder, Xing Liu, Tao Lin, Dawei He, Jianguo Wen, Guanghui Wei

Faculty, Staff and Student Publications

PURPOSE: To establish a predictive model for upper urinary tract damage (UUTD) in children with neurogenic bladder (NB) and verify its efficacy.

METHODS: A retrospective study was conducted that consisted of a training cohort with 167 NB patients and a validation cohort with 100 NB children. The clinical data of the two groups were compared first, and then univariate and multivariate logistic regression analyses were performed on the training cohort to identify predictors and develop the nomogram. The accuracy and clinical usefulness of the nomogram were verified by receiver operating characteristic (ROC) curve, calibration curve and decision curve analyses.

RESULTS: …

Quantification Of Infarct Core Signal Using Ct Imaging In Acute Ischemic Stroke, Mudassir Farooqui, Juan Vivanco-Suarez, Santiago Ortega Gutierrez, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

In stroke care, the extent of irreversible brain injury, termed infarct core, plays a key role in determining eligibility for acute treatments, such as intravenous thrombolysis and endovascular reperfusion therapies. Many of the pivotal randomized clinical trials testing those therapies used MRI Diffusion-Weighted Imaging (DWI) or CT Perfusion (CTP) to define infarct core. Unfortunately, these modalities are not available 24/7 outside of large stroke centers. As such, there is a need for accurate infarct core determination using faster and more widely available imaging modalities including Non-Contrast CT (NCCT) and CT Angiography (CTA). Prior studies have suggested that CTA provides improved …

Brain Antigens Stimulate Proliferation Of T Lymphocytes With A Pathogenic Phenotype In Multiple Sclerosis Patients

Faculty, Staff and Student Publications

A method to stimulate T lymphocytes with a broad range of brain antigens would facilitate identification of the autoantigens for multiple sclerosis and enable definition of the pathogenic mechanisms important for multiple sclerosis. In a previous work, we found that the obvious approach of culturing leukocytes with homogenized brain tissue does not work because the brain homogenate suppresses antigen-specific lymphocyte proliferation. We now report a method that substantially reduces the suppressive activity. We used this non-suppressive brain homogenate to stimulate leukocytes from multiple sclerosis patients and controls. We also stimulated with common viruses for comparison. We measured proliferation, selected the …

A Novel Framework To Estimate Cognitive Impairment Via Finger Interaction With Digital Devices, Rahul Mahajan, Aaron Ritter, Teresa Arroyo-Gallego, Luca Giancardo

Faculty, Staff and Student Publications

Measuring cognitive function is essential for characterizing brain health and tracking cognitive decline in Alzheimer's Disease and other neurodegenerative conditions. Current tools to accurately evaluate cognitive impairment typically rely on a battery of questionnaires administered during clinical visits which is essential for the acquisition of repeated measurements in longitudinal studies. Previous studies have shown that the remote data collection of passively monitored daily interaction with personal digital devices can measure motor signs in the early stages of synucleinopathies, as well as facilitate longitudinal patient assessment in the real-world scenario with high patient compliance. This was achieved by the automatic discovery …

Cross-Talk Between Histone Methyltransferases And Demethylases Regulate Rest Transcription During Neurogenesis, Javiera Bravo-Alegria, Lei Guo, Lin Xu, Arif Harmanci, Vidya Gopalakrishnan

Faculty, Staff and Student Publications

The RE1 Silencing Transcription Factor (REST) is a major regulator of neurogenesis and brain development. Medulloblastoma (MB) is a pediatric brain cancer characterized by a blockade of neuronal specification. REST gene expression is aberrantly elevated in a subset of MBs that are driven by constitutive activation of sonic hedgehog (SHH) signaling in cerebellar granular progenitor cells (CGNPs), the cells of origin of this subgroup of tumors. To understand its transcriptional deregulation in MBs, we first studied control of Rest gene expression during neuronal differentiation of normal mouse CGNPs. Higher Rest expression was observed in proliferating CGNPs compared to differentiating neurons. …

Racial And Socioeconomic Disparities In Patients With Meningioma: A Retrospective Cohort Study, James C Bayley, Arya Shetty, Jacob Mandel, Ali Jalali, K Kelly Gallagher, Alex D Sweeney, Arif O Harmanci, Akdes S Harmanci, Tiemo Klisch, Shankar P Gopinath, Ganesh Rao, Daniel Yoshor, Akash J Patel

Faculty, Staff and Student Publications

BACKGROUND: Meningiomas are the most common intracranial neoplasms. Although genomic analysis has helped elucidate differences in survival, there is evidence that racial disparities may influence outcomes. African Americans have a higher incidence of meningiomas and poorer survival outcomes. The etiology of these disparities remains unclear, but may include a combination of pathophysiology and other factors.

OBJECTIVE: To determine factors that contribute to different clinical outcomes in racial populations.

METHODS: We retrospectively reviewed 305 patients who underwent resection for meningiomas at a single tertiary care facility. We used descriptive statistics and univariate, multivariable, and Kaplan-Meier analyses to study clinical, radiographical, and …

Deep Graph Convolutional Network For Us Birth Data Harmonization, Xiaoqian Jiang

Faculty, Staff and Student Publications

In this paper, we developed a feasible and efficient deep-learning-based framework to combine the United States (US) natality data for the last five decades, with changing variables and factors, into a consistent database. We constructed a graph based on the property and elements of databases, including variables, and conducted a graph convolutional network (GCN) to learn the embeddings of variables on the constructed graph, where the learned embeddings implied the similarity of variables. Specifically, we devised a loss function with a slack margin and a banlist mechanism (for a random walk) to learn the desired structure (two nodes sharing more …

Risk Of Alzheimer's Disease Following Influenza Vaccination: A Claims-Based Cohort Study Using Propensity Score Matching, Yejin Kim, Kamal N Phelps, Rosemarie E Schmandt, Albert Amran, Ryan Coburn, Srivathsan Ramesh, Qian Xiao, Paul E Schulz

Faculty, Staff and Student Publications

BACKGROUND: Prior studies have found a reduced risk of dementia of any etiology following influenza vaccination in selected populations, including veterans and patients with serious chronic health conditions. However, the effect of influenza vaccination on Alzheimer's disease (AD) risk in a general cohort of older US adults has not been characterized.

OBJECTIVE: To compare the risk of incident AD between patients with and without prior influenza vaccination in a large US claims database.

METHODS: Deidentified claims data spanning September 1, 2009 through August 31, 2019 were used. Eligible patients were free of dementia during the 6-year look-back period and≥65 years …

Fairly Predicting Graft Failure In Liver Transplant For Organ Assigning, Kai Zhang, Xiaoqian Jiang, Xia Hu

Faculty, Staff and Student Publications

Liver transplant is an essential therapy performed for severe liver diseases. The fact of scarce liver resources makes the organ assigning crucial. Model for End-stage Liver Disease (MELD) score is a widely adopted criterion when making organ distribution decisions. However, it ignores post-transplant outcomes and organ/donor features. These limitations motivate the emergence of machine learning (ML) models. Unfortunately, ML models could be unfair and trigger bias against certain groups of people. To tackle this problem, this work proposes a fair machine learning framework targeting graft failure prediction in liver transplant. Specifically, knowledge distillation is employed to handle dense and sparse …

Facilitating Federated Genomic Data Analysis By Identifying Record Correlations While Ensuring Privacy, Jaideep Vaidya, Xiaoqian Jiang, Erman Ayday

Faculty, Staff and Student Publications

With the reduction of sequencing costs and the pervasiveness of computing devices, genomic data collection is continually growing. However, data collection is highly fragmented and the data is still siloed across different repositories. Analyzing all of this data would be transformative for genomics research. However, the data is sensitive, and therefore cannot be easily centralized. Furthermore, there may be correlations in the data, which if not detected, can impact the analysis. In this paper, we take the first step towards identifying correlated records across multiple data repositories in a privacy-preserving manner. The proposed framework, based on random shuffling, synthetic record …

Caries Risk Documentation And Prevention: Emeasures For Dental Electronic Health Records, Todd R Johnson, Gregory W Olson, Shwetha V Kumar, Krishna K Kookal, Aram Kim, Enihomo Obadan-Udoh, Elizabeth Mertz, Kristen Simmons, Joanna Mullins, Ryan Brandon, Muhammad F Walji, Elsbeth Kalenderian

Faculty, Staff and Student Publications

BACKGROUND: Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures).

OBJECTIVE: We report the feasibility and validity of implementing two eMeasures. The eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA) and corresponding appropriate risk-based preventative treatments for patients at elevated risk of caries (appropriateness of care [eAoC]) in two academic institutions and one accountable care organization, in the 2019 reporting year.

METHODS: Both eMeasures define the numerator and denominator beginning at the patient level, populations' specifications, and validated the automated queries. For …

Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, And Beyond

Faculty, Staff and Student Publications

Patient care in intensive care environments is complex, time-sensitive, and data-rich, factors that make these settings particularly well-suited to clinical decision support (CDS). A wide range of CDS interventions have been used in intensive care unit environments. The field needs well-designed studies to identify the most effective CDS approaches. Evolving artificial intelligence and machine learning models may reduce information-overload and enable teams to take better advantage of the large volume of patient data available to them. It is vital to effectively integrate new CDS into clinical workflows and to align closely with the cognitive processes of frontline clinicians.

The Times, They Are A-Changin': Tracking Shifts In Mental Health Signals From Early Phase To Later Phase Of The Covid-19 Pandemic In Australia, Siqin Wang, Xiao Huang, Tao Hu, Mengxi Zhang, Zhenlong Li, Huan Ning, Jonathan Corcoran, Asaduzzaman Khan, Yan Liu, Jiajia Zhang, Xiaoming Li

Geosciences Faculty Publications and Presentations

Introduction Widespread problems of psychological distress have been observed in many countries following the outbreak of COVID-19, including Australia. What is lacking from current scholarship is a national-scale assessment that tracks the shifts in mental health during the pandemic timeline and across geographic contexts.

Methods Drawing on 244 406 geotagged tweets in Australia from 1 January 2020 to 31 May 2021, we employed machine learning and spatial mapping techniques to classify, measure and map changes in the Australian public’s mental health signals, and track their change across the different phases of the pandemic in eight Australian capital cities.

Results Australians’ …

Editorial: Coastal Flooding: Modeling, Monitoring, And Protection Systems, Valentina Prigiobbe, Clint Dawson, Yao Hu, Hatim O. Sharif, Navid Tahvildari

Civil & Environmental Engineering Faculty Publications

Coastal flooding has received significant attention in recent years due to future sea-level rise (SLR) projections and intensification of precipitation, which will exacerbate frequent flooding, coastal erosion, and eventually create permanently inundated low-elevation land. Coastal governments will be forced to implement measures to manage risk on the population and infrastructure and build protection systems to mitigate or adapt to the negative impacts of flooding. Research in this area is required to establish holistic frameworks for timely and accurate flooding forecast and design of protection systems.

Recent Advancements In Electrochemical Conversion Of Carbon Dioxide, Nandan Nag, Amit Kumar, Sumit Sharma, Sandeep Kumar, Amit K. Thakur

Civil & Environmental Engineering Faculty Publications

Electrochemical reduction of carbon dioxide into eco-friendly and clean products is a promising approach to eradicate pollution. Although carbon dioxide emission is inhibited by the advent of renewable sources of energy, it is present in the atmosphere and needs to be cleaned. The reduction of carbon dioxide from atmospheric gases can be accomplished by its adsorption and subsequent transportation to electrolytic chambers, where it is reduced to hydrocarbons, organic acids or carbonates. This review focuses on developing a three compartment electrochemical cell to reduce carbon dioxide used as a catholyte. Various factors affecting the electrochemical reduction of carbon dioxide and …