Digital Commons Network^™

Great Salt Lake Model Depletion, Katherine Wright

Spring Runoff Conference

When does water leasing make sense? Using New Information to Make Better Leases.

Lease, but only if it makes sense.

• Farmers have a legal right to use water on their farms for agriculture.
• Leasing might be a good economic decision for you, but not your neighbor.
• Leasing is voluntary, the purpose of this presentation is to explain the benefits of leasing and give you the information you need to decide if it is right for you. 

Utah Water Research Lab, David Tarboton

Spring Runoff Conference

The concept of a dedicated water research laboratory evolved over years, with significant contributions from Vaughn E. Hansen, Dean F. Peterson, and George D. Clyde. The UWRL represents the culmination of a long-held vision at USU to advance water research.

Role Of Eye-Tracking Technology And Software Algorithms In Enhancing Adhd Detection And Diagnosis: A Systematic Literature Review, Lauren E. Perkins

Honors College Theses

This systematic literature review explores the role of eye-tracking technology and software algorithms in enhancing the detection and diagnosis of ADHD. ADHD, a neurodevelopmental disorder affecting both children and adults, is traditionally diagnosed through behavioral assessments, which may lack objectivity. Recent studies suggest that eye-tracking, specifically focusing on saccades, fixations, and blink rates, offers the potential for more accurate and objective measures of ADHD. The review examines clinical trials, observational studies, and machine learning research to assess the correlation between ADHD and eye movement patterns. Results indicate that individuals with ADHD exhibit distinct eye movement patterns, which can be quantified …

Cyber Threat Intelligence For Smart Grids Using Knowledge Graphs, Digital Twins, And Hybrid Machine Learning In Scada Networks, Nabeel Al-Qirim, Munir Majdalawieh, Anoud Bani-Hani, Hussam Al Hamadi

All Works

In the SCADA (Supervisory Control and Data Acquisition) network of a smart grid, the network switch is connected to multiple Intelligent Electronic Devices (IEDs) that are based on protective relays. False-Data Injection Attacks (FDIA), Remote-Tripping Command Injection (RTCI), and System Reconfiguration Attacks (SRA) are three types of cyber-attacks on SCADA networks, resulting in single-line-to-ground (SLG) fault, IED-relay failure, and circuit-breaker open issues occur. The existing cyber threat intelligence (CTI) approaches of grids are unable to provide visualization of cyber-attacking grid effects. To understand the full effect of the attacks, there is a need for a knowledge-graph method-based digital-twin cyber-attack visualization …

Unlocking Precision Using K-Means++- Improved Genetic Algorithm-Radial Basis Function Neural Network: Data-Driven Evolution Of Smart Gloves For Gesture Recognition, Liang Xiao Ding, Kuan Way Chee, Hong Lü, Anand Paul, Jeonghong Kim, Jang Myung Lee

School of Public Health Faculty Publications

Human-computer interaction technologies have been used since the 1970s but have only gained growing popularity in recent years with new design paradigms. Ongoing research and development in gesture recognition systems with broad application prospects have focused on improving accuracy and real-time performance as well as the robustness of specific machine learning algorithms against environmental conditions. This paper addresses the accuracy enhancement of a novel Fifth Dimension Technologies data-glove-based gesture recognition system using a genetic-algorithm (GA)-trained k-means++-improved radial basis function (RBF) or GK-RBF neural network. First, we analyzed and modeled the sensor distribution in the data glove and proposed joint constraints …

Assessment Indicator System For Siting Of Geologic Co2 Sequestration In Low-Porosity And Low-Permeability Saline Aquifers: A Case Study Of The Ordos Basin, Mou Yu, Wang Haofan, Shaanxi Key Laboratory For Carbon Neutral Technology, Carbon Neutrality College (Yulin), Northwest University, Xi’An 710069, China Xuejun, Ma Jinfeng, Luo Shaocheng, Li Lin, Ding Zhao

Coal Geology & Exploration

Objective CO₂ injection and geologic sequestration in deep saline aquifers as underground spatial resources represents an important means of achieving the targets of greenhouse gas emission reduction and carbon neutrality. Current assessments of the siting and potential for geologic CO₂ sequestration in saline aquifers focus primarily on the macroscopic basin and regional scales, with the assessment indicator system scarcely accounting for the suitability of low-porosity and low-permeability strata. Methods Using data from 192 wells in the Yusheng area, Ordos Basin, this study conducted the division and correlation of intervals bearing no hydrocarbon, carried out lithologic and physical interpretations …

Tundra Recovery Post-Fire In The Yukon-Kuskokwim Delta, Alaska, Leah K. Clayton, Kevin Schaefer, Elizabeth E. Hoy, Clayton D. Elder, Nancy H. F. French, Gerald V. Frost, Et.Al.

Michigan Tech Publications

The extent of wildfires in tundra ecosystems has dramatically increased since the turn of the 21st century due to climate change and the resulting amplified Arctic warming. We simultaneously studied the recovery of vegetation, subsurface soil moisture, and active layer thickness (ALT) post-fire in the permafrost-underlain uplands of the Yukon-Kuskokwim Delta in southwestern Alaska to understand the interaction between these factors and their potential implications. We used a space-for-time substitution methodology with 2017 Landsat 8 imagery and synthetic aperture radar products, along with 2016 field data, to analyze tundra recovery trajectories in areas burned from 1953 to 2017. We found …

Alterity And Kinship: Co-Writing Posthumanist Speculative Nonfiction With Ai, Jeffrey Bardzell, Maliheh Ghajargar

Engineering Faculty Articles and Research

As a response to the climate crisis, scholarly literature has introduced new theoretical perspectives, such as posthumanism, which seek to reimagine the relationships between humans and nonhuman others, including environments, animals, and plants. Reimagining these relationships depends in large part on our ability to engage nonhumans in their otherness, or alterity, but doing so is challenging. Responding to calls throughout posthuman literature for experimental new modes of imaginative encounter with nonhumans, and inspired by speculative traditions from literature to design, we devise a methodology involving “creative experiments” aimed at disrupting, decentering, and disorienting the human-centered thinking that interferes with humans’ …

Critical Appraisal Of Multidrug Therapy In The Ambulatory Management Of Patients With Covid-19 And Hypoxemia Part I. Evidence Supporting The Strength Of Association, Eleftherios Gkioulekas, Peter A. Mccullough, Colleen Aldous

School of Mathematical & Statistical Sciences Faculty Publications

This critical appraisal is focused on three published case series of 119 COVID-19 patients with hypoxemia who were successfully treated in the United States, Zimbabwe, and Nigeria with similar off-label ivermectin-based multidrug treatments that may include ivermectin, nebulized nanosilver, doxycycline, zinc, Vitamins C, and Vitamin D, resulting in rapid recovery of oxygen levels. We used a simplified self-controlled case series method to investigate the association between treatment and the existence of hospitalization rate reduction. External controls of hospitalized patients were compared against the subgroup of patients with baseline room air SpO2 ≤ 90% to investigate the association between treatment and …

Critical Appraisal Of Multidrug Therapy In The Ambulatory Management Of Patients With Covid-19 And Hypoxemia. Part Ii: Causal Inference Using The Bradford Hill Criteria, Eleftherios Gkioulekas, Peter A. Mccullough, Colleen Aldous

School of Mathematical & Statistical Sciences Faculty Publications

We continue the critical appraisal of three published case series of 119 COVID-19 patients with hypoxemia, treated in the United States, Zimbabwe, and Nigeria with similar ivermectin-based multidrug treatments, to assess the available evidence supporting a causal relationship between treatment and reduction in hospitalizations and mortality. A narrative review was conducted to assess the Bradford Hill criteria for a causal association. We used a previously proposed refinement of the Bradford Hill criteria that reorganized them into three categories of direct, mechanistic, and parallel evidence. The efficacy of the two most aggressive ivermectin-based multidrug protocols is supported by the Bradford Hill …

Applications Of Linear Discriminant Analysis In The Biomechanics Of Anterior Cruciate Ligament Injury, Taofeek Braimoh

USF Tampa Graduate Theses and Dissertations

Anterior cruciate ligament (ACL) injury is a prevalent and significant concern in sports medicine, often resulting in long-term consequences that affect quality of life. Despite advancements in medical technology, current methods for addressing the problem of ACL injuries remain inefficient, subjective, and limited in their predictive power. This study explores the potential of Linear Discriminant Analysis (LDA), a supervised machine learning (ML) technique, to improve the diagnosis and risk profiling of ACL injuries. This research aims to create an objective, effective, and precise technique for determining the risk of ACL injuries by examining key biomechanical, physical, and demographical features. The …

Facile Synthesis Of Tetraaryl Phosphonium Ionic Liquids, Stephanie C. Jones, Devin J. Schwaibold, Grant Meadows, Brennan Shuler, Richard E. Sykora, Frank Rolf Fronczék, James H. Davis, Benjamin Wicker

EKU Faculty and Staff Scholarship

The syntheses of triphenyl-2-pyridylphosphonium salts, [Mopyphos]A, where A-= BF4-, B(C6H5)4-, (CF3SO2)2N-, Sac-, and Ace-. (Sac-= saccharinate, Ace-= acesulfamate) are described. These salts can be synthesized on a multi-gram scale with good yields and have been characterized by NMR, single crystal XRD, and HRMS. Thermal analyses indicate that the bistriflimide (Tf2N-= (CF3SO2)2N-) salts are especially amenable towards high-temperature ionic liquid (IL) applications with decomposition temperatures above 450 degrees C. The synthetic methods described herein can be utilized to generate several phosphonium bistriflimide ILs of the general formula [(C6H5)3P-Ar]Tf2N, where Ar = N-heteroaryl).

Value-Based Healthcare Reimagined: A Mixed-Methods Study On Behavioral Health Clinicians' Perspectives, Amanda L. Strickland

Electronic Theses and Dissertations

This study explores how behavioral health clinicians perceive Value-Based Healthcare (VBHC), a model designed by Porter and Teisberg (2006) to improve outcomes relative to costs. While widely promoted in healthcare reform, VBHC poses unique challenges when applied to behavioral health settings. Using an explanatory mixed-methods design, this study first assessed clinicians’ awareness of VBHC through a survey of 23 licensed clinicians at a Community Mental Health Center (CMHC) in Colorado. Quantitative findings revealed that one-third of participants were aware of VBHC with awareness differing by role prompting further exploration in a qualitative phase. Semi-structured interviews with eight clinicians provided deeper …

Synthetic Protein Mimetic Based Therapies For Neurodegeneration, Nicholas H. Stillman

Electronic Theses and Dissertations

Protein-protein interactions (PPIs) are crucial for the regulation of a majority of, if not every fundamental cellular process. Despite their role in regular biological processes, dysregulated and/or aberrant protein-protein interactions (aPPIs) are often related to the onset of disease including cancer, viral infection, and amyloid diseases. aPPIs have historically been deemed ‘undruggable’ due to their large surface area and lack of a binding cavity; however, today, more than 40 disease-related aPPIs have been targeted with small molecules and several of those have reached clinical trials.

A class of synthetic protein mimetics called oligopyridylamides (OPs) has been shown to inhibit disease-related …

Local Structure Of Zinc-Indium-Tin Oxide Films Via Grazing-Incidence X-Ray Pair-Distribution Functions And Theoretical Methods, G. B. González, C. J. Benmore, Julia E. Medvedeva, J. S. Okasinski, C. Riegger, O. Medina, M. M. Stulajter, T. Bsaibes, G. Cardenas, S. Cone, K. Edlund, M. Osorio, T. Holmes, I. Zhuravlev

Physics Faculty Research & Creative Works

A detailed experimental and theoretical study on the local (r ≤ 4.5 Å) atomic structure of amorphous and crystalline zinc-indium-tin oxide (ZITO) thin films using grazing-incidence x-ray Pair-Distribution Functions (PDFs), ab initio Molecular Dynamics (MD), and Empirical Potential Structure Refinement (EPSR) Monte Carlo simulations is presented. High-energy synchrotron x rays, a two-dimensional detector, and different incident angles were used to probe the depth uniformity of five (ZnO)0.15 (In2O3)0.70 (SnO2)0.15 films that were deposited via pulsed-laser deposition at growth temperatures (TG) ranging from 25 to 300 °C. Films deposited at TG ≤ 150 °C were amorphous. The partially crystalline (TG = …

Optimizing Parameters For Efficient Computation With Fully Homomorphic Encryption Schemes, Cavi̇dan Yakupoğlu Karaağaç, Kurt Rohloff

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we aim to provide a parameter selection approach for the BFVrns scheme, one of the prominent fully homomorphic encryption (FHE) schemes. Selecting parameters for lattice-based FHE schemes poses a practical challenge for both experts and nonexperts. To solve this problem, we introduce a hybrid approach that combines theoretical approach with experimental analysis. First, we employ regression analysis to examine the impact of parameters on both performance and security. The varying behavior of FHE parameters in terms of performance, security, and ciphertext expansion factor (CEF) makes parameter selection more challenging. To address this issue, we employ a multi-objective …

Decomposition Lstm With Dual Multi-Head Self-Attention For Wind Turbine Drivetrain State Forecasting, Haikun Jia, Huini Sun, Shuang Bai

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the clean and renewable nature of wind energy, accurate prediction of rotor loads and operating states for wind turbine units has become of paramount importance. Currently, traditional methods relying on expert analysis combined with instrument testing for qualitative reasoning are both time-consuming and labor-intensive, and their accuracy guarantees are limited. In response to wind farm data entailing the interweaving of data from multiple sources and the diverse interrelations across various features and time steps, this study introduces a method for predicting rotor loads and operating states. Initially, we employ an iterative multi-scale seasonal-trend decomposition block to capture latent …

Impact Of Carbonate-Hosted Zn-Pb Ore Deposits On Groundwater Chemistry: Üzümcü-Olgunlar Mining Site (Hakkari, Türkiye), Ci̇han Tuncer, Yüksel Örgün Tutay, Muhterem Demiruğlu

Turkish Journal of Earth Sciences

Hakkari, known for its high economic value Zn-Pb deposits in Türkiye, has been predominantly producing Zn ore for about 20 years. This study investigated the hydrogeochemical properties of groundwater and surface water collected from the vicinity of carbonate-oxide Zn-Pb mine sites in southern Hakkari to evaluate the effects of mineral deposits and mining activities on groundwater chemistry, as there are potential sources of natural pollution. Samples were collected four times at regular intervals during 2021–2022 from points determined upstream, downstream, and around the mine sites, springs, and streams. The samples were analyzed for majorions, trace elements, and isotopes (18O, 2H, …

Postseismic Groundwater Quality Investigation In Aquifers Following Earthquake-Induced Demolition Wastes: Hatay (Türkiye) Case Study, Pinar Avci, Gali̇p Yüce

Turkish Journal of Earth Sciences

The February 6, 2023 seismic sequence that hit, the Antakya district of Hatay (Türkiye), killed more than 50,000 people and caused extensive structural damages, resulting in the collapse of 80% of the building stock that generated over 100 million tons of debris. Understanding the impact of seismic events on water resources is highly important for ensuring human and environmental health. Herewith, a study was carried out over the Hatay area to assess the post-earthquake sustainable usability of groundwater for drinking, domestic, and irrigation purposes. 17 water points were investigated in September 2023, encompassing alluvial deposits with relatively high hydraulic conductivity …

Identification Of Candidate Ultraviolet Counterparts To Globular Cluster X-Ray Binaries, William Schuster

College of Science and Health Theses and Dissertations

X-ray binaries function as sources of potential energy that keep globular clusters from collapsing in on themselves, and therefore, understanding X-ray binaries is crucial to understanding globular clusters, and our galaxy as a whole. The dense cores of globular clusters can prevent both optical photometry and infrared photometry from adequately measuring the brightness of individual stars. However, the cores of globular clusters are much less crowded in the ultraviolet, which allows for the identification of individual stars within the core. By identifying ultraviolet counterparts to each X-ray source within a globular cluster, the type of X-ray emitter can be determined. …

Racial And Ethnic Inequalities In Actual Vs Nearest Delivery Hospitals, Nansi S. Boghossian, Lucy T. Greenberg, Jeffrey S. Buzas, Joshua Radack, Molly Passarella, Jeannette Rogowski, George R. Saade, Ciaran S. Phibbs, Scott A. Lorch

Faculty Publications

IMPORTANCE Minoritized racial and ethnic groups, such as American Indian and Black individuals, often receive lower quality health care compared with White individuals. There is limited understanding of how these disparities extend to obstetric care, particularly when comparing the quality of care at the actual delivery hospital vs the nearest obstetric hospital based on the birthing individual’s residence. OBJECTIVE To examine inequality in care based on the actual delivery hospital and the closest delivery hospital to the birthing individual’s residential zip code centroid. DESIGN, SETTING, AND PARTICIPANTS This population-based retrospective cohort study used data from 5 states (2008 to 2020 …

Multikernel Embedded Fusion Unet (Mkef-Unet): A Robust Deep Learning Approach For Accurate Segmentation Of Chagas Parasites, Preet Kumar, Carlos Brito-Loeza, Lavdie Rada

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a novel approach for segmenting Chagas parasites on stained blood smear samples from mice during the acute phase of infection with Trypanosoma cruzi utilizing a U-Net-based deep learning model named multikernel embedded fusion UNet (MKEF-UNet). Our proposed model incorporates DenseNet-121 for feature extraction, a classifier module for predicting parasite information, and a segmentation decoder with multiscale feature fusion to generate precise segmentation results. Notably, the integration of the embedded vector module, multikernel convolutions with dilations, and advanced data augmentation techniques significantly enhance the model’s robustness and generalization capabilities. In extensive experiments on the Chagas dataset, MKEF-UNet achieves …

Student Expectations And Outcomes In Virtual Vs In-Person Interprofessional Simulations: A Qualitative Analysis, Padmavathy Ramaswamy, Abbey M Bachmann, Tiffany Champagne-Langabeer, Chasisty L Gilder, Samuel E Neher, Jennifer L Swails

Faculty, Staff and Student Publications

Background: Health-related programs frequently integrate interprofessional education (IPE) into their training. The COVID-19 pandemic transitioned many IPE programs online, making it essential to assess student expectations and perceived learning outcomes across virtual simulations and in-person settings.

Methods: This qualitative study compared student expectations and self-reported outcomes across in-person and virtual case scenarios at a Texas health science center. Responses to open-ended questions from two data collection periods were analyzed using inductive coding and thematic analysis.

Results: Students from nursing, medicine, dentistry, public health, and informatics participated in each group. Three major themes emerged from this study: communication, teamwork, and …

An Alternative To Biliverdin, Mesobiliverdin Ixα And Mesobiliverdin-Enriched Microalgae: A Review On The Production And Applications Of Mesobiliverdin-Related Products, Naveena Poudyal, Jon Y. Takemoto, Yuan-Yu Lin, Cheng-Wei T. Chang

Chemistry and Biochemistry Student Research

Despite attracting interest for decades due to its anti-inflammatory and antioxidant capabilities, the use of biliverdin IXα (BV) in medicine and agriculture is hampered by uncertain purity and limited availability. A significant amount of effort has been devoted to the production and application of BV, but with limited success. Mesobiliverdin IXα (MBV), a natural BV analog derived from microalgae, offers a path to overcome the limitations of BV. MBV production is scalable, and it can be obtained at high purity. MBV and BV share important structural features (e.g., bridging propionate groups) and both are substrates of biliverdin reductase A (BVRA), …

Linking Water Quality And Climate Change To Long-Term Trends In Species Abundance In Norwalk Harbor, Viktoria Savatorova, Aidan Kieft, Nicole C. Spiller, Kasey Burns

Spora: A Journal of Biomathematics

This study examines the effects of environmental changes on fish populations in Norwalk Harbor, focusing on winter flounder (Pseudopleuronectes americanus), cunner (Tautogolabrus adspersus), northern pipefish (Syngnathus fuscus), and naked goby (Gobiosoma bosci) as examples of species responding to climate-related shifts. We analyze how water temperature, salinity, and dissolved oxygen correlate with fish abundance. To assess statistically significant differences in catch per unit effort (CPUE) across harbor regions, we applied the Kruskal-Wallis test followed by Dunn's post-hoc test. Seasonal variations in CPUE were examined by comparing monthly catch data for each species. K-means …

Phase Separation Clustering Of Poly Ubiquitin Cargos On Ternary Mixture Lipid Membranes By Synthetically Cross-Linked Ubiquitin Binder Peptides, Soojung Kim, Kamsy K. Okafor, Rina Tabuchi, Cedric Briones, Il Hyung Lee

Department of Chemistry and Biochemistry Faculty Scholarship and Creative Works

Ubiquitylation is involved in various physiological processes, such as signaling and vesicle trafficking, whereas ubiquitin (UB) is considered an important clinical target. The polymeric addition of UB enables cargo molecules to be recognized specifically by multivalent binding interactions with UB-binding proteins, which results in various downstream processes. Recently, protein condensate formation by ubiquitylated proteins has been reported in many independent UB processes, suggesting its potential role in governing the spatial organization of ubiquitylated cargo proteins. We created modular polymeric UB binding motifs and polymeric UB cargos by synthetic bioconjugation and protein purification. Giant unilamellar vesicles with lipid raft composition were …

International Expert Consensus On The Current Status And Future Prospects Of Artificial Intelligence In Metabolic And Bariatric Surgery, Mohammad Kermansaravi, Sonja Chiappetta, Shahab Shahabi Shahmiri, Julian Varas, Chetan Parmar, Yung Lee, Jerry T. Dang, Asim Shabbir, Daniel Hashimoto, Amir Hossein Davarpanah Jazi, Ozanan R. Meireles, Edo Aarts, Hazem Almomani, Aayad Alqahtani, Ali Aminian, Estuardo Behrens, Dieter Birk, Felipe J. Cantu, Ricardo V. Cohen, Maurizio De Luca, Nicola Di Lorenzo, Bruno Dillemans, Mohamad Hayssam Elfawal, Daniel Moritz Felsenreich, Michel Gagner, Hector Gabriel Galvan, Carlos Galvani, Khaled Gawdat, Omar M. Ghanem, Et Al

School of Medicine Faculty Publications

Artificial intelligence (AI) is transforming the landscape of medicine, including surgical science and practice. The evolution of AI from rule-based systems to advanced machine learning and deep learning algorithms has opened new avenues for its application in metabolic and bariatric surgery (MBS). AI has the potential to enhance various aspects of MBS, including education and training, decision-making, procedure planning, cost and time efficiency, optimization of surgical techniques, outcome and complication prediction, patient education, and access to care. However, concerns persist regarding the reliability of AI-generated decisions and associated ethical considerations. This study aims to establish a consensus on the role …

Solar Flare Prediction Using Multivariate Time Series Of Photospheric Magnetic Field Parameters: A Comparative Analysis Of Vector, Time Series, And Graph Data Representations, Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi

Computer Science Student Research

The purpose of this study is to provide a comprehensive resource for the selection of data representations for machine learning-oriented models and components in solar flare prediction tasks. Major solar flares occurring in the solar corona and heliosphere can bring potential destructive consequences, posing significant risks to astronauts, space stations, electronics, communication systems, and numerous technological infrastructures. For this reason, the accurate detection of major flares is essential for mitigating these hazards and ensuring the safety of our technology-dependent society. In response, leveraging machine learning techniques for predicting solar flares has emerged as a significant application within the realm of …

A Deep Sparse Capsule Network For Non-Invasive Blood Glucose Level Estimation Using A Ppg Sensor, Narmatha Chellamani, Saleh Ali Albelwi, Manimurugan Shanmuganathan, Palanisamy Amirthalingam, Emad Muteb Alharbi, Hibah Qasem Salman Alatawi, Kousalya Prabahar, Jawhara Bader Aljabri, Anand Paul

School of Public Health Faculty Publications

Diabetes, a chronic medical condition, affects millions of people worldwide and requires consistent monitoring of blood glucose levels (BGLs). Traditional invasive methods for BGL monitoring can be challenging and painful for patients. This study introduces a non-invasive, deep learning (DL)-based approach to estimate BGL using photoplethysmography (PPG) signals. Specifically, a Deep Sparse Capsule Network (DSCNet) model is proposed to provide accurate and robust BGL monitoring. The proposed model’s workflow includes data collection, preprocessing, feature extraction, and predictions. A hardware module was designed using a PPG sensor and Raspberry Pi to collect patient data. In preprocessing, a Savitzky–Golay filter and moving …

03.17.2025 Ored Connect, Liz Williamson

ORED Newsletter

SPA director Andrea Rich

ARC Nomination Deadline Extended