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Faculty Publications

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Scintillation Light Detection In The 6-M Drift-Length Protodune Dual Phase Liquid Argon Tpc, A. Abed, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. Alrashed, C. Alt, Roberto Petti, Sanjib R. Mishra Ph.D., Et. Al. Jul 2022

Scintillation Light Detection In The 6-M Drift-Length Protodune Dual Phase Liquid Argon Tpc, A. Abed, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. Alrashed, C. Alt, Roberto Petti, Sanjib R. Mishra Ph.D., Et. Al.

Faculty Publications

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6×6×6 m3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected …

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Predicting Pavement Structural Condition Using Machine Learning Methods, Nazmus Sakib Ahmed, Nathan Huynh, Sarah Gassman, Robert Mullen, Charles Pierce, Yuche Chen Jul 2022

Predicting Pavement Structural Condition Using Machine Learning Methods, Nazmus Sakib Ahmed, Nathan Huynh, Sarah Gassman, Robert Mullen, Charles Pierce, Yuche Chen

Faculty Publications

State departments of transportation recognize the need to incorporate pavement structural condition in their pavement performance models and/or decision processes used to select candidate projects for preservation, rehabilitation, or reconstruction at the network level. However, pavement structural condition data are costly to obtain. To this end, this paper develops and evaluates the effectiveness of two machine learning methods, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), for predicting a flexible pavement’s structural condition. The aim is to be able to predict whether a pavement section’s structural condition is poor or not based on Annual Average Daily Traffic (AADT), truck percentage, …

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An Acoustofluidic Scanning Nanoscope Using Enhanced Image Stacking And Processing, Geonsoo Jin, Joseph Rich, Jianping Xia, Albert J. He, Chenglong Zhao, Tony Jun Huang Jul 2022

An Acoustofluidic Scanning Nanoscope Using Enhanced Image Stacking And Processing, Geonsoo Jin, Joseph Rich, Jianping Xia, Albert J. He, Chenglong Zhao, Tony Jun Huang

Faculty Publications

Nanoscale optical resolution with a large field of view is a critical feature for many research and industry areas, such as semiconductor fabrication, biomedical imaging, and nanoscale material identification. Several scanning microscopes have been developed to resolve the inverse relationship between the resolution and field of view; however, those scanning microscopes still rely upon fluorescence labeling and complex optical systems. To overcome these limitations, we developed a dual-camera acoustofluidic nanoscope with a seamless image merging algorithm (alpha-blending process). This design allows us to precisely image both the sample and the microspheres simultaneously and accurately track the particle path and location. …

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Isotopic Evidence For Sources Of Dissolved Carbon And The Role Of Organic Matter Respiration In The Fraser River Basin, Canada, Britta M. Voss, Timothy I. Eglinton, Bernhard Peucker-Ehrenbrink, Valier Galy, Susan Q. Lang Ph.D., M.S., B.S., Cameron Mcintyre, Robert G.M. Spencer, Ekaterina Bulygina, Zhaohui Aleck Wang, Katherine A. Guay Jul 2022

Isotopic Evidence For Sources Of Dissolved Carbon And The Role Of Organic Matter Respiration In The Fraser River Basin, Canada, Britta M. Voss, Timothy I. Eglinton, Bernhard Peucker-Ehrenbrink, Valier Galy, Susan Q. Lang Ph.D., M.S., B.S., Cameron Mcintyre, Robert G.M. Spencer, Ekaterina Bulygina, Zhaohui Aleck Wang, Katherine A. Guay

Faculty Publications

Sources of dissolved and particulate carbon to the Fraser River system vary significantly in space and time. Tributaries in the northern interior of the basin consistently deliver higher concentrations of dissolved organic carbon (DOC) to the main stem than other tributaries. Based on samples collected near the Fraser River mouth throughout 2013, the radiocarbon age of DOC exported from the Fraser River does not change significantly across seasons despite a spike in DOC concentration during the freshet, suggesting modulation of heterogeneous upstream chemical and isotopic signals during transit through the river basin. Dissolved inorganic carbon (DIC) concentrations are highest in …

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Structural Health Monitoring Of Fatigue Cracks For Steel Bridges With Wireless Large-Area Strain Sensors, Sdiq Anwar Taher, Jian Li, Jong-Hyun Jeong, Simon Laflamme, Hongki Jo, Caroline Bennett, William N. Collins, Austin Downey Jul 2022

Structural Health Monitoring Of Fatigue Cracks For Steel Bridges With Wireless Large-Area Strain Sensors, Sdiq Anwar Taher, Jian Li, Jong-Hyun Jeong, Simon Laflamme, Hongki Jo, Caroline Bennett, William N. Collins, Austin Downey

Faculty Publications

This paper presents a field implementation of the structural health monitoring (SHM) of fatigue cracks for steel bridge structures. Steel bridges experience fatigue cracks under repetitive traffic loading, which pose great threats to their structural integrity and can lead to catastrophic failures. Currently, accurate and reliable fatigue crack monitoring for the safety assessment of bridges is still a difficult task. On the other hand, wireless smart sensors have achieved great success in global SHM by enabling long-term modal identifications of civil structures. However, long-term field monitoring of localized damage such as fatigue cracks has been limited due to the lack …

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Circadiomics: Circadian Omic Web Portal, Muntaha Samad, Forest Agostinelli, Tomoki Sato, Kohei Shimaji, Pierre Baldi Jul 2022

Circadiomics: Circadian Omic Web Portal, Muntaha Samad, Forest Agostinelli, Tomoki Sato, Kohei Shimaji, Pierre Baldi

Faculty Publications

Circadian rhythms are a foundational aspect of biology. These rhythms are found at the molecular level in every cell of every living organism and they play a fundamental role in homeostasis and a variety of physiological processes. As a result, biomedical research of circadian rhythms continues to expand at a rapid pace. To support this research, CircadiOmics (http://circadiomics.igb.uci.edu/) is the largest annotated repository and analytic web server for high-throughput omic (e.g. transcriptomic, metabolomic, proteomic) circadian time series experimental data. CircadiOmics contains over 290 experiments and over 100 million individual measurements, across >20 unique tissues/organs, and 11 different species. Users are …

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Efficiently Searching Extreme Mechanical Properties Via Boundless Objective-Free Exploration And Minimal First-Principles Calculations, Joshua Ojih, Mohammed Al-Fahdi, Alejandro David Rodriguez, Kamal Choudhary, Ming Hu Jul 2022

Efficiently Searching Extreme Mechanical Properties Via Boundless Objective-Free Exploration And Minimal First-Principles Calculations, Joshua Ojih, Mohammed Al-Fahdi, Alejandro David Rodriguez, Kamal Choudhary, Ming Hu

Faculty Publications

Despite the machine learning (ML) methods have been largely used recently, the predicted materials properties usually cannot exceed the range of original training data. We deployed a boundless objective-free exploration approach to combine traditional ML and density functional theory (DFT) in searching extreme material properties. This combination not only improves the efficiency for screening large-scale materials with minimal DFT inquiry, but also yields properties beyond original training range. We use Stein novelty to recommend outliers and then verify using DFT. Validated data are then added into the training dataset for next round iteration. We test the loop of training-recommendation-validation in …

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Multi-Substituted Quinolines As Hiv-1 Integrase Allosteric Inhibitors, Long Phi Dinh, Jian Sun, Courtney D. Glenn, Krunal Patel, Julie A. Pigza, Matthew G. Donahue, Larry Yet, Jacques Kessl Jul 2022

Multi-Substituted Quinolines As Hiv-1 Integrase Allosteric Inhibitors, Long Phi Dinh, Jian Sun, Courtney D. Glenn, Krunal Patel, Julie A. Pigza, Matthew G. Donahue, Larry Yet, Jacques Kessl

Faculty Publications

Allosteric HIV-1 integrase (IN) inhibitors, or ALLINIs, are a new class of antiviral agents that bind at the dimer interface of the IN, away from the enzymatic catalytic site and block viral replication by triggering an aberrant multimerization of the viral enzyme. To further our understanding of the important binding features of multi-substituted quinoline-based ALLINIs, we have examined the IN multimerization and antiviral properties of substitution patterns at the 6 or 8 position. We found that the binding properties of these ALLINIs are negatively impacted by the presence of bulky substitutions at these positions. In addition, we have observed that …

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A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela Jul 2022

A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela

Faculty Publications

Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …

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A Wet/Dry Point Treatment Method Of Fvcom, Part Ii: Application To The Okatee/Colleton River In South Carolina, Changsheng Chen, Haosheng Huang, Huichan Lin, Jack Blanton, Chunyan Li, Francisco Andrade Jul 2022

A Wet/Dry Point Treatment Method Of Fvcom, Part Ii: Application To The Okatee/Colleton River In South Carolina, Changsheng Chen, Haosheng Huang, Huichan Lin, Jack Blanton, Chunyan Li, Francisco Andrade

Faculty Publications

The wet/dry point treatment method of FVCOM was applied to simulate the tide-induced flooding/drying process in the estuarine–tidal-creek–saltmarsh complex of the Okatee/Colleton River Estuary, South Carolina. The simulation results were compared with observed currents at three mooring sites and flooded areas observed from remote-sensing hypsometric measurements, demonstrating that FVCOM can robustly reproduce tidal and residual currents in the river and the flooding process onto the intertidal saltmarsh. The simulated flow field reveals that the Okatee/Colleton River Estuary is characterized by multiple residual eddies. Driven by the periodic tidal forcing, this estuarine system features a chaotic water transport process. Numerous residual …

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Event Based Approach For Modeling Indoor Airflow Patterns, Ehsan Mousavi, Arup Bhattacharya Jul 2022

Event Based Approach For Modeling Indoor Airflow Patterns, Ehsan Mousavi, Arup Bhattacharya

Faculty Publications

People spend a significant proportion of their time indoors, where the quality of indoor air affects the productivity, efficiency, and well-being of occupants. One of the oldest challenges in building construction is designing a ventilation system that ensures optimum indoor air quality. Acceptable indoor air should provide thermal comfort and minimize human exposure to contamination. Characterizing these two elements requires information on both heat/mass transfer in the microenvironment and the time-specific activity of individuals who move among these microenvironments. While researchers have utilized simulation tools to investigate this complex human-environment interaction, current numerical techniques severely limit the simulations to overly …

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Symplectic Effective Field Theory For Nuclear Structure Studies, D. Kekejian, J. P. Draayer, V. I. Mokeev, C. D. Roberts Jul 2022

Symplectic Effective Field Theory For Nuclear Structure Studies, D. Kekejian, J. P. Draayer, V. I. Mokeev, C. D. Roberts

Faculty Publications

A symplectic effective field theory that unveils the observed emergence of symplectic symmetry in atomic nuclei is advanced. Specifically, starting from a simple extension of the harmonic-oscillator Lagrangian, an effective field theory applied against symplectic basis states is shown to yield a Hamiltonian system with one fitted parameter. The scale of the system can be determined self-consistently as the ratio of the average volume of a nucleus assumed to be spherical to its volume as determined by the average number of oscillator quanta, which is stretched by the fact that the plane-wave solution satisfies the equations of motion at every …

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Droplet Behavior In Overexpanded Supersonic Two-Phase Jets, Shyam Menon, Mohana Gurunadhan Jul 2022

Droplet Behavior In Overexpanded Supersonic Two-Phase Jets, Shyam Menon, Mohana Gurunadhan

Faculty Publications

The interaction of liquid droplets generated by spray atomization with high-speed co-flowing gas is of interest in various applications including fuel injection, spray cooling, and surface coating. The underlying processes involve interactions between the droplets themselves, and with the carrier gas. Additionally, they are influenced by shock and expansion waves present in high-speed flows, accompanied by resulting velocity and pressure fluctuations. Non-intrusive diagnostics including Shadowgraphy and Phase Doppler Particle Anemometry, along with flow simulations, are used to study droplet behavior, characterized by size and velocity changes, as a finely atomized spray is propelled by a carrier gas through a supersonic, …

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Predicting Elastic Constants Of Refractory Complex Concentrated Alloys Using Machine Learning Approach, Uttam Bhandari, Hamed Ghadimi, Congyan Zhang, Shizhong Yang, Shengmin Guo Jul 2022

Predicting Elastic Constants Of Refractory Complex Concentrated Alloys Using Machine Learning Approach, Uttam Bhandari, Hamed Ghadimi, Congyan Zhang, Shizhong Yang, Shengmin Guo

Faculty Publications

Refractory complex concentrated alloys (RCCAs) have drawn increasing attention recently owing to their balanced mechanical properties, including excellent creep resistance, ductility, and oxidation resistance. The mechanical and thermal properties of RCCAs are directly linked with the elastic constants. However, it is time consuming and expensive to obtain the elastic constants of RCCAs with conventional trial-and-error experiments. The elastic constants of RCCAs are predicted using a combination of density functional theory simulation data and machine learning (ML) algorithms in this study. The elastic constants of several RCCAs are predicted using the random forest regressor, gradient boosting regressor (GBR), and XGBoost regression …

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Modeling A Decision Support System For Covid-19 Using Systems Dynamics And Fuzzy Inference, Vinayaka Gude Jul 2022

Modeling A Decision Support System For Covid-19 Using Systems Dynamics And Fuzzy Inference, Vinayaka Gude

Faculty Publications

Covid-19 has impacted the lives of people across the world with deaths and unprecedented economic damage. Countries have employed various restrictions and lockdowns to slow down the rate of its spread with varying degrees of success. This research aims to propose an optimal strategy for dealing with a pandemic taking the deaths and economy into account. A complete lockdown until vaccination is not suitable as it can destroy the economy, whereas having no restrictions would result in more Covid-19 cases. Therefore, there is a need for a dynamic model which can propose a suitable strategy depending on the economic and …

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Biometrics And An Ai Bill Of Rights, Margaret Hu Jul 2022

Biometrics And An Ai Bill Of Rights, Margaret Hu

Faculty Publications

This Article contends that an informed discussion on an AI Bill of Rights requires grappling with biometric data collection and its integration into emerging AI systems. Biometric AI systems serve a wide range of governmental purposes, including policing, border security and immigration enforcement, and biometric cyberintelligence and biometric-enabled warfare. These systems are increasingly categorized as "high-risk" when deployed in ways that may impact fundamental constitutional rights and human rights. There is growing recognition that high-risk biometric AI systems, such as facial recognition identification, can pose unprecedented challenges to criminal procedure rights. This Article concludes that a failure to recognize these …

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A Comparison Of Correlation-Agnostic Techniques For Magnetic Navigation, Clark N. Taylor, Josh Hiatt Jul 2022

A Comparison Of Correlation-Agnostic Techniques For Magnetic Navigation, Clark N. Taylor, Josh Hiatt

Faculty Publications

Navigation using a Global Navigation Satellite System (GNSS) is common for autonomous vehicles (ground or air). Unfortunately, GNSS-based navigation solutions are often susceptible to jamming, interference, and a limited number of satellites. A proposed technique to aid in navigation when a GNSS-based system fails is magnetic navigation - navigation using the Earth's magnetic anomaly field. This solution comes with its own set of problems including the need for quality magnetic maps in every area in which magnetic navigation will be used. Many of the currently available magnetic maps are generated from a combination of dated magnetic surveys, resulting in maps …

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“Where The Truth Really Lies”: Listening To Voices From African American Communities In The Southern States About Covid-19 Vaccine Information And Communication, Ran Zhang, Shan Qiao, Brooke Mckeever, Bankole Olatosi, Xiaoming Li Jun 2022

“Where The Truth Really Lies”: Listening To Voices From African American Communities In The Southern States About Covid-19 Vaccine Information And Communication, Ran Zhang, Shan Qiao, Brooke Mckeever, Bankole Olatosi, Xiaoming Li

Faculty Publications

The high uptake of COVID-19 vaccines is one of the most promising measures to control the pandemic. However, some African American (AA) communities exhibit vaccination hesitancy due to mis- or disinformation. It is important to understand the challenges in accessing reliable COVID-19 vaccine information and to develop feasible health communication interventions based on voices from AA communities. We conducted 2 focus group discussions (FGDs) among 18 community stakeholders recruited from 3 counties in South Carolina on 8 October and 29 October 2021. The FGDs were conducted online via Zoom meetings. The FGD data were managed and thematically analyzed using NVivo …

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Listening To Voices From African American Communities In The Southern States About Covid-19 Vaccine Information And Communication: A Qualitative Study, Ran Zhang, Shan Qiao, Bankole Olatosi Ph.D., Xiaoming Li Ph.D. Jun 2022

Listening To Voices From African American Communities In The Southern States About Covid-19 Vaccine Information And Communication: A Qualitative Study, Ran Zhang, Shan Qiao, Bankole Olatosi Ph.D., Xiaoming Li Ph.D.

Faculty Publications

The high uptake of COVID-19 vaccines is one of the most promising measures to control the pandemic. However, some African American (AA) communities exhibit vaccination hesitancy due to mis- or disinformation. It is important to understand the challenges in accessing reliable COVID-19 vaccine information and to develop feasible health communication interventions based on voices from AA communities. We conducted 2 focus group discussions (FGDs) among 18 community stakeholders recruited from 3 counties in South Carolina on 8 October and 29 October 2021. The FGDs were conducted online via Zoom meetings. The FGD data were managed and thematically analyzed using NVivo …

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Active 2d-Dna Fingerprinting Of Wirelesshart Adapters To Ensure Operational Integrity In Industrial Systems, Willie H. Mims, Michael A. Temple, Robert F. Mills Jun 2022

Active 2d-Dna Fingerprinting Of Wirelesshart Adapters To Ensure Operational Integrity In Industrial Systems, Willie H. Mims, Michael A. Temple, Robert F. Mills

Faculty Publications

The need for reliable communications in industrial systems becomes more evident as industries strive to increase reliance on automation. This trend has sustained the adoption of WirelessHART communications as a key enabling technology and its operational integrity must be ensured. This paper focuses on demonstrating pre-deployment counterfeit detection using active 2D Distinct Native Attribute (2D-DNA) fingerprinting. Counterfeit detection is demonstrated using experimentally collected signals from eight commercial WirelessHART adapters. Adapter fingerprints are used to train 56 Multiple Discriminant Analysis (MDA) models with each representing five authentic network devices. The three non-modeled devices are introduced as counterfeits and a total of …

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We Must Stop Fossil Fuel Emissions To Protect Permafrost Ecosystems, Benjamin W. Abbott, Michael Brown, Joanna C. Carey, Jessica G. Ernakovich, Jennifer M. Frederick, Laodong Guo, Gustaf Hugelius, Raymond M. Lee, Michael M. Loranty, Robie Macdonald, Paul J. Mann, Susan M. Natali, David Olefeldt, Pam Pearson, Abigail Rec, Martin Robards, Verity G. Salmon, Sara Sayedi, Christina Schadel, Edward A. G. Schuur, Sarah Shakil, Arial J. Shogren, Jens Strauss, Suzanne E. Tank, Brett F. Thornton, Rachael Treharne, Merritt Turetsky, Carolina Voigt, Nancy Wright, Yuanhe Yang, Jay P. Zarnetske, Qiwen Zhang, Scott Zolkos Jun 2022

We Must Stop Fossil Fuel Emissions To Protect Permafrost Ecosystems, Benjamin W. Abbott, Michael Brown, Joanna C. Carey, Jessica G. Ernakovich, Jennifer M. Frederick, Laodong Guo, Gustaf Hugelius, Raymond M. Lee, Michael M. Loranty, Robie Macdonald, Paul J. Mann, Susan M. Natali, David Olefeldt, Pam Pearson, Abigail Rec, Martin Robards, Verity G. Salmon, Sara Sayedi, Christina Schadel, Edward A. G. Schuur, Sarah Shakil, Arial J. Shogren, Jens Strauss, Suzanne E. Tank, Brett F. Thornton, Rachael Treharne, Merritt Turetsky, Carolina Voigt, Nancy Wright, Yuanhe Yang, Jay P. Zarnetske, Qiwen Zhang, Scott Zolkos

Faculty Publications

Climate change is an existential threat to the vast global permafrost domain. The diverse human cultures, ecological communities, and biogeochemical cycles of this tenth of the planet depend on the persistence of frozen conditions. The complexity, immensity, and remoteness of permafrost ecosystems make it difficult to grasp how quickly things are changing and what can be done about it. Here, we summarize terrestrial and marine changes in the permafrost domain with an eye toward global policy. While many questions remain, we know that continued fossil fuel burning is incompatible with the continued existence of the permafrost domain as we know …

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Allure: A Multi-Modal Guided Environment For Helping Children Learn To Solve A Rubik's Cube With Automatic Solving And Interactive Explanations, Kausik Lakkaraju, Thahimum Hassan, Vedant Khandelwal, Prathamjeet Singh, Cassidy Bradley, Ronak Shah, Forest Agostinelli, Biplav Srivastava, Dezhi Wu Jun 2022

Allure: A Multi-Modal Guided Environment For Helping Children Learn To Solve A Rubik's Cube With Automatic Solving And Interactive Explanations, Kausik Lakkaraju, Thahimum Hassan, Vedant Khandelwal, Prathamjeet Singh, Cassidy Bradley, Ronak Shah, Forest Agostinelli, Biplav Srivastava, Dezhi Wu

Faculty Publications

Modern artificial intelligence (AI) methods have been used to solve problems that many humans struggle to solve. This opens up new opportunities for knowledge discovery and education. We demonstrate ALLURE, a collaborative educational AI system for learning to solve the Rubik's cube that is designed to help students improve their problem solving skills. ALLURE can both find its own strategies for solving the Rubik's cube and explain those strategies to humans. In the future, ALLURE will also be able to collaborate with humans by building on user-provided strategies for solving the Rubik's cube and as well as generalize to other …

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Solving Inverse Conductivity Problems In Doubly Connected Domains By The Homogenization Functions Of Two Parameters, Jun Lu, Lianpeng Shi, Chein-Shan Liu, C.S. Chen Jun 2022

Solving Inverse Conductivity Problems In Doubly Connected Domains By The Homogenization Functions Of Two Parameters, Jun Lu, Lianpeng Shi, Chein-Shan Liu, C.S. Chen

Faculty Publications

In the paper, we make the first attempt to derive a family of two-parameter homogenization functions in the doubly connected domain, which is then applied as the bases of trial solutions for the inverse conductivity problems. The expansion coefficients are obtained by imposing an extra boundary condition on the inner boundary, which results in a linear system for the interpolation of the solution in a weighted Sobolev space. Then, we retrieve the spatial- or temperature-dependent conductivity function by solving a linear system, which is obtained from the collocation method applied to the nonlinear elliptic equation after inserting the solution. Although …

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Association Between The Dietary Inflammatory Index And Gastric Disease Risk: Findings From A Korean Population-Based Cohort Study, Sundara Raj Sreeja, Trong-Dat Le, Bang Wool Eom, Seung Hyun Oh, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert Scd, Mi Kyung Kim Jun 2022

Association Between The Dietary Inflammatory Index And Gastric Disease Risk: Findings From A Korean Population-Based Cohort Study, Sundara Raj Sreeja, Trong-Dat Le, Bang Wool Eom, Seung Hyun Oh, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert Scd, Mi Kyung Kim

Faculty Publications

Evidence suggests that diets with high pro-inflammatory potential may play a substantial role in the origin of gastric inflammation. This study aimed to examine the association between the energy-adjusted dietary inflammatory index (E-DIITM) and gastric diseases at baseline and after a mean follow-up of 7.4 years in a Korean population. A total of 144,196 participants from the Korean Genome and Epidemiology Study_Health Examination (KoGES_HEXA) cohort were included. E-DII scores were computed using a validated semi-quantitative food frequency questionnaire. Multivariate logistic regression and Cox proportional hazards regression were used to assess the association between the E-DII and gastric disease risk. In …

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Adolescent Health Risk Behaviors, Adverse Experiences, And Self-Reported Hunger: Analysis Of 10 States From The 2019 Youth Risk Behavior Surveys, Kathryn L. Krupsky, Sarah Silwa, Hilary Seligman, Andrea D. Brown, Angela D. Liese Ph.D., Zewditu Demissie, Ellen Barnidge Jun 2022

Adolescent Health Risk Behaviors, Adverse Experiences, And Self-Reported Hunger: Analysis Of 10 States From The 2019 Youth Risk Behavior Surveys, Kathryn L. Krupsky, Sarah Silwa, Hilary Seligman, Andrea D. Brown, Angela D. Liese Ph.D., Zewditu Demissie, Ellen Barnidge

Faculty Publications

We examined associations between adolescent self-reported hunger, health risk behaviors, and adverse experiences during the 2018–2019 school year. Youth Risk Behavior Survey data were pooled from 10 states. Prevalence ratios were calculated, and we assessed effect measure modification by sex. The prevalence of self-reported hunger was 13%. Self-reported hunger was associated with a higher prevalence of every health risk behavior/adverse experience analyzed, even after adjusting for sex, grade, and race/ethnicity. Sex did not modify associations. Findings underscore needs for longitudinal research with more robust measures of adolescent food insecurity to clarify the temporality of relationships.

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Search For Multimessenger Signals In Nova Coincident With Ligo/Virgo Detections, M. A. Acero, P. Adamson, L. Aliaga, T. Alion, V. Alakhberdian, N. Anfimov, A. Antoshkin, L. Asquith, A. Aurisano, A. Back, C. Backhouse, M. Biard, N. Balashov, P. Baldi, B. A. Bambah, S. Bashar, K. Bays, S. Bending, R. Bernstein, V. Bhatnagar, Roberto Petti, Et. Al. Jun 2022

Search For Multimessenger Signals In Nova Coincident With Ligo/Virgo Detections, M. A. Acero, P. Adamson, L. Aliaga, T. Alion, V. Alakhberdian, N. Anfimov, A. Antoshkin, L. Asquith, A. Aurisano, A. Back, C. Backhouse, M. Biard, N. Balashov, P. Baldi, B. A. Bambah, S. Bashar, K. Bays, S. Bending, R. Bernstein, V. Bhatnagar, Roberto Petti, Et. Al.

Faculty Publications

Using the NOvA neutrino detectors, a broad search has been performed for any signal coincident with 28 gravitational wave events detected by the LIGO/Virgo Collaboration between September 2015 and July 2019. For all of these events, NOvA is sensitive to possible arrival of neutrinos and cosmic rays of GeV and higher energies. For five (seven) events in the NOvA Far (Near) Detector, timely public alerts from the LIGO/Virgo Collaboration allowed recording of MeV-scale events. No signal candidates were found.

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Event-Related Brain Potential Correlates Of Event-Based Prospective Memory In Children With Learning Disability, Lili Jing, Qi Zhao, Yafei Zhang, Jiaojiao Wan, Xiaoming Li Ph.D. Jun 2022

Event-Related Brain Potential Correlates Of Event-Based Prospective Memory In Children With Learning Disability, Lili Jing, Qi Zhao, Yafei Zhang, Jiaojiao Wan, Xiaoming Li Ph.D.

Faculty Publications

Prospective memory (PM) has been reported to be impaired in children with learning disabilities (LD), but few studies have examined the underlying neural mechanism of this impairment. To address this issue, the present study applied ERP technique to explore the difference of event-based prospective memory (EBPM) in 21 children with LD and 20 non-LD children with double task paradigm. Results from behavioral data showed that LD children exhibited lower accuracy than non-LD children. The ERP results showed that the two groups displayed significant difference in the ERP components, with longer N300 latency in LD group, but there was no obvious …

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Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman Jun 2022

Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman

Faculty Publications

Purpose — Aircraft fail to meet mission capable rate goals due to a lack of supply of aircraft parts in inventory where the aircraft breaks. This triggers an order at the repair location. To maximize mission capable rate, the time from order to delivery needs to be minimized. The purpose of this research is to examine the case of three airfields for the order to delivery time of mission critical aircraft parts for a specific aircraft type. Design/methodology/approach — This research captured data from three information systems to assess the order fulfillment process. The data were analyzed to determine the …

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Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill Jun 2022

Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill

Faculty Publications

Purpose — This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of conflict. Design/methodology/approach — In this paper statistical learning methods are used to create new country clusters that are then used in a comparative analysis of model-based conflict prediction. Findings — In this study a reorganization of the countries assigned to specific areas of responsibility are shown to provide improvements in the ability of models to predict conflict. Research limitations/implications — The study is based on actual historical data and is purely data driven. …

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Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman Jun 2022

Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman

Faculty Publications

Purpose — Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.
Design/methodology/approach — This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the …

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