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Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan Aug 2022

Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan

Publications

Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R2 (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …

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Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan Aug 2022

Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan

Data

Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R2 (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …

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Alternative Supplementary Cementitious Materials In Ultra-High Performance Concrete, Craig Newtson, Seyedsaleh Mousavinezhad, Gregory J. Gonzales, William K. Toledo, Judit M. Garcia Aug 2022

Alternative Supplementary Cementitious Materials In Ultra-High Performance Concrete, Craig Newtson, Seyedsaleh Mousavinezhad, Gregory J. Gonzales, William K. Toledo, Judit M. Garcia

Publications

Ultra-high performance concrete (UHPC) is an emerging material with remarkable mechanical and durability properties that contains large amounts of cementitious materials. Silica fume is a main supplementary cementitious material (SCM) in UHPC, however, it is more expensive than cement and other SCMs, so it is often substituted with inexpensive class F fly ash. Unfortunately, future availability of fly ash is uncertain as the energy industry moves toward renewable energy. Fly ash shortages create an urgent need to find cost-effective and environmentally-friendly alternatives for fly ash. This study investigated replacing cement, fly ash, and silica fume in UHPC mixtures with ground …

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A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal Aug 2022

A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal

Data

Pavement construction monitoring and quality assurance (QA) practices are mostly based on costly, discrete, and destructive methods. Most quality assurance programs are based on pavement construction procedures encompassing in-situ coring for layer thickness determination, density measurements, laboratory testing to measure volumetric properties, and smoothness measurements in case of the availability of a profiler. The main objective of this study was to develop a machine learning-based classifier for predicting pavement roughness and aggregate segregation based on digital image analysis, image recognition, and deep learning machine models. The developed Convolution Neural Networks (CNN) models were trained, tested, and validated using 600-pavement surface …

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Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments, Zahid Hossain, Rifat Bulut, Fares Tarhuni, Hussein Al-Dakheeli Aug 2022

Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments, Zahid Hossain, Rifat Bulut, Fares Tarhuni, Hussein Al-Dakheeli

Data

Arkansas produces the most of the rice in the United States. About 20% of poddy is rice husk (RH), which is burnt under controlled conditions to produce rice rusk ash (RHA). The RHA is considered an environmental hazard and a significant challenge for rice millers. However, RHA is rich in pozzolanic material, which is mainly silica. In this study, RHA is used to stabilize poor soils. Another commonly used stabilizer, hydrated lime (HL), has also been evaluated for comparison purposes. Thus, this study aimed to determine the optimum percentages of RHA, HL, or a combination of these two agents by …

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Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang Aug 2022

Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang

Publications

The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …

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Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt Aug 2022

Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt

Data

Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …

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Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang Aug 2022

Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang

Data

The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …

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Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques, Momen R. Mousa, Marwa Hassan Aug 2022

Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques, Momen R. Mousa, Marwa Hassan

Data

Performance prediction models are used by state agencies to predict future trends in distress indices, hence, determining the required maintenance and/or rehabilitation treatment as well as the deterioration rate and remaining pavement service life. However, most of these models are based on a limited number of parameters and cannot predict the performance distress indices reliably. Such limitation resulted in having, most of the time, a maximum prediction period of five years. As a solution and coping with the ever-increasing size of pavement data, machine learning techniques have become a promising alternative. The objective of this study was to develop a …

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Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D Aug 2022

Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D

Publications

Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …

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Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D Aug 2022

Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D

Data

Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …

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Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt Aug 2022

Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt

Publications

Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …

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Relational Turbulence And Social Network Engagement During The Summer Of Covid-19: A Repeated Measures, Dyadic Analysis, Kellie S. Brisini, Denise H. Solomon Aug 2022

Relational Turbulence And Social Network Engagement During The Summer Of Covid-19: A Repeated Measures, Dyadic Analysis, Kellie S. Brisini, Denise H. Solomon

Faculty Publications

Background/Purpose: Relational turbulence theory suggests that changes in and around relationships create the potential for relational turbulence when everyday routines and scripts are upended and communication becomes polarized. In turn, perceptions of a romantic relationship as chaotic or tumultuous can influence a person’s engagement with their social network. Alternately, previous research also suggests that engagement with friends and family has the potential to influence married partner’s relationship quality. Research Design: This study examined these propositions among a sample of married couples (N = 64, 128 individuals) whose daily experiences and relationship dynamics changed during the COVID-19 lockdown period. Results/Conclusions: Based …

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Developing A Conceptual Passive Contact Tracing System For Commercial Buildings Using Wifi Indoor Positioning, Sorena Vosoughkhosravi, Amirhosein Jafari Aug 2022

Developing A Conceptual Passive Contact Tracing System For Commercial Buildings Using Wifi Indoor Positioning, Sorena Vosoughkhosravi, Amirhosein Jafari

Faculty Publications

Contact tracing is one of the critical tools for fighting against pandemic disease outbreaks, such as the fast-growing SARS-CoV-2 virus and its different variants. At present, automated contact tracing systems face two main challenges: (1) requiring application installation on smart devices and (2) protecting the users’ privacy. This study introduces a conceptual passive contact tracing system using indoor WiFi positioning to address these challenges and investigate the role of such a system in commercial buildings. In this regard, this study uses a simulated small-office layout in a case study to demonstrate the applicability of the proposed system. The special use …

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The Need For A Framework Addressing The Temporal Aspects Of Fish Sperm Motility Leading To Community-Level Standardization, Harvey Blackburn, Leticia Torres, Yue Liu, Terrence R. Tiersch Aug 2022

The Need For A Framework Addressing The Temporal Aspects Of Fish Sperm Motility Leading To Community-Level Standardization, Harvey Blackburn, Leticia Torres, Yue Liu, Terrence R. Tiersch

Faculty Publications

Motility is a widely available parameter that can be used to assess sperm quality of aquatic species. Sperm from fishes with external fertilization usually undergo a dynamic and short-lived period of motility after activation. The common practice of assigning a single value at an arbitrary peak of motility presents challenges for reproducibility, community-level standardization, and comparisons across studies. This study aimed to explore statistical approaches to standardize motility reporting, and to develop an initial framework for community-level standards. Sperm samples from 14 zebrafish (Danio rerio) with a total of 21,705 cells were analyzed by use of computer-assisted sperm analysis with …

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Icam-1 Abundance Is Increased In Pancreatic Islets Of Hyperglycemic Female Nod Mice And Is Rapidly Upregulated By Nf-Κb In Pancreatic B-Cells, Thomas M. Martin, Susan J. Burke, Heidi M. Batdorf, David H. Burk, Sujoy Ghosh, Samuel D. Dupuy, Michael D. Karlstad, J. Jason Collier Aug 2022

Icam-1 Abundance Is Increased In Pancreatic Islets Of Hyperglycemic Female Nod Mice And Is Rapidly Upregulated By Nf-Κb In Pancreatic B-Cells, Thomas M. Martin, Susan J. Burke, Heidi M. Batdorf, David H. Burk, Sujoy Ghosh, Samuel D. Dupuy, Michael D. Karlstad, J. Jason Collier

Division of Basic Science Faculty Publications

Type 1 diabetes (T1D) is classified as an autoimmune disease where pancreatic b-cells are specifically targeted by cells of the immune system. The molecular mechanisms underlying this process are not completely understood. Herein, we identified that the Icam1 gene and ICAM-1 protein were selectively elevated in female NOD mice relative to male mice, fitting with the sexual dimorphism of diabetes onset in this key mouse model of T1D. In addition, ICAM-1 abundance was greater in hyperglycemic female NOD mice than in age-matched normoglycemic female NOD mice. Moreover, we discovered that the Icam1 gene was rapidly upregulated in response to IL-1β …

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A Higher Proportion Of Small Adipocytes Is Associated With Increased Visceral And Ectopic Lipid Accumulation During Weight Gain In Response To Overfeeding In Men, Ursula White, Robbie A. Beyl, Eric Ravussin Aug 2022

A Higher Proportion Of Small Adipocytes Is Associated With Increased Visceral And Ectopic Lipid Accumulation During Weight Gain In Response To Overfeeding In Men, Ursula White, Robbie A. Beyl, Eric Ravussin

Clinical Research Faculty Publications

Background: Adipose tissue (AT) expansion occurs by hypertrophy (increase in size) and hyperplasia (increase in number) of adipocytes. The AT expandability hypothesis postulates that impaired subcutaneous AT expansion leads to ectopic fat accretion, contributing to impaired metabolic health. The role of adipogenesis as a contributing factor is debatable. Subjects/Methods: In the present analysis, we assess changes in adipocyte size distribution in relation to changes in ectopic fat accretion in response to 8-weeks of overfeeding in 22 men (28 ± 5.4 years; BMI 25.5 ± 2.3 kg/m2) who were fed 40% over their baseline energy requirements. Results: Participants gained 6.7 ± …

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Reply To G Taubes, Mi Friedman, And V Torres-Carot Et Al., Kevin D. Hall, I. Sadaf Farooqi, Jeffery M. Friedman, Samuel Klein, Ruth J.F. Loos, David J. Mangelsdorf, Stephen O’Rahilly, Eric Ravussin, Leanne M. Redman, Donna H. Ryan, John R. Speakman, Deirdre K. Tobias Aug 2022

Reply To G Taubes, Mi Friedman, And V Torres-Carot Et Al., Kevin D. Hall, I. Sadaf Farooqi, Jeffery M. Friedman, Samuel Klein, Ruth J.F. Loos, David J. Mangelsdorf, Stephen O’Rahilly, Eric Ravussin, Leanne M. Redman, Donna H. Ryan, John R. Speakman, Deirdre K. Tobias

Clinical Research Faculty Publications

No abstract provided.

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Nutritional Quality Of Calorie Restricted Diets In The Calerie™ 1 Trial, Susan B. Racette, Valene Garr Barry, Connie W. Bales, Megan A. Mccrory, Kathleen A. Obert, Cheryl H. Gilhooly, Susan B. Roberts, Corby K. Martin, Catherine Champagne, Sai Krupa Das Aug 2022

Nutritional Quality Of Calorie Restricted Diets In The Calerie™ 1 Trial, Susan B. Racette, Valene Garr Barry, Connie W. Bales, Megan A. Mccrory, Kathleen A. Obert, Cheryl H. Gilhooly, Susan B. Roberts, Corby K. Martin, Catherine Champagne, Sai Krupa Das

Clinical Research Faculty Publications

Objectives: The aim was to determine the nutritional adequacy of calorie restricted (CR) diets during CR interventions up to 12 months. Methods: The Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy (CALERIE™) phase 1 trial consisted of 3 single-site studies to test the feasibility and effectiveness of CR in adults without obesity. After baseline assessments, participants who were randomized to a CR intervention received education and training from registered dietitians on how to follow a healthful CR diet. Food diaries were completed at baseline and during the CR interventions (~6, 9, and 12 months) when participants were self-selecting …

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Testosterone Undecanoate Administration Prevents Declines In Fat-Free Mass But Not Physical Performance During Simulated Multi-Stressor Military Operations, Alyssa N. Varanoske, Melissa N. Harris, Callie Hebert, Emily E. Howard, Neil M. Johannsen, Steven B. Heymsfield, Frank L. Greenway, Lee M. Margolis, Harris R. Lieberman, Robbie A. Beyl, David D. Church, Arny A. Ferrando, Stefan M. Pasiakos, Jennifer C. Rood Aug 2022

Testosterone Undecanoate Administration Prevents Declines In Fat-Free Mass But Not Physical Performance During Simulated Multi-Stressor Military Operations, Alyssa N. Varanoske, Melissa N. Harris, Callie Hebert, Emily E. Howard, Neil M. Johannsen, Steven B. Heymsfield, Frank L. Greenway, Lee M. Margolis, Harris R. Lieberman, Robbie A. Beyl, David D. Church, Arny A. Ferrando, Stefan M. Pasiakos, Jennifer C. Rood

Clinical Research Faculty Publications

Male military personnel conducting strenuous operations experience reduced testosterone concentrations, muscle mass, and physical performance. Pharmacological restoration of normal testosterone concentrations may attenuate performance decrements by mitigating muscle mass loss. Previously, administering testosterone enanthate (200 mg/wk) during 28 days of energy deficit prompted supraphysiological testosterone concentrations and lean mass gain without preventing isokinetic/isometric deterioration. Whether administering a practical dose of testosterone protects muscle and performance during strenuous operations is undetermined. The objective of this study was to test the effects of a single dose of testosterone undecanoate on body composition and military-relevant physical performance during a simulated operation. After a …

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Gradient And Acceleration Of Decline In Physical And Cognitive Functions In Older Adults: A Disparity Analysis, H. Ip Edward, Shyh Huei Chen, W. Jack Rejeski, Karen Bandeen-Roche, Kathleen M. Hayden, Christina E. Hugenschmidt, June Pierce, Michael E. Miller, Jaime L. Speiser, Stephen B. Kritchevsky, Denise K. Houston, Robert L. Newton, Stephen R. Rapp, Dalane W. Kitzman Aug 2022

Gradient And Acceleration Of Decline In Physical And Cognitive Functions In Older Adults: A Disparity Analysis, H. Ip Edward, Shyh Huei Chen, W. Jack Rejeski, Karen Bandeen-Roche, Kathleen M. Hayden, Christina E. Hugenschmidt, June Pierce, Michael E. Miller, Jaime L. Speiser, Stephen B. Kritchevsky, Denise K. Houston, Robert L. Newton, Stephen R. Rapp, Dalane W. Kitzman

Population and Public Health Science Faculty Publications

Background: Substantive previous work has shown that both gait speed and global cognition decline as people age. Rates of their decline, as opposed to cross-sectional measurements, could be more informative of future functional status and other clinical outcomes because they more accurately represent deteriorating systems. Additionally, understanding the sex and racial disparity in the speed of deterioration, if any, is also important as ethnic minorities are at an increased risk of mobility disability and dementia. Method: Data from 2 large longitudinal intervention studies were integrated. Rates of decline were derived from individual-level measures of gait speed of 400-m walk and …

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Obesity Management In The Primary Prevention Of Hepatocellular Carcinoma, Elizabeth R.M. Zunica, Elizabeth C. Heintz, Christopher L. Axelrod, John P. Kirwan Aug 2022

Obesity Management In The Primary Prevention Of Hepatocellular Carcinoma, Elizabeth R.M. Zunica, Elizabeth C. Heintz, Christopher L. Axelrod, John P. Kirwan

Division of Basic Science Faculty Publications

Hepatocellular carcinoma (HCC) is the most frequent primary hepatic malignancy and a leading cause of cancer-related death globally. HCC is associated with an indolent clinical presentation, resulting in frequent advanced stage diagnoses where surgical resection or transplant therapies are not an option and medical therapies are largely ineffective at improving survival. As such, there is a critical need to identify and enhance primary prevention strategies to mitigate HCC-related morbidity and mortality. Obesity is an independent risk factor for the onset and progression of HCC. Furthermore, obesity is a leading cause of nonalcoholic steatohepatitis (NASH), the fasting growing etiological factor of …

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Comparison Of Weight Loss Data Collected By Research Technicians Versus Electronic Medical Records: The Propel Trial, Peter T. Katzmarzyk, Emily F. Mire, Emily F. Mire, Corby K. Martin, Robert L. Newton, Robert L. Newton, John W. Apolzan, John W. Apolzan, Eboni G. Price-Haywood, Eboni G. Price-Haywood, Kara D. Denstel, Kara D. Denstel, Ronald Horswell, San T. Chu, William D. Johnson, Corby K. Martin, William D. Johnson, Robert K. Singletary, Cheryl Lewis, Phillip Brantley, Ronald Horswell, Betty Kennedy, Dachuan Zhang, Stephanie Authement, Shiquita Brooks, Danielle S. Burrell, Leslie Forest-Everage, Angelle Graham Ullmer, Laurie Murphy, Cristalyn Reynolds, Kevin Sanders, Stephen Bower, Hillary Gahagan, Tabitha K. Gray Aug 2022

Comparison Of Weight Loss Data Collected By Research Technicians Versus Electronic Medical Records: The Propel Trial, Peter T. Katzmarzyk, Emily F. Mire, Emily F. Mire, Corby K. Martin, Robert L. Newton, Robert L. Newton, John W. Apolzan, John W. Apolzan, Eboni G. Price-Haywood, Eboni G. Price-Haywood, Kara D. Denstel, Kara D. Denstel, Ronald Horswell, San T. Chu, William D. Johnson, Corby K. Martin, William D. Johnson, Robert K. Singletary, Cheryl Lewis, Phillip Brantley, Ronald Horswell, Betty Kennedy, Dachuan Zhang, Stephanie Authement, Shiquita Brooks, Danielle S. Burrell, Leslie Forest-Everage, Angelle Graham Ullmer, Laurie Murphy, Cristalyn Reynolds, Kevin Sanders, Stephen Bower, Hillary Gahagan, Tabitha K. Gray

Clinical Research Faculty Publications

Background/objectives: Pragmatic trials are increasingly used to study the implementation of weight loss interventions in real-world settings. This study compared researcher-measured body weights versus electronic medical record (EMR)-derived body weights from a pragmatic trial conducted in an underserved patient population. Subjects/methods: The PROPEL trial randomly allocated 18 clinics to usual care (UC) or to an intensive lifestyle intervention (ILI) designed to promote weight loss. Weight was measured by trained technicians at baseline and at 6, 12, 18, and 24 months. A total of 11 clinics (6 UC/5 ILI) with 577 enrolled patients also provided EMR data (n = 561), which …

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Density Of States And Delocalization For Discrete Magnetic Random Schrödinger Operators, Simon Becker, Rui Han Aug 2022

Density Of States And Delocalization For Discrete Magnetic Random Schrödinger Operators, Simon Becker, Rui Han

Faculty Publications

We study discrete magnetic random Schrödinger operators on the square and honeycomb lattice. For the non-random magnetic operator on the hexagonal lattice with any rational magnetic flux, we show that the middle two dispersion surfaces exhibit Dirac cones. We then derive an asymptotic expansion for the density of states on the honeycomb lattice for oscillations of arbitrary rational magnetic flux. This allows us, as a corollary, to rigorously study the quantum Hall effect and conclude dynamical delocalization close to the conical point under disorder. We obtain similar results for the discrete random Schrödinger operator on the Z2-lattice with …

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Valley-Floor Snowfall In Taylor Valley, Antarctica, From 1995 To 2017: Spring, Summer And Autumn, Madeline E. Myers, Peter T. Doran, Krista F. Myers Aug 2022

Valley-Floor Snowfall In Taylor Valley, Antarctica, From 1995 To 2017: Spring, Summer And Autumn, Madeline E. Myers, Peter T. Doran, Krista F. Myers

Faculty Publications

We present an analysis of the 20 year snowfall dataset in Taylor Valley and the results of a new snow cover monitoring study. Snowfall has been measured at four sites in Taylor Valley from 1995 to 2017. We focus on valley-floor snowfall when wind does not exceed 5 m s-1, and we exclude winter from our analysis due to poor data quality. Snowfall averaged 11 mm water equivalent (w.e.) from 1995 to 2017 across all stations and ranged from 1 to 58 mm w.e. Standard deviations ranged from 3 to 17 mm w.e., highlighting the strong interannual variability of snowfall …

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Measurement Of Neutron-Capture Cross Sections Of Ge70,72 Using The Dance Facility, A. Laminack, J. C. Blackmon, A. Couture, J. P. Greene, M. Krtička, K. T. Macon, S. Mosby, C. Prokop, J. L. Ullmann, S. Valenta Aug 2022

Measurement Of Neutron-Capture Cross Sections Of Ge70,72 Using The Dance Facility, A. Laminack, J. C. Blackmon, A. Couture, J. P. Greene, M. Krtička, K. T. Macon, S. Mosby, C. Prokop, J. L. Ullmann, S. Valenta

Faculty Publications

Background: Approximately half of all atomic nuclei heavier than iron are synthesized by the slow neutron-capture process. The weak component of this process is not well understood and the reaction rates of each isotope in the s-process path affect nucleosynthesis abundances downstream. Purpose: To measure the neutron-capture cross sections of two weak s-process nuclei, Ge70,72, using the neutron time-of-flight technique. Measuring the capture cross sections for isotopes in this region of the chart of nuclides has proven challenging due to dominant scattering cross sections. Method: Samples consisted of pellets made of pressed enriched metallic powders. The Ge70,72 neutron-capture cross sections …

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Improving The Low-Energy Transient Sensitivity Of Amego-X Using Single-Site Events, I. Martinez-Castellanos, Henrike Fleischhack, C. Karwin, M. Negro, D. Tak, Amy Lien, C. A. Kierans, Zorawar Wadiasingh, Yasushi Fukazawa, Marco Ajello, Matthew G. Baring, E. Burns, R. Caputo, Dieter H. Hartmann, Jeremy S. Perkins, Judith L. Racusin, Yong Sheng Aug 2022

Improving The Low-Energy Transient Sensitivity Of Amego-X Using Single-Site Events, I. Martinez-Castellanos, Henrike Fleischhack, C. Karwin, M. Negro, D. Tak, Amy Lien, C. A. Kierans, Zorawar Wadiasingh, Yasushi Fukazawa, Marco Ajello, Matthew G. Baring, E. Burns, R. Caputo, Dieter H. Hartmann, Jeremy S. Perkins, Judith L. Racusin, Yong Sheng

Faculty Publications

AMEGO-X, the All-sky Medium Energy Gamma-ray Observatory eXplorer, is a proposed instrument designed to bridge the so-called “MeV gap” by surveying the sky with unprecedented sensitivity from ∼100 keV to about 1 GeV. This energy band is of key importance for multimessenger and multiwavelength studies but it is nevertheless currently underexplored. AMEGO-X addresses this situation by proposing a design capable of detecting and imaging gamma rays via both Compton interactions and pair production processes. However, some of the objects that AMEGO-X will study, such as gamma-ray bursts and magnetars, extend to energies below ∼100 keV where the dominant interaction becomes …

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Weak Thermal State Quadrature-Noise Shadow Imaging, Pratik J. Barge, Ziqi Niu, Savannah L. Cuozzo, Eugeniy E. Mikhailov, Irina Novikova, Hwang Lee, Lior Cohen Aug 2022

Weak Thermal State Quadrature-Noise Shadow Imaging, Pratik J. Barge, Ziqi Niu, Savannah L. Cuozzo, Eugeniy E. Mikhailov, Irina Novikova, Hwang Lee, Lior Cohen

Faculty Publications

In this work, we theoretically and experimentally demonstrate the possibility to create an image of an opaque object using a few-photon thermal optical field. We utilize the quadrature-noise shadow imaging (QSI) technique that detects the changes in the quadrature-noise statistics of the probe beam after its interaction with an object. We show that such a thermal QSI scheme has an advantage over the classical differential imaging when the effect of dark counts is considered. At the same time, the easy availability of thermal sources for any wavelength makes the method practical for broad range of applications, not accessible with, e.g., …

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Interviewing For Residency Positions While Completing A Graduate Degree: Considerations For Graduate Students, Mentors, And Program Directors, Wayne Newhauser, Garrett Pitcher, Christine Swanson, Samuel G. Armato, Hania Al-Hallaq Aug 2022

Interviewing For Residency Positions While Completing A Graduate Degree: Considerations For Graduate Students, Mentors, And Program Directors, Wayne Newhauser, Garrett Pitcher, Christine Swanson, Samuel G. Armato, Hania Al-Hallaq

Faculty Publications

No abstract provided.

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Ogle-2018-Blg-0799lb: A Q ∼2.7 × 10-3planet With Spitzer Parallax, Weicheng Zang, Yossi Shvartzvald, Andrzej Udalski, Jennifer C. Yee, Chung Uk Lee, Takahiro Sumi, Xiangyu Zhang, Hongjing Yang, Shude Mao, Sebastiano Calchi Novati, Andrew Gould, Wei Zhu, Charles A. Beichman, Geoffery Bryden, Sean Carey, B. Scott Gaudi, Calen B. Henderson, Przemek Mróz, Jan Skowron, Radoslaw Poleski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Krzysztof Ulaczyk, Krzysztof A. Rybicki, Patryk Iwanek, Marcin Wrona, Michael D. Albrow, Sun Ju Chung, Cheongho Han, Kyu Ha Hwang, Youn Kil Jung Aug 2022

Ogle-2018-Blg-0799lb: A Q ∼2.7 × 10-3planet With Spitzer Parallax, Weicheng Zang, Yossi Shvartzvald, Andrzej Udalski, Jennifer C. Yee, Chung Uk Lee, Takahiro Sumi, Xiangyu Zhang, Hongjing Yang, Shude Mao, Sebastiano Calchi Novati, Andrew Gould, Wei Zhu, Charles A. Beichman, Geoffery Bryden, Sean Carey, B. Scott Gaudi, Calen B. Henderson, Przemek Mróz, Jan Skowron, Radoslaw Poleski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Krzysztof Ulaczyk, Krzysztof A. Rybicki, Patryk Iwanek, Marcin Wrona, Michael D. Albrow, Sun Ju Chung, Cheongho Han, Kyu Ha Hwang, Youn Kil Jung

Faculty Publications

We report the discovery and analysis of a planet in the microlensing event OGLE-2018-BLG-0799. The planetary signal was observed by several ground-based telescopes, and the planet-host mass ratio is q = (2.65 ± 0.16) × 10-3. The ground-based observations yield a constraint on the angular Einstein radius θE, and the microlensing parallax vector πE, is strongly constrained by the Spitzer data. However, the 2019 Spitzer baseline data reveal systematics in the Spitzer photometry, so there is ambiguity in the magnitude of the parallax. In our preferred interpretation, a full Bayesian analysis using a Galactic model indicates that the planetary system …

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