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- Creator:
- Clemett, Nathaniel M, Collette, Matthew D, and Simmons, Benjamin
- Description:
- To produce this dataset, three modes of the flywheel were tested. The first was with the flywheel off, which produced a baseline for roll without stabilization. The second mode was active stabilization with the flywheel spinning. An IMU on board took in roll in degrees. An Arduino uno used the roll angle to precess the flywheel to a degree that countered the roll. The last mode was passive stabilization with the flywheel on. Here, the precession belt was removed which allowed the flywheel to freely precess and counter the moment generated by the roll.
- Discipline:
- Engineering
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- Creator:
- Zalta, Alyson K., Vanderboll, Kathryn, Dent, Amy L., Contreras, Isaias M., Malek, Nadia, Lascano, Xrystyan N., Zellner, Kelly L., Grandhi, Jyotsna, Araujo, Precious J., Straka, Kelci, Liang, Cathy Z., Czarny, Jordyn E., Martinez, Jazmin, and Burgess, Helen J.
- Description:
- An individual participant data meta-analysis was conducted to examine 1) the degree to which bedtime, wake time, and chronotype correlate with posttraumatic stress disorder (PTSD) severity among individuals diagnosed with PTSD, 2) the standardized mean difference in bedtime, wake time, and chronotype for those with and without a PTSD diagnosis, and 3) moderators of these relationships. This deposit includes the full dataset used for data analyses. No proprietary software is required to open any of these files.
- Keyword:
- Psychology, Posttraumatic Stress Disorder, Sleep Timing, Chronotype, and Meta-Analysis
- Citation to related publication:
- Zalta, A. K., Vanderboll, K., Dent, A. L., Contreras, I. M., Malek, N., Lascano, X. N., Zellner, K. L., Grandhi, J., Araujo, P. J., Straka, K., Liang, C. Z., Czarny, J. E., Martinez, J., & Burgess, H. J. (2023). Sleep timing, chronotype, and posttraumatic stress disorder: An individual participant data meta-analysis. Psychiatry research, 321, 115061. Advance online publication. https://doi.org/10.1016/j.psychres.2023.115061
- Discipline:
- Health Sciences
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- Creator:
- Krupka, Erin
- Description:
- The survey data used in this project is from two larger overarching projects titled the Rice Preferences Study and the Black Student Success Study. The Rice Preferences Study began with a sample of 661 entering undergraduates matriculating in August of 2016. This was 66.7% of the entering class, randomly selected. Of that sample, 553 completed the study with an 83.7% response rate. Prior to coming to campus in fall 2016 Rice students were given a battery of incentivized preference measures including risk aversion, loss aversion, altruism, in-group favoritism, time discounting, competitiveness, and so on. Over the subsequent four years that group was tested with new and repeated measures, in two to four tests per year. As a basis for comparison, each year a smaller sample (between 112 And 148) was drawn from incoming classes and tested with the same instruments. The remaining students from the Class of 2020 who had never been tested were invited in March 2020 to complete the initial study (259 of 376 completed the study). In March 2020, as Rice University closed, the team joined together to build a COVID module for the long-term Rice panel, as well as the other members of the Class of 2020. A total of 670 participated in this wave (67.1% of the graduating class). The Black Student Success Study recruited samples from PVAMU and TAMU in 2017 and again in 2019. This study aimed at understanding the effects of stereotype threat on Black student success in two different university environments in Texas: PVAMU, a historically Black university with about 9,000 students, 65% female, and 83% Black; and TAMU, a large state university with about 70,000 students, 47% female and 3.7% Black. That study was ongoing in 2020 when COVID struck. A total of 880 subjects responded to the initial survey out of a total of 3,709 who were contacted. Black subjects were over-sampled at TAMU, and constituted 37% of the TAMU sample. Respondents completed a one-hour survey that included measures of identity, non-cognitive skills, stereotype-threat vulnerability, and controls for economic preferences (survey measures) and family background. They were paid $20 for completing the study. In March 2020 additional funding was awarded through NSF to expand and follow the Rice, TAMU and PVAMU panels, focusing on the impact of COVID-19.
- Keyword:
- Norms, Preferences, Social Identity, COVID-19
- Discipline:
- Social Sciences
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- Creator:
- Hoover, Lindzey V
- Description:
- This study investigated co-occurrence among food addiction (FA), problematic substance use (alcohol, cannabis, cigarettes, nicotine vaping), parental history of problematic alcohol use, and obesity. Participants (n=357) completed self-report measures on food addiction, personal substance use, and parental history of alcohol use. Participants also completed demographic questions and self-reported height and weight were used to calculate BMI. Pearson zero-order correlations were conducted to identify sociodemographic covariates (socioeconomic status, age, and sex at birth). Modified Poisson regression (with robust standard error estimations) were used to estimate risk ratios among food addiction, parental history of problematic alcohol use, personal substance use (alcohol, cannabis, cigarettes, nicotine vaping), and obesity. Significance was set at p<.05. However, given multiple testing, 99% CI estimates are reported in the final manuscript instead of 95% CI estimates. Unadjusted and adjusted (for sociodemographic covariates) analyses were conducted. Risk of food addiction was higher in participants with problematic alcohol, smoking, vaping, parental history of problematic alcohol use, and (in unadjusted only) cannabis use. Risk of food addiction was only higher in participants with obesity after adjusting for covariates. Obesity was not significantly associated with problematic substance use and parental history or problematic alcohol use. Thus, food addiction, but not obesity, co-occurred with problematic substance use and a family history of problematic alcohol use. Results support the conceptualization of food addiction as an addictive disorder.
- Keyword:
- Food Addiction, Substance Use, Obesity, and Family History
- Citation to related publication:
- Hoover, L. V., Yu, H. P., Cummings, J. R., Ferguson, S. G., & Gearhardt, A. N. (2022). Co-occurrence of food addiction, obesity, problematic substance use, and parental history of problematic alcohol use. Psychology of Addictive Behaviors. Advance online publication. DOI: 10.1037/adb0000870
- Discipline:
- Social Sciences
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- Creator:
- Hoover, Lindzey V
- Description:
- This study investigated the mediating role of emotion dysregulation in the association between childhood trauma and food addiction. Participants (n=310) completed self-report measures of food addiction, childhood trauma experiences, emotion dysregulation, and demographic variables. Pearson zero-order correlations were conducted to identify potential covariates. Age, socioeconomic status, BMI, and education were significantly associated with study variables and were included as covariates in analyses. Moderated mediational analyses were used to investigate whether DERS (emotion regulation) mediated the association between the CTQ (childhood trauma) and YFAS2.0 (food addiction) and to explore whether gender identity (men vs women) moderated this association. Emotion dysregulation partially mediated associations between food addiction and childhood trauma. Gender moderated associations between childhood trauma and emotion dysregulation as well as childhood trauma and food addiction. Both moderating pathways were significantly stronger for men compared to women. Results suggest that emotion dysregulation may be an important mediating factor in the association between childhood trauma and food addiction, particularly for men.
- Keyword:
- childhood trauma, food addiction, emotion dysregulation, and gender differences
- Citation to related publication:
- Hoover, L. V., Yu, H. P., Duval, E. R., & Gearhardt, A. N. (2022). Childhood trauma and food addiction: The role of emotion regulation difficulties and gender differences. Appetite. Advance online publication. DOI: 10.1016/j.appet.2022.106137
- Discipline:
- Social Sciences
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- Creator:
- Thomer, Andrea K. , Starks, Joseph R. , Rayburn, Alexandria, and Lenard, Michael
- Description:
- This dataset is the results from qualitatively coding the 76 articles that represent the dataset from our literature review. We categorized papers according to their approach (case study, other research project, position paper), setting (library, museum, research lab), and publication domain (library information science, computer science, domain publication, other). We also coded for the focus of the paper, and whether motivating needs were listed as a reason for migration.
- Citation to related publication:
- Thomer, AK, Starks, JS, Rayburn, A, Lenard, M. Maintaining repositories, databases, and digital collections in memory institutions: an integrative review. Accepted at the 85th Annual Association for Information Science and Technology.
- Discipline:
- Social Sciences
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- Creator:
- Liemohn, Michael W, Adam, Joshua G, and Ganushkina, Natalia Y
- Description:
- Many statistical tools have been developed to aid in the assessment of a numerical model’s quality at reproducing observations. Some of these techniques focus on the identification of events within the data set, times when the observed value is beyond some threshold value that defines it as a value of keen interest. An example of this is whether it will rain, in which events are defined as any precipitation above some defined amount. A method called the sliding threshold of observation for numeric evaluation (STONE) curve sweeps the event definition threshold of both the model output and the observations, resulting in the identification of threshold intervals for which the model does well at sorting the observations into events and nonevents. An excellent data-model comparison will have a smooth STONE curve, but the STONE curve can have wiggles and ripples in it. These features reveal clusters when the model systematically overestimates or underestimates the observations. This study establishes the connection between features in the STONE curve and attributes of the data-model relationship. The method is applied to a space weather example.
- Keyword:
- space physics, statistical methods, and STONE curve
- Citation to related publication:
- Liemohn, M. W., Adam, J. G., & Ganushkina, N. Y. (2022). Analysis of features in a sliding threshold of observation for numeric evaluation (STONE) curve. Space Weather, 20, e2022SW003102. https://doi.org/10.1029/2022SW003102
- Discipline:
- Science
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- Creator:
- Hoffmann, Alex
- Description:
- This data contains 3 magnetometer signals of 4 noise sources. It was created to test a Underdetermined Blind Source Separation algorithm for magnetic signals.
- Keyword:
- Signal Processing, Magnetic Field, Underdetermined Blind Source Separation , UBSS, and BSS
- Discipline:
- Engineering
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- Creator:
- Larson, Joanna G and Weiner, Abraham
- Description:
- This dataset consists of 11 linear external morphological measurements from 1,614 adult frog individuals from 434 species that all naturally occur in the Western Hemisphere. We used these data to investigate patterns of multidimensional morphospace structure in frog assemblages along the latitudinal diversity gradient in the Americas. The measured traits are predictive of adult microhabitat use, diel activity patterns, locomotion, mating habitat, and diet.
- Keyword:
- functional traits, morphology, frog, anura, and amphibian
- Citation to related publication:
- Larson, JG, PO Title, and DL Rabosky. Expansion and packing of frog morphospace along the Western Hemisphere latitudinal diversity gradient revealed by functional traits. In prep
- Discipline:
- Science
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- Creator:
- Brian C. Weeks
- Description:
- Description: Each folder contains all of the data for a specific specimen; the folder names correspond to the University of Michigan Museum of Zoology catalog number for the specimen. Folders with a “-“ in the name are individual specimens that were photographed multiple independent times; the number following the “-“ indicates the repetition number (i.e. the folder named “UMMZ_242382-10” contains the tenth set of photographs for specimen UMMZ 242382). The photographs are necessary to train and test the Skelevision model, which is a computer vision approach to identifying and measuring elements of the skeleton (length of the tibiotarsus, tarsometatarsus, femur, humerus, ulna, radius, carpometacarpus, 2nd digit 1st phalanx, skull, and keel; the outer diameter of the sclerotic ring at its widest point; and the distance from the back of the skull to the tip of the bill). The data span 115 species of passerines across 79 genera from 59 families.
- Keyword:
- Bird skeleton, neural network, and functional traits
- Citation to related publication:
- Weeks, B.C., Zhou, Z., O’Brien, B., Darling, R., Dean, M., Dias, T., Hassena, G., Zhang, M., and Fouhey, D.F. 2022. A deep neural network for high throughput measurement of functional traits on museum skeletal specimens. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.13864
- Discipline:
- Science