Molecular dynamics symulation of hydrogen diffusion in palladium

In the present work, the diffusion of hydrogen atoms in the crystal lattice of palladium was investigated using the molecular dynamics. The diffusion coefficients, activation energies and preexponential factors were determined for structures with different hydrogen concentration. It is determined that the diffusion coefficients decrease and the activation energy of diffusion grows with increasing concentrations of hydrogen

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Chronic immune barrier dysregulation among women with a history of violence victimization

We explored the association between violence victimization and increased risk for acquiring sexually transmitted infections (STIs) in women by measuring cellular immune barrier properties from the female reproductive tract. STI-negative participants reporting repeated prior victimization occurrences through the lifetime trauma and victimization history (LTVH) instrument were more likely to exhibit alterations in barrier homeostasis and the composition of critical immune mediators irrespective of demographic parameters or presence of bacterial vaginosis. By combining cellular data with mixed-effect linear modeling, we uncovered differences in local T cells, MHCII+ antigen-presenting cells, and epithelial cells indicative of altered trafficking behavior, increased immunosuppressive function, and decreased barrier integrity at sites of STI exposure that correlate most strongly with LTVH score. These data evidence a biological link between a history of violence victimization and risk of STI acquisition through immune dysregulation in the female reproductive tract.US CDC; Emory University; NIH [R01HL122559, 1R15AI113457-01A1, K23HD078153-01A1]; Emory University Center for AIDS research [P30AI050409]; Atlanta Clinical and Translational Sciences Institute [KLR2TR000455, UL1TR000454]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]