Don't believe it! A global perspective on cognitive reflection and conspiracy theories about COVID-19 pandemic

The COVID-19 pandemic increased the saliency of an old phenomenon – conspiracy theories. In times of a global crisis and an unprecedented access to information, fake news seems to spread as fast as the virus. A global pandemic requires more than ever self-compliance. Only behavior change and vaccination on a large scale can bring us to normality. Yet believing in conspiracy theories about COVID-19 is expected to undermine such compliance. What determines susceptibility to believing in misinformation? In this study, using data on mostly representative samples of 45 countries around the world (38,113 participants), we found evidence that people with more deliberate thinking are less likely to believe in conspiracy theories. Furthermore, on the individual level people who are more prone to believe in conspiracy theories are less likely to comply with behavior change. We are in the midst of the biggest coordination game and such insights in social psychology can inform policymakers

A Comparison of the Red Green Blue Air Mass Imagery and Hyperspectral Infrared Retrieved Profiles

The Red Green Blue (RGB) Air Mass imagery is derived from multiple channels or paired channel differences. Multiple channel products typically provide additional information than a single channel can provide alone. The RGB Air Mass imagery simplifies the interpretation of temperature and moisture characteristics of air masses surrounding synoptic and mesoscale features. Despite the ease of interpretation of multiple channel products, the combination of channels and channel differences means the resulting product does not represent a quantity or physical parameter such as brightness temperature in conventional single channel satellite imagery. Without a specific quantity to reference, forecasters are often confused as to what RGB products represent. Hyperspectral infrared retrieved profiles of temperature, moisture, and ozone can provide insight about the air mass represented on the RGB Air Mass product and provide confidence in the product and representation of air masses despite the lack of a quantity to reference for interpretation. This study focuses on RGB Air Mass analysis of Hurricane Sandy as it moved north along the U.S. East Coast, while transitioning to a hybrid extratropical storm. Soundings and total column ozone retrievals were analyzed using data from the Cross-track Infrared and Advanced Technology Microwave Sounder Suite (CrIMSS) on the Suomi National Polar Orbiting Partnership satellite and the Atmospheric Infrared Sounder (AIRS) on the National Aeronautics and Space Administration Aqua satellite along with dropsondes that were collected from National Oceanic and Atmospheric Administration and Air Force research aircraft. By comparing these datasets to the RGB Air Mass, it is possible to capture quantitative information that could help in analyzing the synoptic environment enough to diagnose the onset of extratropical transition. This was done by identifying any stratospheric air intrusions (SAIs) that existed in the vicinity of Sandy as the wind field expanded and the cloud pattern evolved into an atypical pattern

Relationships of Chute-Side Measurements to Carcass Measurements

Three data sets were compiled to determine the relationship of weight, performance, hip height and ultrasound-measured fat thickness to hot carcass weight and fat thickness. Weight is generally the best predictor of relative differences in carcass weight at any time in the production system. Hip heights do not predict relative differences in carcass weight. Although the combination of hip height and weight is a more precise indicator of carcass weight than is hip height alone, generally this combination is inferior to weight alone. Only ultrasound-measured fat thickness predicted relative differences in fat thickness. Prediction of relative differences in carcass weight from body weight and fat thickness from ultrasound scans improved as marketing date approached

Impact of the Assimilation of Hyperspectral Infrared Retrieved Profiles on Advanced Weather and Research Model Simulations of a Non-Convective Wind Event

Non-convective wind events commonly occur with passing extratropical cyclones and have significant societal and economic impacts. Since non-convective winds often occur in the absence of specific phenomena such as a thunderstorm, tornado, or hurricane, the public are less likely to heed high wind warnings and continue daily activities. Thus non-convective wind events result in as many fatalities as straight line thunderstorm winds. One physical explanation for non-convective winds includes tropopause folds. Improved model representation of stratospheric air and associated non-convective wind events could improve non-convective wind forecasts and associated warnings. In recent years, satellite data assimilation has improved skill in forecasting extratropical cyclones; however errors still remain in forecasting the position and strength of extratropical cyclones as well as the tropopause folding process. The goal of this study is to determine the impact of assimilating satellite temperature and moisture retrieved profiles from hyperspectral infrared (IR) sounders (i.e. Atmospheric Infrared Sounder (AIRS), Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI)) on the model representation of the tropopause fold and an associated high wind event that impacted the Northeast United States on 09 February 2013. Model simulations using the Advanced Research Weather Research and Forecasting Model (ARW) were conducted on a 12-km grid with cycled data assimilation mimicking the operational North American Model (NAM). The results from the satellite assimilation run are compared to a control experiment (without hyperspectral IR retrievals), 32-km North American Regional Reanalysis (NARR) interpolated to a 12-km grid, and 13-km Rapid Refresh analyses

Sorting Strategies for Yearlings

One hundred sixty medium-framed English-cross steers were used in each year of a two-year study to determine effects of three sorting strategies on performance, carcass characteristics and profitability in an extensive beef production system. Sorting by weight before the grazing period or entering the feedlot decreased variation in carcass weight. Sorting by weight before the grazing period increased marbling scores and resulted in significantly higher premiums. However, no sorting strategy significantly increased carcass weight or improved profitability

Sorting Strategies for Yearlings

One hundred sixty medium-framed English-cross steers were used in each year of a two-year study to determine effects of three sorting strategies on performance, carcass characteristics and profitability in an extensive beef production system. Sorting by weight before the grazing period or entering the feedlot decreased variation in carcass weight. Sorting by weight before the grazing period increased marbling scores and resulted in significantly higher premiums. However, no sorting strategy significantly increased carcass weight or improved profitability