Performance under pressure in skill tasks: An analysis of professional darts

Ötting M, Deutscher C, Schneemann S, Langrock R, Gehrmann S, Scholten H. Performance under pressure in skill tasks: An analysis of professional darts. PLOS ONE. 2020;15(2): e0228870.Understanding and predicting how individuals perform in high-pressure situations is of importance in designing and managing workplaces. We investigate performance under pressure in professional darts as a near-ideal setting with no direct interaction between players and a high number of observations per subject. Analyzing almost one year of tournament data covering 32,274 dart throws, we find no evidence in favor of either choking or excelling under pressure

Finite temperature fluctuation-induced order and responses in magnetic topological insulators

We derive an effective field theory model for magnetic topological insulators and predict that a magnetic electronic gap persists on the surface for temperatures above the ordering temperature of the bulk. Our analysis also applies to interfaces of heterostructures consisting of a ferromagnetic and a topological insulator. In order to make quantitative predictions for MnBi2Te4 and for EuS-Bi2Se3 heterostructures, we combine the effective field theory method with density functional theory and Monte Carlo simulations. For MnBi2Te4 we predict an upwards Néel temperature shift at the surface up to 15%, while the EuS-Bi2Se3 interface exhibits a smaller relative shift. The effective theory also predicts induced Dzyaloshinskii-Moriya interactions and a topological magnetoelectric effect, both of which feature a finite temperature and chemical potential dependence

CAS: Centre for advanced studies

An introduction to the Centre for Advanced Studies.JRC.A.5-Scientific Developmen

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

The Demand for English Premier League Soccer Betting

Deutscher C, Ötting M, Schneemann S, Scholten H. The Demand for English Premier League Soccer Betting. JOURNAL OF SPORTS ECONOMICS. 2019;20(4):556-579.Betting markets have grown considerably lately. Despite their impact on the economic importance of professional sports, they just received academic interest recently. This article determines factors affecting the amount of money bet as well as the number of matched bets placed on the largest European soccer league, namely, the English Premier League between 2009-2010 and 2015-2016. Data from the betting exchange Betfair suggest season progress, weekday, number of substitutes, both teams market values, as well as uncertainty of outcome to determine market transactions and, hence, the economic importance

The Demand for English Premier League Soccer Betting

Deutscher C, Ötting M, Schneemann S, Scholten H. The Demand for English Premier League Soccer Betting. JOURNAL OF SPORTS ECONOMICS. 2019;20(4):556-579.Betting markets have grown considerably lately. Despite their impact on the economic importance of professional sports, they just received academic interest recently. This article determines factors affecting the amount of money bet as well as the number of matched bets placed on the largest European soccer league, namely, the English Premier League between 2009-2010 and 2015-2016. Data from the betting exchange Betfair suggest season progress, weekday, number of substitutes, both teams market values, as well as uncertainty of outcome to determine market transactions and, hence, the economic importance

Unifying learning object repositories in MACE

During the last years a series of repositories containing leaning contents for architecture have been created. With all these repositories financed, designed, implemented and maintained independently of each other, valuable and expensive information contained in the repositories lies — scattered over several European countries — in several thousand learning objects. With each single repository holding its own set of learning objects and metadata schemas describing them and not being connected to others, the contents are unnecessary hard to find and cannot be used to the full extent possible. This is partly due to legal and to technical difficulties. In MACE, we aim to overcome these issues and create an infrastructure to enable the discovery and identification of learning objects all across different repositories in a uniform way.status: publishe