THREE-DIMENSIONAL KINEMATICS OF THE BATTED BALL IN BASEBALL: THE EFFECT OF SPIN ON THE BALL TRAJECTORY AND FLIGHT DISTANCE

The purpose of this study was to describe the three-dimensional kinematics of batted baseballs toward the same-field, center-field, and opposite-field, and estimate the effect of ball spin on trajectory and flight distance. Two collegiate baseball players performed free-batting, and they were instructed to hit a ball as far as possible in each direction. Twenty-seven trials were analyzed, and compared the ball kinematics among three hitting directions. The mean flight distance for the center-field was greater than that of the other fields. For the same-field and opposite-field, the amount of side spin components was larger than that of the center-field. Thus, it was indicated that the batted ball trajectories for the same-field and opposite-field were curved due to the Magnus force works horizontally, and flight distance tended to be shorter than that of the center-field

Reducing nitrogen footprints of consumer-level food loss and protein overconsumption in Japan, considering gender and age differences

The agro-food system perturbs the nitrogen (N) cycle through its N loads to the environment. The present study focused on food-related consumer-level N loads in Japan from 1961–2015, with a particular focus on food loss and protein overconsumption. Gender and age differences were also analyzed. Consumer-level food loss was negligible until the 1970s, when it began to slowly increase, accounting for an average of 13.2% of the annual net supply during 2011–2015. Japanese people have consumed more protein than the World Health Organization’s recommended intake since 1961. Protein overconsumption increased until the mid-1990s, when it began to decrease, but it still accounted for an average of 32.3% of total annual protein consumption during 2011–2015. The national mean of food N footprints (total release of reactive N into the environment related to individual food consumption) in the same period was 18.3 kg N capita ^–1 yr ^–1 , of which food loss accounted for 4% and protein overconsumption for 37%. The food N footprint of each sex/age class varied from 16.0–21.6 kg N capita ^–1 yr ^–1 , males had a larger footprint in each age class. Seven scenarios to reduce the N footprints were evaluated; a scenario that included halving protein overconsumption, livestock meat consumption, and food loss was estimated to reduce the food N footprint by 31%. Thus, there is room for reducing consumer-induced N loads to the environment. Campaigns aimed at boosting healthy and environmentally friendly diets should consider the diverse consumption patterns of different sex and age classes

Impacts of El Nino Southern Oscillation on the Global Yields of Major Crops

The monitoring and prediction of climate-induced variations in crop yields, production and export prices in major food-producing regions have become important to enable national governments in import-dependent countries to ensure supplies of affordable food for consumers. Although the El Nino/Southern Oscillation (ENSO) often affects seasonal temperature and precipitation, and thus crop yields in many regions, the overall impacts of ENSO on global yields are uncertain. Here we present a global map of the impacts of ENSO on the yields of major crops and quantify its impacts on their global-mean yield anomalies. Results show that El Nino likely improves the global-mean soybean yield by 2.15.4 but appears to change the yields of maize, rice and wheat by -4.3 to +0.8. The global-mean yields of all four crops during La Nina years tend to be below normal (-4.5 to 0.0).Our findings highlight the importance of ENSO to global crop production

The Global Gridded Crop Model Intercomparison phase 1 simulation dataset

The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual data fields at a spatial resolution of 0.5 arc-degree longitude and latitude. Fourteen crop modeling groups provided output for up to 11 historical input datasets spanning 1901 to 2012, and for up to three different management harmonization levels. Each group submitted data for up to 15 different crops and for up to 14 output variables. All simulations were conducted for purely rainfed and near-perfectly irrigated conditions on all land areas irrespective of whether the crop or irrigation system is currently used there. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts, and insights on how to further improve global gridded crop model frameworks. We describe dataset characteristics and individual model setup narratives. © 2019, The Author(s)

Microscopic approach to current-driven domain wall dynamics

This review describes in detail the essential techniques used in microscopic theories on spintronics. We have investigated the domain wall dynamics induced by electric current based on the $s$-$d$ exchange model. The domain wall is treated as rigid and planar and is described by two collective coordinates: the position and angle of wall magnetization. The effect of conduction electrons on the domain wall dynamics is calculated in the case of slowly varying spin structure (close to the adiabatic limit) by use of a gauge transformation. The spin-transfer torque and force on the wall are expressed by Feynman diagrams and calculated systematically using non-equilibrium Green's functions, treating electrons fully quantum mechanically. The wall dynamics is discussed based on two coupled equations of motion derived for two collective coordinates. The force is related to electron transport properties, resistivity, and the Hall effect. Effect of conduction electron spin relaxation on the torque and wall dynamics is also studied.Comment: manucript accepted to Phys. Re

Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark

Future change of daily precipitation indices in Japan: a stochastic weather generator-based bootstrap approach to provide probabilistic climate information

This study proposes the stochastic weather generator (WG)-based bootstrap approach to provide the probabilistic climate change information on mean precipitation as well as extremes, which applies a WG (i.e., LARS-WG) to daily precipitation under the present-day and future climate conditions derived from dynamical and statistical downscaling models. Additionally, the study intercompares the precipitation change scenarios derived from the multimodel ensemble for Japan focusing on five precipitation indices (mean precipitation, MEA; number of wet days, FRE; mean precipitation amount per wet day, INT; maximum number of consecutive dry days, CDD; and 90th percentile value of daily precipitation amount in wet days, Q90). Three regional climate models (RCMs: NHRCM, NRAMS and TWRF) are nested into the high-resolution atmosphere-ocean coupled general circulation model (MIROC3.2HI AOGCM) for A1B emission scenario. LARS-WG is validated and used to generate 2000 years of daily precipitation from sets of grid-specific parameters derived from the 20-year simulations from the RCMs and statistical downscaling model (SDM: CDFDM). Then 100 samples of the 20-year of continuous precipitation series are resampled, and mean values of precipitation indices are computed, which represents the randomness inherent in daily precipitation data. Based on these samples, the probabilities of change in the indices and the joint occurrence probability of extremes (CDD and Q90) are computed. High probabilities are found for the increases in heavy precipitation amount in spring and summer and elongated consecutive dry days in winter over Japan in the period 2081-2100, relative to 1981-2000. The joint probability increases in most areas throughout the year, suggesting higher potential risk of droughts and excess water-related disasters (e. g., floods) in a 20 year period in the future. The proposed approach offers more flexible way in estimating probabilities of multiple types of precipitation extremes including their joint probability compared to conventional approaches

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements