Suchergebnisse

Public-private partnerships (PPPs) have been widely used in infrastructure development in the past 30 years. However, a number of PPP projects have suffered serious risk scenarios and ended up with project failures. The change from a short-term contract period of traditional projects (fewer than five years) to a long-term contract period of PPP projects (20–30 years) has raised challenges to the traditional risk management. The high occurrence of renegotiations and early terminations of PPP projects suggest that ex ante risk management is no longer enough and ex post risk management is needed. This study aims to propose an ex post risk management model, under which renegotiations and early terminations are introduced. The application of this model begins with risk impact evaluation, then ex post risk response measures assessment, selection, and enforcement. An illustrative case is provided in the Appendix at the end of the article. The outputs of this study would facilitate governments' decision making in PPP projects under serious risk scenarios.

Justifiable usage of large-scale crop model simulations requires transparent, comprehensive and spatially extensive evaluations of their performance and associated accuracy. Simulated crop yields of a Pan-European implementation of the Environmental Policy Integrated Climate (EPIC) crop model were satisfactorily evaluated with reported regional yield data from EUROSTAT for four major crops, including winter wheat, rainfed and irrigated maize, spring barley and winter rye. European-wide land use, elevation, soil and daily meteorological gridded data were integrated in GIS and coupled with EPIC. Default EPIC crop and biophysical process parameter values were used with some minor adjustments according to suggestion from scientific literature. The model performance was improved by spatial calculations of crop sowing densities, potential heat units, operation schedules, and nutrient application rates. EPIC performed reasonable in the simulation of regional crop yields, with long-term averages predicted better than inter-annual variability: linear regression R2 ranged from 0.58 (maize) to 0.91 (spring barley) and relative estimation errors were between +-30% for most of the European regions. The modelled and reported crop yields demonstrated similar responses to driving meteorological variables. However, EPIC performed better in dry compared to wet years. A yield sensitivity analysis of crop nutrient and irrigation management factors and cultivar specific characteristics for contrasting regions in Europe revealed a range in model response and attainable yields. We also show that modelled crop yield is strongly dependent on the chosen PET method. The simulated crop yield variability was lower compared to reported crop yields. This assessment should contribute to the availability of harmonised and transparently evaluated agricultural modelling tools in the EU as well as the establishment of modelling benchmark as a requirement for sound and ongoing policy evaluations in the agricultural and environmental domains.

Justifiable usage of large-scale crop model simulations requires transparent, comprehensive and spatially extensive evaluations of their performance and associated accuracy. Simulated crop yields of a Pan-European implementation of the Environmental Policy Integrated Climate (EPIC) crop model were satisfactorily evaluated with reported regional yield data from EUROSTAT for four major crops, including winter wheat, rainfed and irrigated maize, spring barley and winter rye. European-wide land use, elevation, soil and daily meteorological gridded data were integrated in GIS and coupled with EPIC. Default EPIC crop and biophysical process parameter values were used with some minor adjustments according to suggestion from scientific literature. The model performance was improved by spatial calculations of crop sowing densities, potential heat units, operation schedules, and nutrient application rates. EPIC performed reasonable in the simulation of regional crop yields, with long-term averages predicted better than inter-annual variability: linear regression R2 ranged from 0.58 (maize) to 0.91 (spring barley) and relative estimation errors were between +-30% for most of the European regions. The modelled and reported crop yields demonstrated similar responses to driving meteorological variables. However, EPIC performed better in dry compared to wet years. A yield sensitivity analysis of crop nutrient and irrigation management factors and cultivar specific characteristics for contrasting regions in Europe revealed a range in model response and attainable yields. We also show that modelled crop yield is strongly dependent on the chosen PET method. The simulated crop yield variability was lower compared to reported crop yields. This assessment should contribute to the availability of harmonised and transparently evaluated agricultural modelling tools in the EU as well as the establishment of modelling benchmark as a requirement for sound and ongoing policy evaluations in the agricultural and environmental domains.

Alcohol is among the most widely used psychoactive substances worldwide. Ethanol metabolites such as acetate, thought to be primarily the result of ethanol breakdown by hepatic aldehyde dehydrogenase 2 (ALDH2), contribute to alcohol's behavioural effects and alcoholism. Here, we show that ALDH2 is expressed in astrocytes in the mouse cerebellum and that ethanol metabolism by astrocytic ALDH2 mediates behavioural effects associated with ethanol intoxication. We show that ALDH2 is expressed in astrocytes in specific brain regions and that astrocytic, but not hepatocytic, ALDH2 is required to produce ethanol-derived acetate in the mouse cerebellum. Cerebellar astrocytic ALDH2 mediates low-dose ethanol-induced elevation of GABA levels, enhancement of tonic inhibition and impairment of balance and coordination skills. Thus, astrocytic ALDH2 controls the production, cellular and behavioural effects of alcohol metabolites in a brain-region-specific manner. Our data indicate that astrocytic ALDH2 is an important, but previously under-recognized, target in the brain to alter alcohol pharmacokinetics and potentially treat alcohol use disorder. Copyright 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply. ; https://doi.org/10.1038/s42255-021-00357-z