Climate change and human health in Alpine environments: an interdisciplinary impact chain approach understanding today's risks to address tomorrow's challenges.

The European Alps, home to a blend of permanent residents and millions of annual tourists, are found to be particularly sensitive to climate change. This article employs the impact chain concept to explore the interplay between climate change and health in Alpine areas, offering an interdisciplinary assessment of current and future health consequences and potential adaptation strategies.Rising temperatures, shifting precipitation patterns and increasing extreme weather events have profound implications for the Alpine regions.

Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy.

Shallow landslides represent potentially damaging processes in mountain areas worldwide. These geomorphic processes are usually caused by an interplay of predisposing, preparatory, and triggering environmental factors. At regional scales, data-driven methods have been used to model shallow landslides by addressing the spatial and temporal components separately.

Evaluation of potential changes in landslide susceptibility and landslide occurrence frequency in China under climate change.

Climate change can alter the frequency and intensity of extreme rainfall across the globe, leading to changes in hazards posed by rainfall-induced landslides. In recent decades, China suffered great human and economic losses due to rainfall-induced landslides. However, how the landslide hazard situation will evolve in the future is still unclear, also because of sparse comprehensive evaluations of potential changes in landslide susceptibility and landslide occurrence frequency under climate change.

Correlation does not imply geomorphic causation in data-driven landslide susceptibility modelling - Benefits of exploring landslide data collection effects.

Data-driven landslide susceptibility models formally integrate spatial landslide information with explanatory environmental variables that describe predisposing factors of slope instability. Well-performing models are commonly utilized to identify landslide-prone terrain or to understand the causes of slope instability. In most cases, however, the available landslide data is affected by spatial biases (e.

Synthesis of novel benzoic acid derivatives with benzothiazolyl subunit and evaluation as aldose reductase inhibitors.

Several methyl benzothiazolyloxybenzoates, S-isosters, and the corresponding benzoic acids were synthesized and tested as aldose reductase inhibitors (ARIs). Out of this series, the ester derivative 2a-7 was found to exhibit the highest enzyme-inhibitoric activity. In order to investigate this unexpected result, further modifications were carried out which allowed us to explain this finding and to open a path to a novel class of ARIs.