Rate and duration of hospitalisation for acute pulmonary embolism in the real-world clinical practice of different countries : Analysis from the RIETE registry

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Compositional response of Amazon forests to climate change.

Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate-induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long-term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO2 concentrations): maximum tree size, biogeographic water-deficit affiliation and wood density. Tree communities have become increasingly dominated by large-statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry-affiliated genera have become more abundant, while the mortality of wet-affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry-affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate-change drivers, but yet to significantly impact whole-community composition. The Amazon observational record suggests that the increase in atmospheric CO2 is driving a shift within tree communities to large-statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change

A cost-effective sensor system to train light weight juggling using an interactive virtual reality interface

This paper presents a novel approach to train how to juggle using a sensor system based on one of the most commercial, sophisticated and accessible input devices, the Wii Remote controller. This platform, particularly its infrared camera, is used to develop a real-time sensor system for hand motion tracking and fit it into a virtual reality interface. The quality of our algorithm was tested through this 3D virtual interface, which has the finality to give the user visual feedback of his/her hand positions, and created for the user the sensation of juggling