Mapping and characterization of small-scale aeolian structures on Mars: An example from the MSL landing site in Gale Crater

A new set of methodologies, which allow a simple and fast mapping and characterization of small-scale aeolian structures on Mars is introduced in this work. We follow an object-based approach in which the bedform crestlines are automatically mapped and characterized. From the methodology validation, we conclude that the quality of the obtained results is comparable with human-produced photointerpretations. We show that the accuracy associated with the measurement of mean trends from the automatically mapped patterns is less than 10°. Through the analysis of two areas located near the MSL landing site in Gale Crater, we explore some of the possibilities that the automatic mapping technique enables. Namely, for multitemporal surveys and ripple pattern analysis. We demonstrate how the mapped ripple patterns can be used to assess local wind orientations, and we analyze some examples that illustrate the diversity of wavelength spatial distributions that can be found on Mars. We try to relate these pattern wavelength variations with the possible local influence of granulometry and wind shear velocity

European study of research and development in mobility technology for persons with disabilities

In the fall of 2010, the National Science Foundation, the National Institutes of Health and the U.S. Veteran's Administration jointly supported a review of mobility technology in Europe. A delegation of American Scientists traveled to Europe to visit a number of research centers and engaged in a demonstration and dialogue related to the global state-of-the-art for mobility impairment rectification and augmentation. From the observations and exchanges between the U.S. delegation and host institutions, the researchers were able to derive a series of papers which are now published in this thematic series of Journal of NeuroEngineering and Rehabilitation. The papers describe the main themes of the European mobility technology research activities showing a healthy picture of research and innovation in the field

Estimating Alpha, Beta, and Gamma Diversity Through Deep Learning

The reliable mapping of species richness is a crucial step for the identification of areas of high conservation priority, alongside other value and threat considerations. This is commonly done by overlapping range maps of individual species, which requires dense availability of occurrence data or relies on assumptions about the presence of species in unsampled areas deemed suitable by environmental niche models. Here, we present a deep learning approach that directly estimates species richness, skipping the step of estimating individual species ranges. We train a neural network model based on species lists from inventory plots, which provide ground truth data for supervised machine learning. The model learns to predict species richness based on spatially associated variables, including climatic and geographic predictors, as well as counts of available species records from online databases. We assess the empirical utility of our approach by producing independently verifiable maps of alpha, beta, and gamma plant diversity at high spatial resolutions for Australia, a continent with highly heterogeneous diversity patterns. Our deep learning framework provides a powerful and flexible new approach for estimating biodiversity patterns, constituting a step forward toward automated biodiversity assessments

An Efficient Method to Take into Account Forecast Uncertainties in Large Scale Probabilistic Power Flow

The simulation of uncertainties due to renewable and load forecasts is becoming more and more important in security assessment analyses performed on large scale networks. This paper presents an efficient method to account for forecast uncertainties in probabilistic power flow (PPF) applications, based on the combination of PCA (Principal Component Analysis) and PEM (Point Estimate Method), in the context of operational planning studies applied to large scale AC grids. The benchmark against the conventional PEM method applied to large power system models shows that the proposed method assures high speed up ratios, preserving a good accuracy of the marginal distributions of the outputs

The past and future human impact on mammalian diversity

To understand the current biodiversity crisis, it is crucial to determine how humans have affected biodiversity in the past. However, the extent of human involvement in species extinctions from the Late Pleistocene onward remains contentious. Here, we apply Bayesian models to the fossil record to estimate how mammalian extinction rates have changed over the past 126,000 years, inferring specific times of rate increases. We specifically test the hypothesis of human-caused extinctions by using posterior predictive methods. We find that human population size is able to predict past extinctions with 96% accuracy. Predictors based on past climate, in contrast, perform no better than expected by chance, suggesting that climate had a negligible impact on global mammal extinctions. Based on current trends, we predict for the near future a rate escalation of unprecedented magnitude. Our results provide a comprehensive assessment of the human impact on past and predicted future extinctions of mammals

Estimating Age-Dependent Extinction: Contrasting Evidence from Fossils and Phylogenies.

The estimation of diversification rates is one of the most vividly debated topics in modern systematics, with considerable controversy surrounding the power of phylogenetic and fossil-based approaches in estimating extinction. Van Valen's seminal work from 1973 proposed the "Law of constant extinction," which states that the probability of extinction of taxa is not dependent on their age. This assumption of age-independent extinction has prevailed for decades with its assessment based on survivorship curves, which, however, do not directly account for the incompleteness of the fossil record, and have rarely been applied at the species level. Here, we present a Bayesian framework to estimate extinction rates from the fossil record accounting for age-dependent extinction (ADE). Our approach, unlike previous implementations, explicitly models unobserved species and accounts for the effects of fossil preservation on the observed longevity of sampled lineages. We assess the performance and robustness of our method through extensive simulations and apply it to a fossil data set of terrestrial Carnivora spanning the past 40 myr. We find strong evidence of ADE, as we detect the extinction rate to be highest in young species and declining with increasing species age. For comparison, we apply a recently developed analogous ADE model to a dated phylogeny of extant Carnivora. Although the phylogeny-based analysis also infers ADE, it indicates that the extinction rate, instead, increases with increasing taxon age. The estimated mean species longevity also differs substantially, with the fossil-based analyses estimating 2.0 myr, in contrast to 9.8 myr derived from the phylogeny-based inference. Scrutinizing these discrepancies, we find that both fossil and phylogeny-based ADE models are prone to high error rates when speciation and extinction rates increase or decrease through time. However, analyses of simulated and empirical data show that fossil-based inferences are more robust. This study shows that an accurate estimation of ADE from incomplete fossil data is possible when the effects of preservation are jointly modeled, thus allowing for a reassessment of Van Valen's model as a general rule in macroevolution

The flash flood of the Bisagno Creek on 9th October 2014: An “unfortunate” combination of spatial and temporal scales

SummaryOn the 9th October, 2014 a strong event hit the central part of Liguria Region producing disastrous consequences to the city of Genoa where the Bisagno Creek flooded causing one death and lots of damage. The precipitation pattern responsible for the event had peculiar spatial and temporal characteristics that led to an unexpected flash flood. The temporal sequence of rainfall intensities and the particular severity of rainfall showers at small temporal scale, together with the size of the sub-basin hit by the most intense part of the rainfall were the unfortunate concurrent ingredients that led to an “almost perfect” flash flood. The peak flow was estimated to be a 100–200years order return period.The effects of the spatial and temporal scales of the precipitation pattern were investigated by coupling a rainfall downscaling model with a hydrological model setting up an experiment that follows a probabilistic approach.Supposing that the correct volume of precipitation at different spatial and temporal scales is known, the experiment provided the probability of generating events with similar effects in terms of streamflow.Furthermore, the study gives indications regarding the goodness and reliability of the forecasted rainfall field needed, not only in terms of total rainfall volume, but even in spatial and temporal pattern, to produce the observed ground effects in terms of streamflow

Fossil biogeography: a new model to infer dispersal, extinction and sampling from palaeontological data.

Methods in historical biogeography have revolutionized our ability to infer the evolution of ancestral geographical ranges from phylogenies of extant taxa, the rates of dispersals, and biotic connectivity among areas. However, extant taxa are likely to provide limited and potentially biased information about past biogeographic processes, due to extinction, asymmetrical dispersals and variable connectivity among areas. Fossil data hold considerable information about past distribution of lineages, but suffer from largely incomplete sampling. Here we present a new dispersal-extinction-sampling (DES) model, which estimates biogeographic parameters using fossil occurrences instead of phylogenetic trees. The model estimates dispersal and extinction rates while explicitly accounting for the incompleteness of the fossil record. Rates can vary between areas and through time, thus providing the opportunity to assess complex scenarios of biogeographic evolution. We implement the DES model in a Bayesian framework and demonstrate through simulations that it can accurately infer all the relevant parameters. We demonstrate the use of our model by analysing the Cenozoic fossil record of land plants and inferring dispersal and extinction rates across Eurasia and North America. Our results show that biogeographic range evolution is not a time-homogeneous process, as assumed in most phylogenetic analyses, but varies through time and between areas. In our empirical assessment, this is shown by the striking predominance of plant dispersals from Eurasia into North America during the Eocene climatic cooling, followed by a shift in the opposite direction, and finally, a balance in biotic interchange since the middle Miocene. We conclude by discussing the potential of fossil-based analyses to test biogeographic hypotheses and improve phylogenetic methods in historical biogeography

Percutaneous transluminal angioplasty is feasible and effective in patients on chronic dialysis with severe peripheral artery disease

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Publisher Correction: The impact of endothermy on the climatic niche evolution and the distribution of vertebrate diversity.

In the version of this Article originally published, in Fig. 3a the first boundary was incorrectly labelled the "K/T boundary"; it should have read the "K/Pg boundary". The two equations in the main text were incorrectly omitted from the HTML. In the description of the posterior distribution of an ancestral state, the normal distribution was incorrectly described as being "assigned as prior to the node value"; it should have read "assigned as calibration to the node value". In the associated equation (the second equation in the text), the denominator of the last term was incorrectly given as "Node prior"; it should have read "Node calibration". In the same equation, the numerator of the third term on the right-hand side of the equation contained incorrect superscript notation on the x and this is shown in the full equation in the notice below.In the Acknowledgements, the following two sentences were incorrectly omitted: "The authors thank the Vital-IT facilities of the Swiss Institute of Bioinformatics for the computational support" and "This work was funded by the University of Lausanne and the Swiss National Science Foundation (CRSIII3-147630) to N.S." In the Author contributions section, the first sentence was incorrectly given as "J.R. designed the study. J.R., N.S. and D. Silvestro designed the methodology and ran the analyses"; it should have read "J.R., D.S. and N.S. designed the study and the methodology". In the Supplementary Information, all three instances of the word "prior" were incorrect and should have read "calibration".These errors have now been corrected in all versions of the Article