Mover – Activity Monitor and Fall Detector for Android

Mover is an exciting application that allows you to track your activity level and helps you become more active. Mover includes also an experimental fall detection system

Processing and classification of biological images: Application to histology

This article deals with a histological problem by using image processing and feature extraction in images of renal tissues of rats and their classification through various methods such as: Bayesian inference, decision trees and support vector machines

Canine parvovirus : a predicting canine model for sepsis

Research Areas: Veterinary SciencesBackground: Sepsis is a severe condition associated with high prevalence and mortality rates. Parvovirus enteritis is a predisposing factor for sepsis, as it promotes intestinal bacterial translocation and severe immunosuppression. This makes dogs infected by parvovirus a suitable study population as far as sepsis is concerned. The main objective of the present study was to evaluate the differences between two sets of SIRS (Systemic Inflammatory Response Syndrome) criteria in outcome prediction: SIRS 1991 and SIRS 2001. The possibility of stratifying and classifying septic dogs was assessed using a proposed animal adapted PIRO (Predisposition, Infection, Response and Organ dysfunction) scoring system. Results: The 72 dogs enrolled in this study were scored for each of the PIRO elements, except for Infection, as all were considered to have the same infection score, and subjected to two sets of SIRS criteria, in order to measure their correlation with the outcome. Concerning SIRS criteria, it was found that the proposed alterations on SIRS 2001 (capillary refill time or mucous membrane colour alteration) were significantly associated with the outcome (OR = 4.09, p < 0.05), contrasting with the 1991 SIRS criteria (p = 0.352) that did not correlate with the outcome. No significant statistical association was found between Predisposition (p = 1), Response (p = 0.1135), Organ dysfunction (p = 0.1135), total PIRO score (p = 0.093) and outcome. To explore the possibility of using the SIRS criteria as a fast decision-making tool, a Fast-andFrugal tree (FFT) was created with a sensitivity of 92% and a specificity of 29%. Conclusion: These results suggest that increasing the SIRS criteria specificity may improve their prognostic value and their clinical usefulness. In order to improve the proposed PIRO scoring system outcome prediction ability, more specific criteria should be added, mainly inflammatory and organ dysfunction biomarkers.info:eu-repo/semantics/publishedVersio

Agronomic performance of interspecific Paspalum hybrids under nitrogen fertilization or mixed with legumes

Nitrogen supply and mixtures with legumes affect agronomic performance of pas- tures, and both practices can guide breeding decisions in Paspalum hybrids. The goals of this study were: (a) quantify herbage accumulation (HA), leaf accumulation (LA), cold tolerance, and N use efficiency (NUE) in P. plicatulum × P. guenoarum hybrids subjected to N fertilization or grown in a mixture with legumes; (b) compare the grass–legume system to a grass–N fertilizer system; and (c) select the best hybrid for future cultivar releases. A randomized complete block design with three repli- cations and a split-plot treatment arrangement was used for 2 yr, with five N rates (0, 60, 120, 240, and 480 kg N ha−1) and a grass–legume mixture [grass + white clover (Trifolium repens L.) + birdsfoot trefoil (Lotus corniculatus L.)] as whole plots, and six genotypes as subplots (hybrids: 1020133, 102069, 103084, 103061; and controls: P. guenoarum ‘Azulão’ and Megathyrsus maximus ‘Aruana’). Higher N rates increased HA, LA, and cold tolerance. Higher NUE was obtained between 60 and 120 kg N ha−1. In the grass–legume mixture HA was similar to the rates of 60 and 120 kg N ha−1. Hybrid 1020133 had HA similar to the controls, LA greater than Aruana, and greater cold tolerance and NUE at 60 kg N ha−1 than Azulão and Aruana. Hybrid 1020133 should be selected for further animal performance stud- ies. The agronomic performance of perennial pastures can be improved through N management, and NUE should be a selection criterion in forage breeding

Stone-stacking as a looming threat to rock-dwelling biodiversity

Non peer reviewe

Multidimensional scaling for the evaluation of a geostatistical seismic elastic inversion methodology

Due to the nature of seismic inversion problems, there are multiple possible solutions that can equally fit the observed seismic data while diverging from the real subsurface model. Consequently, it is important to assess how inverse-impedance models are converging toward the real subsurface model. For this purpose, we evaluated a new methodology to combine the multidimensional scaling (MDS) technique with an iterative geostatistical elastic seismic inversion algorithm. The geostatistical inversion algorithm inverted partial angle stacks directly for acoustic and elastic impedance (AI and EI) models. It was based on a genetic algorithm in which the model perturbation at each iteration was performed recurring to stochastic sequential simulation. To assess the reliability and convergence of the inverted models at each step, the simulated models can be projected in a metric space computed by MDS. This projection allowed distinguishing similar from variable models and assessing the convergence of inverted models toward the real impedance ones. The geostatistical inversion results of a synthetic data set, in which the real AI and EI models are known, were plotted in this metric space along with the known impedance models. We applied the same principle to a real data set using a cross-validation technique. These examples revealed that the MDS is a valuable tool to evaluate the convergence of the inverse methodology and the impedance model variability among each iteration of the inversion process. Particularly for the geostatistical inversion algorithm we evaluated, it retrieves reliable impedance models while still producing a set of simulated models with considerable variability

Geographical variation of prementum size in Iberian Cordulegaster boltonii (Odonata: Cordulegastridae) populations

Within wide geographical areas, Odonata populations can show biometric differences as a consequence of both biotic (e.g., predation, competition) and abiotic factors (mainly temperature). These differences can occur in the larval stage, although reliable characters are needed to detect differences. We analyzed whether Cordulegaster boltonii larvae from 18 Iberian populations differ regarding head width and prementum size (maximum width, minimum width, and maximum length), using measurements taken on final stage exuviae. Prementum length was greater in southern populations than in northern ones. Geographic latitude and temperature were the variables that best explained this variation in females, whereas latitude and altitude above sea level offered the best explanation among males