Assembling and Verification of a Fitness Test Battery for the Recruitment of the Swiss Army and Nation-Wide Use

The aim of this study was to assess the reliability, validity and feasibility of selected physical performance tests, to compile a new fi tness test battery based on these results and to obtain standard values for young men. 79 men (20.3 ± 1.1 y) performed the tests for the reliability part, while 60 men (20.3 ± 1.1 y) completed the tests for the validity part of the study. Feasibility was confi rmed by 25 sport experts who conducted the test battery among 1704 men (19.5 ± 1.0 y). For standard values, the data of 12 862 men (19.9 ± 1.0 y) were collected. Based on the reliability and validity data, the following 5 tests were selected for the fi tness-test battery: 1) progressive endurance run, 2) seated 2-kg-shot put, 3) standing long jump, 4) trunk muscle strength test and 5) 1-leg standing test. The reliability and validity of the selected performance tests were suffi cient to very good (r = 0.50–0.90 and r = 0.64–0.91, respectively). The suggested fi tness-test battery can be applied among large groups

Handwriting word recognition using windowed Bernoulli HMMs

[EN] Hidden Markov Models (HMMs) are now widely used for off-line handwriting recognition in many lan- guages. As in speech recognition, they are usually built from shared, embedded HMMs at symbol level, where state-conditional probability density functions in each HMM are modeled with Gaussian mixtures. In contrast to speech recognition, however, it is unclear which kind of features should be used and, indeed, very different features sets are in use today. Among them, we have recently proposed to directly use columns of raw, binary image pixels, which are directly fed into embedded Bernoulli (mixture) HMMs, that is, embedded HMMs in which the emission probabilities are modeled with Bernoulli mix- tures. The idea is to by-pass feature extraction and to ensure that no discriminative information is filtered out during feature extraction, which in some sense is integrated into the recognition model. In this work, column bit vectors are extended by means of a sliding window of adequate width to better capture image context at each horizontal position of the word image. Using these windowed Bernoulli mixture HMMs, good results are reported on the well-known IAM and RIMES databases of Latin script, and in particular, state-of-the-art results are provided on the IfN/ENIT database of Arabic handwritten words.Giménez Pastor, A.; Alkhoury, I.; Andrés Ferrer, J.; Juan Císcar, A. (2014). Handwriting word recognition using windowed Bernoulli HMMs. Pattern Recognition Letters. 35:149-156. doi:10.1016/j.patrec.2012.09.002S1491563

Are owl pellets good estimators of prey abundance?

Some ecologists have been skeptics about the use of owl pellets to estimate small mammal's fauna. This is due to the assumptions required by this method: (a) that owls hunt at random, and (b) that pellets represent a random sample from the environment. We performed statistical analysis to test these assumptions and to assess the effectiveness of Barn owl pellets as a useful estimator of field abundances of its preys. We used samples collected in the arid Extra-Andean Patagonia along an altitudinal environmental gradient from lower Monte ecoregion to upper Patagonian steppe ecoregion, with a mid-elevation ecotone. To test if owls hunt at random, we estimated expected pellet frequency by creating a distribution of random pellets, which we compared with data using a simulated chi-square. To test if pellets represent a random sample from the environment, differences between ecoregions were evaluated by PERMANOVAs with Bray–Curtis dissimilarities. We did not find evidence that owls foraged non-randomly. Therefore, we can assume that the proportions of the small mammal's species in the diet are representative of the proportions of the species in their communities. Only Monte is different from other ecoregions. The ecotone samples are grouped with those of Patagonian steppes. There are no real differences between localities in the small mammal's abundances in each of these ecoregions and/or Barn owl pellets cannot detect patterns at a smaller spatial scale. Therefore, we have no evidence to invalidate the use of owl pellets at an ecoregional scale.Fil: Andrade, Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; ArgentinaFil: Menezes, Jorge Fernando Saraiva de. Universidade Federal do Rio de Janeiro; BrasilFil: Monjeau, Jorge Adrian. Universidade Federal do Rio de Janeiro; Brasil. Fundación Bariloche; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Handwriting recognition by using deep learning to extract meaningful features

[EN] Recent improvements in deep learning techniques show that deep models can extract more meaningful data directly from raw signals than conventional parametrization techniques, making it possible to avoid specific feature extraction in the area of pattern recognition, especially for Computer Vision or Speech tasks. In this work, we directly use raw text line images by feeding them to Convolutional Neural Networks and deep Multilayer Perceptrons for feature extraction in a Handwriting Recognition system. The proposed recognition system, based on Hidden Markov Models that are hybridized with Neural Networks, has been tested with the IAM Database, achieving a considerable improvement.Work partially supported by the Spanish MINECO and FEDER founds under project TIN2017-85854-C4-2-R.Pastor Pellicer, J.; Castro-Bleda, MJ.; España Boquera, S.; Zamora-Martinez, FJ. (2019). Handwriting recognition by using deep learning to extract meaningful features. 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Relativistic Hydrodynamics for Heavy--Ion Collisions -- I. General Aspects and Expansion into Vacuum

We present algorithms to solve relativistic hydrodynamics in 3+1--dimensional situations without apparent symmetry to simplify the solution. In simulations of heavy--ion collisions, these numerical schemes have to deal with the physical vacuum and with equations of state with a first order phase transition between hadron matter and a quark--gluon plasma. We investigate their performance for the one--dimensional expansion of baryon-free nuclear matter into the vacuum, which is an analytically solvable test problem that incorporates both the aspect of the vacuum as well as that of a phase transition in the equation of state. The dependence of the lifetime of the mixed phase on the initial energy density is discussed.Comment: 31 pages, 16 uuencoded figure

Artificial Intelligence, Machine Learning and Modeling for Understanding the Oceans and Climate Change

International audienceThe ongoing transformation of climate and biodiversity will have a drastic impact on almost all forms of life in the ocean with further consequences on food security, ecosystem services in coastal and inland communities. Despite these impacts, scientific data and infrastructures are still lacking to understand and quantify the consequences of these perturbations on the marine ecosystem. Understanding this phenomenon is not only an urgent but also a scientifically demanding task. Consequently, it is a problem that must be addressed with a tific cohort approach, where multi-disciplinary teams collaborate to bring the best of different scientific areas. In this proposal paper, we describe our newly launched four-years project focusedon developing new artificial intelligence, machine learning, and mathematical modeling tools to contribute to the understanding of the structure, functioning, and underlying mechanisms and dynamics of the global ocean symbiome and its relation with climate change. These actions should enable the understanding of our oceans and predict and mitigate the consequences of climate and biodiversity changes

Risk reduction through community-based monitoring:the vigías of Tungurahua, Ecuador

Since 2000, a network of volunteers known as vigías has been engaged in community-based volcano monitoring, which involves local citizens in the collection of scientific data, around volcán Tungurahua, Ecuador. This paper provides the first detailed description and analysis of this well-established initiative, drawing implications for volcanic risk reduction elsewhere. Based on 32 semi-structured interviews and other qualitative data collected in June and July 2013 with institutional actors and with vigías themselves, the paper documents the origins and development of the network, identifies factors that have sustained it, and analyses the ways in which it contributes to disaster risk reduction. Importantly, the case highlights how this community-based network performs multiple functions in reducing volcanic risk. The vigías network functions simultaneously as a source of observational data for scientists; as a communication channel for increasing community awareness, understanding of hazard processes and for enhancing preparedness; and as an early warning system for civil protection. Less tangible benefits with nonetheless material consequences include enhanced social capital – through the relationships and capabilities that are fostered – and improved trust between partners. Establishing trust-based relationships between citizens, the vigías, scientists and civil protection authorities is one important factor in the effectiveness and resilience of the network. Other factors discussed in the paper that have contributed to the longevity of the network include the motivations of the vigías, a clear and regular communication protocol, persistent volcanic activity, the efforts of key individuals, and examples of successful risk reduction attributable to the activities of the network. Lessons that can be learned about the potential of community-based monitoring for disaster risk reduction in other contexts are identified, including what the case tells us about the conditions that can affect the effectiveness of such initiatives and their resilience to changing circumstances

H-NS plays a role in expression of Acinetobacter baumannii virulence features

Acinetobacter baumannii has become a major problem in the clinical setting with the prevalence of infections caused by multidrug-resistant strains on the increase. Nevertheless, only a limited number of molecular mechanisms involved in the success of A. baumannii as a human pathogen have been described. In this study, we examined the virulence features of a hypermotile derivative of A. baumannii strain ATCC 17978, which was found to display enhanced adherence to human pneumocytes and elevated levels of lethality toward Caenorhabditis elegans nematodes. Analysis of cellular lipids revealed modifications to the fatty acid composition, providing a possible explanation for the observed changes in hydrophobicity and subsequent alteration in adherence and motility. Comparison of the genome sequences of the hypermotile variant and parental strain revealed that an insertion sequence had disrupted an hns-like gene in the variant. This gene encodes a homologue of the histone-like nucleoid structuring (H-NS) protein, a known global transcriptional repressor. Transcriptome analysis identified the global effects of this mutation on gene expression, with major changes seen in the autotransporter Ata, a type VI secretion system, and a type I pilus cluster. Interestingly, isolation and analysis of a second independent hypermotile ATCC 17978 variant revealed a mutation to a residue within the DNA binding region of H-NS. Taken together, these mutants indicate that the phenotypic and transcriptomic differences seen are due to loss of regulatory control effected by H-NS.This work was supported by project grant 535053 to M.H.B. and I.T.P. from the National Health and Medical Research Council, Australia. B.A.E. is the recipient of a School of Biological Sciences Endeavor International Postgraduate Research Scholarship, and K.A.H. is supported by an APD fellowship from the Australian Research Council (DP110102680)

Search for squarks and gluinos in events with isolated leptons, jets and missing transverse momentum at s√=8 TeV with the ATLAS detector

The results of a search for supersymmetry in final states containing at least one isolated lepton (electron or muon), jets and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. The search is based on proton-proton collision data at a centre-of-mass energy s√=8 TeV collected in 2012, corresponding to an integrated luminosity of 20 fb−1. No significant excess above the Standard Model expectation is observed. Limits are set on supersymmetric particle masses for various supersymmetric models. Depending on the model, the search excludes gluino masses up to 1.32 TeV and squark masses up to 840 GeV. Limits are also set on the parameters of a minimal universal extra dimension model, excluding a compactification radius of 1/R c = 950 GeV for a cut-off scale times radius (ΛR c) of approximately 30