897 resultados para Mesh generation from image data


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We propose the use of a polarization based interferometer with variable transfer function for the generation of temporally flat top pulses from gain switched single mode semiconductor lasers. The main advantage of the presented technique is its flexibility in terms of input pulse characteristics, as pulse duration, spectral bandwidth and operating wavelength. Theoretical predictions and experimental demonstrations are presented and the proposed technique is applied to two different semiconductor laser sources emitting in the 1550 nm region. Flat top pulses are successfully obtained with input seed pulses with duration ranging from 40 ps to 100 ps.

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In the past decades, online learning has transformed the educational landscape with the emergence of new ways to learn. This fact, together with recent changes in educational policy in Europe aiming to facilitate the incorporation of graduate students to the labor market, has provoked a shift on the delivery of instruction and on the role played by teachers and students, stressing the need for development of both basic and cross-curricular competencies. In parallel, the last years have witnessed the emergence of new educational disciplines that can take advantage of the information retrieved by technology-based online education in order to improve instruction, such as learning analytics. This study explores the applicability of learning analytics for prediction of development of two cross-curricular competencies – teamwork and commitment – based on the analysis of Moodle interaction data logs in a Master’s Degree program at Universidad a Distancia de Madrid (UDIMA) where the students were education professionals. The results from the study question the suitability of a general interaction-based approach and show no relation between online activity indicators and teamwork and commitment acquisition. The discussion of results includes multiple recommendations for further research on this topic.

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Funded by COST (European Cooperation in Science and Technology) CEH projects. Grant Numbers: NEC05264, NEC05100 Natural Environment Research Council UK. Grant Number: NE/J008001/1 © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Although nitric oxide synthase (NOS) is widely considered as the major source of NO in biological cells and tissues, direct evidence demonstrating NO formation from the purified enzyme has been lacking. It was recently reported that NOS does not synthesize NO, but rather generates nitroxyl anion (NO−) that is subsequently converted to NO by superoxide dismutase (SOD). To determine if NOS synthesizes NO, electron paramagnetic resonance (EPR) spectroscopy was applied to directly measure NO formation from purified neuronal NOS. In the presence of the NO trap Fe2+-N-methyl-d-glucamine dithiocarbamate, NO gives rise to characteristic EPR signals with g = 2.04 and aN = 12.7 G, whereas NO− is undetectable. In the presence of l-arginine (l-Arg) and cofactors, NOS generated prominent NO signals. This NO generation did not require SOD, and it was blocked by the specific NOS inhibitor N-nitro-l-arginine methyl ester. Isotope-labeling experiments with l-[15N]Arg further demonstrated that NOS-catalyzed NO arose from the guanidino nitrogen of l-Arg. Measurement of the time course of NO formation demonstrated that it paralleled that of l-citrulline. The conditions used in the prior study were shown to result in potent superoxide generation, and this may explain the failure to measure NO formation in the absence of SOD. These experiments provide unequivocal evidence that NOS does directly synthesize NO from l-Arg.

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Objectives To explore how general practitioners have accessed and evaluated evidence from trials on the use of statin lipid lowering drugs and incorporated this evidence into their practice. To draw out the practical implications of this study for strategies to integrate clinical evidence into general medical practice.

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Controversy still exists over the adaptive nature of variation of enzyme loci. In conifers, random amplified polymorphic DNAs (RAPDs) represent a class of marker loci that is unlikely to fall within or be strongly linked to coding DNA. We have compared the genetic diversity in natural populations of black spruce [Picea mariana (Mill.) B.S.P.] using genotypic data at allozyme loci and RAPD loci as well as phenotypic data from inferred RAPD fingerprints. The genotypic data for both allozymes and RAPDs were obtained from at least six haploid megagametophytes for each of 75 sexually mature individuals distributed in five populations. Heterozygosities and population fixation indices were in complete agreement between allozyme loci and RAPD loci. In black spruce, it is more likely that the similar levels of variation detected at both enzyme and RAPD loci are due to such evolutionary forces as migration and the mating system, rather than to balancing selection and overdominance. Furthermore, we show that biased estimates of expected heterozygosity and among-population differentiation are obtained when using allele frequencies derived from dominant RAPD phenotypes.

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Time-variable gravity data from the Gravity Recovery And Climate Experiment (GRACE) mission are used to study total water content over Australia for the period 2002–2010. A time-varying annual signal explains 61% of the variance of the data, in good agreement with two independent estimates of the same quantity from hydrological models. Water mass content variations across Australia are linked to Pacific and Indian Ocean variability, associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), respectively. From 1989, positive (negative) IOD phases were related to anomalously low (high) precipitation in southeastern Australia, associated with a reduced (enhanced) tropical moisture flux. In particular, the sustained water mass content reduction over central and southern regions of Australia during the period 2006–2008 is associated with three consecutive positive IOD events.

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3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

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A new methodology is proposed to produce subsidence activity maps based on the geostatistical analysis of persistent scatterer interferometry (PSI) data. PSI displacement measurements are interpolated based on conditional Sequential Gaussian Simulation (SGS) to calculate multiple equiprobable realizations of subsidence. The result from this process is a series of interpolated subsidence values, with an estimation of the spatial variability and a confidence level on the interpolation. These maps complement the PSI displacement map, improving the identification of wide subsiding areas at a regional scale. At a local scale, they can be used to identify buildings susceptible to suffer subsidence related damages. In order to do so, it is necessary to calculate the maximum differential settlement and the maximum angular distortion for each building of the study area. Based on PSI-derived parameters those buildings in which the serviceability limit state has been exceeded, and where in situ forensic analysis should be made, can be automatically identified. This methodology has been tested in the city of Orihuela (SE Spain) for the study of historical buildings damaged during the last two decades by subsidence due to aquifer overexploitation. The qualitative evaluation of the results from the methodology carried out in buildings where damages have been reported shows a success rate of 100%.

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The classical problem of agricultural productivity measurement has regained interest owing to recent price hikes in world food markets. At the same time, there is a new methodological debate on the appropriate identification strategies for addressing endogeneity and collinearity problems in production function estimation. We examine the plausibility of four established and innovative identification strategies for the case of agriculture and test a set of related estimators using farm-level panel datasets from seven EU countries. The newly suggested control function and dynamic panel approaches provide attractive conceptual improvements over the received ‘within’ and duality models. Even so, empirical implementation of the conceptual sophistications built into these estimators does not always live up to expectations. This is particularly true for the dynamic panel estimator, which mostly failed to identify reasonable elasticities for the (quasi-) fixed factors. Less demanding proxy approaches represent an interesting alternative for agricultural applications. In our EU sample, we find very low shadow prices for labour, land and fixed capital across countries. The production elasticity of materials is high, so improving the availability of working capital is the most promising way to increase agricultural productivity.

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The present data set includes 268,127 vertical in situ fluorescence profiles obtained from several available online databases and from published and unpublished individual sources. Metadata about each profiles are given in the file provided here in further details. The majority of profiles comes from the National Oceanographic Data Center (NODC) and the fluorescence profiles acquired by Bio-Argo floats available on the Oceanographic Autonomous Observations (OAO) platform (63.7% and 12.5% respectively). Different modes of acquisition were used to collect the data presented in this study: (1) CTD profiles are acquired using a fluorometer mounted on a CTD-rosette; (2) OSD (Ocean Station Data) profiles are derived from water samples and are defined as low resolution profiles; (3) the UOR (Undulating Oceanographic Recorder) profiles are acquired by a equipped with a fluorometer and towed by a research vessel; (4) PA profiles are acquired by autonomous platforms (here profiling floats or elephant seals equipped with a fluorometer). Data acquired from gliders are not included in the compilation.