966 resultados para PSYCHIATRY, SCI


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In this work, we propose an algorithm for optical flow estimation using Approximate Nearest Neighbor Fields (ANNF). Proposed optical flow estimation algorithm consists of two steps, flow initialization using ANNF maps and cost filtering. Flow initialization is done by computing the ANNF map using FeatureMatch between two consecutive frames. The ANNF map obtained represents a noisy optical flow, which is refined by making use of superpixels. The best flow associated with each superpixel is computed by optimizing a cost function. The proposed approach is evaluated on Middlebury and MPI-Sintel optical flow dataset and is found to be comparable with the state of the art methods for optical flow estimation.

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In this work, we have explored the prospect of segmenting crowd flow in H. 264 compressed videos by merely using motion vectors. The motion vectors are extracted by partially decoding the corresponding video sequence in the H. 264 compressed domain. The region of interest ie., crowd flow region is extracted and the motion vectors that spans the region of interest is preprocessed and a collective representation of the motion vectors for the entire video is obtained. The obtained motion vectors for the corresponding video is then clustered by using EM algorithm. Finally, the clusters which converges to a single flow are merged together based on the bhattacharya distance measure between the histogram of the of the orientation of the motion vectors at the boundaries of the clusters. We had implemented our proposed approach on the complex crowd flow dataset provided by 1] and compared our results by using Jaccard measure. Since we are performing crowd flow segmentation in the compressed domain using only motion vectors, our proposed approach performs much faster compared to other pixel domain counterparts still retaining better accuracy.

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This paper presents our work on developing an automated micro positioner and a low cost disposable dispenser module having a disposable dispenser core. The dispenser core is made up of Polydimethylsiloxane (PDMS). Once the user specifies the dispensing location in the Graphical User Interface (GUI), the movement of the micropositioner is automatic. The design, fabrication and characterization results of the dispenser module are also presented. The dispensing experiments are performed with Di-Ethanol Amine as the working reagent. The minimum dispensed volume achieved is about 4 nL.

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Representing images and videos in the form of compact codes has emerged as an important research interest in the vision community, in the context of web scale image/video search. Recently proposed Vector of Locally Aggregated Descriptors (VLAD), has been shown to outperform the existing retrieval techniques, while giving a desired compact representation. VLAD aggregates the local features of an image in the feature space. In this paper, we propose to represent the local features extracted from an image, as sparse codes over an over-complete dictionary, which is obtained by K-SVD based dictionary training algorithm. The proposed VLAD aggregates the residuals in the space of these sparse codes, to obtain a compact representation for the image. Experiments are performed over the `Holidays' database using SIFT features. The performance of the proposed method is compared with the original VLAD. The 4% increment in the mean average precision (mAP) indicates the better retrieval performance of the proposed sparse coding based VLAD.

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Ag doped BaTiO3-CuO mixed oxide thin films are evaluated for their carbon-dioxide sensing characteristics. The metal oxide films of different thicknesses are deposited on oxidized p type Si < 100 > substrate by RF Sputtering. Sensing characteristics for different CO2 concentration, (300 ppm - 1000 ppm) are obtained for different operating temperatures, (100 degrees C - 400 degrees C). Optimum temperature for maximum sensitivity is found to be 250 degrees C. The effect of annealing on sensing properties is also evaluated. The unannealed films give better sensitivity than that of annealed films. Response time and recovery time are also calculated.

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Storage of water within a river basin is often estimated by analyzing recession flow curves as it cannot be `instantly' estimated with the aid of available technologies. In this study we explicitly deal with the issue of estimation of `drainable' storage, which is equal to the area under the `complete' recession flow curve (i.e. a discharge vs. time curve where discharge continuously decreases till it approaches zero). But a major challenge in this regard is that recession curves are rarely `complete' due to short inter-storm time intervals. Therefore, it is essential to analyze and model recession flows meaningfully. We adopt the wellknown Brutsaert and Nieber analytical method that expresses time derivative of discharge (dQ/dt) as a power law function of Q : -dQ/dt = kQ(alpha). However, the problem with dQ/dt-Q analysis is that it is not suitable for late recession flows. Traditional studies often compute alpha considering early recession flows and assume that its value is constant for the whole recession event. But this approach gives unrealistic results when alpha >= 2, a common case. We address this issue here by using the recently proposed geomorphological recession flow model (GRFM) that exploits the dynamics of active drainage networks. According to the model, alpha is close to 2 for early recession flows and 0 for late recession flows. We then derive a simple expression for drainable storage in terms the power law coefficient k, obtained by considering early recession flows only, and basin area. Using 121 complete recession curves from 27 USGS basins we show that predicted drainable storage matches well with observed drainable storage, indicating that the model can also reliably estimate drainable storage for `incomplete' recession events to address many challenges related to water resources. (C) 2014 Elsevier Ltd. All rights reserved.

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Manganese dioxide nanoparticles were synthesized by chemical reduction route at different growth temperatures of 40 degrees C, 80 degrees C, 100 degrees C and were characterized using X-ray Diffraction (XRD), Field emission scanning electron microscopy (FESEM), X-ray photoelectron spectroscopy (XPS), Cyclic Voltammetry (CV) and chronoamperometry (CA) analysis. FESEM results show that on increasing growth temperature the morphology changes from clusters into mixture of rods and flakes. XPS analysis reveals the formation of MnO2. Then these particles were immobilized on Pt electrode. A platinum (Pt) electrode modified with low dimensional MnO2 was investigated as a chronoamperometric (CA) sensor for hydrogen peroxide sensing (H2O2). The sample prepared at 100 degrees C shows good electrocatalytic ability for H2O2 sensing when compared with the samples prepared at 40 degrees C and 80 degrees C. At an operating potential of 0.3 V vs. Ag/AgCl catalytic oxidation of the analyte is measured for chronoamperometric (CA) monitoring. The CA signals are linearly proportional to the concentration of H2O2. It is also found that the morphology of the nanostructure plays a vital role in the detection of H2O2. (C) 2014 Elsevier Ltd. All rights reserved.

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A protease inhibitor from the seeds of Butea monosperma (BmPI) was purified, characterized and studied for its influence on developmental physiology of Helicover-pa armigera. BmPI on two-dimensional separations indicated the presence of a 14 kDa protein with an isoelectric point in the acidic region (pl 5.6). Multiple Sequence Analysis data suggested that the BmPI contains a sequence motif which is conserved in various trypsin and chymotrypsin inhibitors of Kunitz-type. The inhibitor exhibited trypsin inhibitory activity in a broad range of pH (4-10) and temperature (10-80 degrees C). The enzyme kinetic studies revealed BmPI as a competitive inhibitor with a K-i value of 1.2 x 10(-9) M. In vitro studies with BmPI indicated measurable inhibitory activity on total gut proteolytic enzymes of H. armigera (IC(50)2.0 mu g/ml) and bovine trypsin. BmPI supplemented artificial diet caused dose dependent mortality and reduction in growth and weight. The fertility and fecundity of H. armigera, declined whereas the larval-pupal duration of the insect life cycle extended. These detrimental effects on H. armigera suggest the usefulness of BmPl in insect pest management of food crops. (C) 2014 Elsevier Ltd. All rights reserved.

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In the present study, amino-silane modified layered organosilicates were used to reinforce cyclic olefin copolymer to enhance the thermal, mechanical and moisture impermeable barrier properties. The optimum clay loading (4%) in the nanocomposite increases the thermal stability of the film while further loading decreases film stability. Water absorption behavior at 62 degrees C was carried out and compared with the behavior at room temperature and 48 degrees C. The stiffness of the matrix increases with clay content and the recorded strain to failure for the composite films was lower than the neat film. Dynamic mechanical analysis show higher storage modulus and low loss modulus for 2.5-4 wt% clay loading. Calcium degradation test and device encapsulation also show the evidence of optimum clay loading of 4 wt% for improved low water vapor transmission rates compared to other nanocomposite films. (C) 2014 Elsevier Ltd. All rights reserved.

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Transcriptional regulation enables adaptation in bacteria. Typically, only a few transcriptional events are well understood, leaving many others unidentified. The recent genome-wide identification of transcription factor binding sites in Mycobacterium tuberculosis has changed this by deciphering a molecular road-map of transcriptional control, indicating active events and their immediate downstream effects.

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India needs to significantly increase its electricity consumption levels, in a sustainable manner, if it has to ensure rapid economic development, a goal that remains the most potent tool for delivering adaptation capacity to its poor who will suffer the worst consequences of climate change. Resource/supply constraints faced by conventional energy sources, techno-economic constraints faced by renewable energy sources, and the bounds imposed by climate change on fossil fuel use are likely to undermine India's quest for having a robust electricity system that can effectively contribute to achieving accelerated, sustainable and inclusive economic growth. One possible way out could be transitioning into a sustainable electricity system, which is a trade-off solution having taken into account the economic, social and environmental concerns. As a first step toward understanding this transition, we contribute an indicator based hierarchical multidimensional framework as an analytical tool for sustainability assessment of electricity systems, and validate it for India's national electricity system. We evaluate Indian electricity system using this framework by comparing it with a hypothetical benchmark sustainable electrical system, which was created using best indicator values realized across national electricity systems in the world. This framework, we believe, can be used to examine the social, economic and environmental implications of the current Indian electricity system as well as setting targets for future development. The analysis with the indicator framework provides a deeper understanding of the system, identify and quantify the prevailing sustainability gaps and generate specific targets for interventions. We use this framework to compute national electricity system sustainability index (NESSI) for India. (C) 2014 Elsevier Ltd. All rights reserved.

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The isometric fluctuation relation (IFR) P. I. Hurtado et al., Proc. Natl. Acad. Sci. USA 108, 7704 (2011)] relates the relative probability of current fluctuations of fixed magnitude in different spatial directions. We test its validity in an experiment on a tapered rod, rendered motile by vertical vibration and immersed in a sea of spherical beads. We analyze the statistics of the velocity vector of the rod and show that they depart significantly from the IFR of Hurtado et al. Aided by a Langevin-equation model we show that our measurements are largely described by an anisotropic generalization of the IFR R. Villavicencio et al., Europhys. Lett. 105, 30009 (2014)], with no fitting parameters, but with a discrepancy in the prefactor whose origin may lie in the detailed statistics of the microscopic noise. The experimentally determined large-deviation function of the velocity vector has a kink on a curve in the plane.

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Oocytes present at birth undergo a progressive process of apoptosis in humans and other mammals as they age. Accepted opinion is that no fresh oocytes are produced other than those present at the time of birth. Studies have shown that DNA repair genes in oocytes of mice and women decline with age, and lack of these genes show higher DNA breaks and increased oocyte death rates. In contrast to the ethical problems associated with monitoring the changes in DNA double-strand breaks in oocytes from young and old humans, it is relatively easy to carry out such a study using a rodent model. In this study, the mRNA levels of DNA repair genes are compared with protein products of some of the genes in the primordial follicles isolated from immature (18-20 days) and aged (400-450 days) female rats. Results revealed a significant decline in mRNA levels of BRAC1 (P < 0.01), RAD51 (P < 0.05), ERCC2 (P < 0.05), and H2AX (P < 0.01) of DNA repair genes and phospho-protein levels of BRAC1 (P < 0.01) and H2AX (P < 0.05) in primordial follicles of aged rats. Impaired DNA repair is confirmed as a mechanism of oocyte ageing. (C) 2014 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

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Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty. (C) 2015 Elsevier Ltd. All rights reserved.