Evaluation of CNN architectures for gait recognition based on optical flow maps

This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Mixing body-parts model for 2D human pose estimation in stereo videos

This study targets 2D articulated human pose estimation (i.e. localisation of body limbs) in stereo videos. Although in recent years depth-based devices (e.g. Microsoft Kinect) have gained popularity, as they perform very well in controlled indoor environments (e.g. living rooms, operating theatres or gyms), they suffer clear problems in outdoor scenarios and, therefore, human pose estimation is still an interesting unsolved problem. The authors propose here a novel approach that is able to localise upper-body keypoints (i.e. shoulders, elbows, and wrists) in temporal sequences of stereo image pairs. The authors' method starts by locating and segmenting people in the image pairs by using disparity and appearance information. Then, a set of candidate body poses is computed for each view independently. Finally, temporal and stereo consistency is applied to estimate a final 2D pose. The authors' validate their model on three challenging datasets: `stereo human pose estimation dataset', `poses in the wild' and `INRIA 3DMovie'. The experimental results show that the authors' model not only establishes new state-of-the-art results on stereo sequences, but also brings improvements in monocular sequences

The AVA Multi-View Dataset for Gait Recognition

In this paper, we introduce a new multi-view dataset for gait recognition. The dataset was recorded in an indoor scenario, using six convergent cameras setup to produce multi-view videos, where each video depicts a walking human. Each sequence contains at least 3 complete gait cycles. The dataset contains videos of 20 walking persons with a large variety of body size, who walk along straight and curved paths. The multi-view videos have been processed to produce foreground silhouettes. To validate our dataset, we have extended some appearance-based 2D gait recognition methods to work with 3D data, obtaining very encouraging results. The dataset, as well as camera calibration information, is freely available for research purpose

Stereo Pictorial Structure for 2D Articulated Human Pose Estimation

In this paper, we consider the problem of 2D human pose estimation on stereo image pairs. In particular, we aim at estimating the location, orientation and scale of upper-body parts of people detected in stereo image pairs from realistic stereo videos that can be found in the Internet. To address this task, we propose a novel pictorial structure model to exploit the stereo information included in such stereo image pairs: the Stereo Pictorial Structure (SPS). To validate our proposed model, we contribute a new annotated dataset of stereo image pairs, the Stereo Human Pose Estimation Dataset (SHPED), obtained from YouTube stereoscopic video sequences, depicting people in challenging poses and diverse indoor and outdoor scenarios. The experimental results on SHPED indicates that SPS improves on state-ofthe- art monocular models thanks to the appropriate use of the stereo informatio

Synthesis and Characterization of Nanocrystalline ZnO Doped with Al3+ and Ni2+ by a Sol-Gel Method Coupled with Ultrasound Irradiation

Zinc oxide is one of the most important semiconducting metal oxides and one of the most promising n-type materials, but its practical use is limited because of both its high thermal conductivity and its low electrical conductivity. Numerous studies have shown that doping with metals in ZnO structures leads to the modification of the band gap energy. In this work, Al-doped ZnO, Ni-doped ZnO, and undoped ZnO nanocrystalline powders were prepared by a sol&-gel method coupled with ultrasound irradiation, and the results show the influence of Al3+ and Ni2+ ions in the ZnO network. The doping concentrations in ZnO of 0.99 atom % for ZnO&-Al and 0.80 atom % for ZnO&-Ni were obtained by X-ray Fluorescence (XRF). X-ray Diffraction (XRD) and Raman Spectroscopy showed a decreased intensity and broadening of main peaks, indicating metallic ions. The crystallite size of the sample was decreased from 24.5 nm (ZnO) to 22.0 nm (ZnO&-Al) and 21 nm (ZnO&-Ni). The textural and morphological properties were analyzed via Nitrogen Adsorption (BET method) and Field Emission Scanning Electron Microscopy (FESEM).The authors of this paper wish to thank Advanced Nanostructured Materials and Applications Network for its support via Secretaría de Educación Pública (SEP)

Mitigation of phytotoxic effect of compost by application of optimized aqueous extraction protocols

The abuse of chemical fertilizers in recent decades has led the promotion of less harmful alternatives, such as compost or aqueous extracts obtained from it. Therefore, it is essential to develop liquid biofertilizers, which in addition of being stable and useful for fertigation and foliar application in intensive agriculture had a remarkable phytostimulant extracts. For this purpose, a collection of aqueous extracts was obtained by applying four different Compost Extraction Protocols (CEP1, CEP2, CEP3, CEP4) in terms of incubation time, temperature and agitation of compost samples from agri-food waste, olive mill waste, sewage sludge and vegetable waste. Subsequently, a physicochemical characterization of the obtained set was performed in which pH, electrical conductivity and Total Organic Carbon (TOC) were measured. In addition, a biological characterization was also carried out by calculating the Germination Index (GI) and determining the Biological Oxygen Demand (BOD5). Furthermore, functional diversity was studied using the Biolog EcoPlates technique. The results obtained confirmed the great heterogeneity of the selected raw materials. However, it was observed that the less aggressive treatments in terms of temperature and incubation time, such as CEP1 (48 h, room temperature (RT)) or CEP4 (14 days, RT), provided aqueous compost extracts with better phytostimulant characteristics than the starting composts. It was even possible to find a compost extraction protocol that maximize the beneficial effects of compost. This was the case of CEP1, which improved the GI and reduced the phytotoxicity in most of the raw materials analyzed. Therefore, the use of this type of liquid organic amendment could mitigate the phytotoxic effect of several composts being a good alternative to the use of chemical fertilizers

Clinical Utility of Ghrelin-O-Acyltransferase (GOAT) Enzyme as a Diagnostic Tool and Potential Therapeutic Target in Prostate Cancer

Recent data suggested that plasma Ghrelin O-Acyl Transferase enzyme (GOAT) levels could represent a new diagnostic biomarker for prostate cancer (PCa). In this study, we aimed to explore the diagnostic and prognostic/aggressiveness capacity of GOAT in urine, as well as to interrogate its putative pathophysiological role in PCa. We analysed urine/plasma levels of GOAT in a cohort of 993 patients. In vitro (i.e., cell-proliferation) and in vivo (tumor-growth in a xenograft-model) approaches were performed in response to the modulation of GOAT expression/activity in PCa cells. Our results demonstrate that plasma and urine GOAT levels were significantly elevated in PCa patients compared to controls. Remarkably, GOAT significantly outperformed PSA in the diagnosis of PCa and significant PCa in patients with PSA levels ranging from 3 to 10 ng/mL (the so-called PSA grey-zone). Additionally, urine GOAT levels were associated to clinical (e.g., Gleason-score, PSA levels) and molecular (e.g., CDK2/CDK6/CDKN2A expression) aggressiveness parameters. Indeed, GOAT overexpression increased, while its silencing/blockade decreased cell-proliferation in PCa cells. Moreover, xenograft tumors derived from GOAT-overexpressing PCa (DU145) cells were significantly higher than those derived from the mock-overexpressing cells. Altogether, our results demonstrate that GOAT could be used as a diagnostic and aggressiveness marker in urine and a therapeutic target in PCa

Boundary condition model for the simulation of organic solar cells

(c) 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/http://www.sciencedirect.com/science/article/pii/S1566119917302434Organic solar cells (OSCs) are promising photovoltaic devices to convert solar energy into electrical energy. Their many advantages such as lightweight, flexibility and low manufacturing costs are intrinsic to the organic/polymeric technology. However, because the performance of OSCs is still not competitive with inorganic solar cells, there is urgent need to improve the device performance using better designs, technologies and models. In this work, we focus on the developing an accurate physics-based model that relates the charge carrier density at the metal-organic boundaries with the current density in OSCs using our previous studies on single-carrier and bipolar diodes. The model for the boundary condition of the charge carrier density at the interfaces of OSCs follows a power-law function with the current density, both in dark and under illumination, and simulated current-voltage characteristics are verified with experimental results. The numerical simulations of the current-voltage characteristics of OSCs consider well-established models for the main physical and optical processes that take place in the device: light absorption and generation of excitons, dissociation of excitons into free charge carriers, charge transport, recombination and injection-extraction of free carriers. Our analysis provides important insights on the influence of the metal-organic interfaces on the overall performance of OSCs. The model is also used to explain the anomalous S-shape current-voltage curves found in some experimental data.This work was supported by Ministerio de Educación y Ciencia under research Grant FPU12/02712 and MINECO/FEDER under research Project MAT2016-76892-C3-3-R, and the Canada Research Chair program, NSERC ResEau strategic network and the NCE IC-IMPACTS

Microscopic calculation of proton capture reactions in mass 60-80 region and its astrophysical implications

Microscopic optical potentials obtained by folding the DDM3Y interaction with the densities from Relativistic Mean Field approach have been utilized to evaluate S-factors of low-energy $(p,\gamma)$ reactions in mass 60-80 region and to compare with experiments. The Lagrangian density FSU Gold has been employed. Astrophysical rates for important proton capture reactions have been calculated to study the behaviour of rapid proton nucleosynthesis for waiting point nuclei with mass less than A=80