Estrategias utilizadas por estudiantes de distintos niveles educativos ante problemas de proporcionalidad compuesta

En este trabajo se analizan las actuaciones de alumnos desde 6.º de Educación Primaria hasta 2.º de Educación Secundaria Obligatoria (11-14 años) con distintos grados de instrucción en proporcionalidad al resolver ciertos problemas de proporcionalidad compuesta. En particular, observamos la tasa de éxito y las distintas estrategias empleadas, tanto correctas como incorrectas. Los resultados muestran un aumento progresivo de la tasa de éxito y una evolución en las estrategias utilizadas desde aquellas que hacen referencia a aspectos de razonamiento proporcional, hacia aquellas en las que prima el componente algorítmico

Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis

3D reconstruction of medical images from slices automatically landmarked with growing neural models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid

Evaluation of different chrominance models in the detection and reconstruction of faces and hands using the growing neural gas network

Physical traits such as the shape of the hand and face can be used for human recognition and identification in video surveillance systems and in biometric authentication smart card systems, as well as in personal health care. However, the accuracy of such systems suffers from illumination changes, unpredictability, and variability in appearance (e.g. occluded faces or hands, cluttered backgrounds, etc.). This work evaluates different statistical and chrominance models in different environments with increasingly cluttered backgrounds where changes in lighting are common and with no occlusions applied, in order to get a reliable neural network reconstruction of faces and hands, without taking into account the structural and temporal kinematics of the hands. First a statistical model is used for skin colour segmentation to roughly locate hands and faces. Then a neural network is used to reconstruct in 3D the hands and faces. For the filtering and the reconstruction we have used the growing neural gas algorithm which can preserve the topology of an object without restarting the learning process. Experiments conducted on our own database but also on four benchmark databases (Stirling’s, Alicante, Essex, and Stegmann’s) and on deaf individuals from normal 2D videos are freely available on the BSL signbank dataset. Results demonstrate the validity of our system to solve problems of face and hand segmentation and reconstruction under different environmental conditions

Fast 2D/3D object representation with growing neural gas

This work presents the design of a real-time system to model visual objects with the use of self-organising networks. The architecture of the system addresses multiple computer vision tasks such as image segmentation, optimal parameter estimation and object representation. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and faces, and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product. The proposed method is easily extensible to 3D objects, as it offers similar features for efficient mesh reconstruction

Immunization expands B cells specific to HIV-1 V3 glycan in mice and macaques.

Broadly neutralizing monoclonal antibodies protect against infection with HIV-1 in animal models, suggesting that a vaccine that elicits these antibodies would be protective in humans. However, it has not yet been possible to induce adequate serological responses by vaccination. Here, to activate B cells that express precursors of broadly neutralizing antibodies within polyclonal repertoires, we developed an immunogen, RC1, that facilitates the recognition of the variable loop 3 (V3)-glycan patch on the envelope protein of HIV-1. RC1 conceals non-conserved immunodominant regions by the addition of glycans and/or multimerization on virus-like particles. Immunization of mice, rabbits and rhesus macaques with RC1 elicited serological responses that targeted the V3-glycan patch. Antibody cloning and cryo-electron microscopy structures of antibody-envelope complexes confirmed that immunization with RC1 expands clones of B cells that carry the anti-V3-glycan patch antibodies, which resemble precursors of human broadly neutralizing antibodies. Thus, RC1 may be a suitable priming immunogen for sequential vaccination strategies in the context of polyclonal repertoires

Library of Seleno-Compounds as Novel Agents against Leishmania Species

The in vitro leishmanicidal activities of a series of 48 recently synthesized selenium derivatives against Leishmania infantum and Leishmania braziliensis parasites were tested using promastigotes and intracellular amastigote forms. The cytotoxicity of the tested compounds for J774.2 macrophage cells was also measured in order to establish their selectivity. Six of the tested compounds (compounds 8, 10, 11, 15, 45, and 48) showed selectivity indexes higher than those of the reference drug, meglumine antimonate (Glucantime), for both Leishmania species; in the case of L. braziliensis, compound 20 was also remarkably selective. Moreover, data on infection rates and amastigote numbers per macrophage showed that compounds 8, 10, 11, 15, 45, and 48 were the most active against both Leishmania species studied. The observed changes in the excretion product profile of parasites treated with these six compounds were also consistent with substantial cytoplasmic alterations. On the other hand, the most active compounds were potent inhibitors of Fe superoxide dismutase (Fe-SOD) in the two parasite species considered, whereas their impact on human CuZn-SOD was low. The high activity, low toxicity, stability, low cost of the starting materials, and straightforward synthesis make these compounds appropriate molecules for the development of affordable antileishmanicidal agents

Inverse Association between trans Isomeric and Long-Chain Polyunsaturated Fatty Acids in Pregnant Women and Their Newborns: Data from Three European Countries

Background: trans unsaturated fatty acids are thought to interfere with essential fatty acid metabolism. To extend our knowledge of this phenomenon, we investigated the relationship between trans isomeric and long-chain polyunsaturated fatty acids (LCPUFA) in mothers during pregnancy and in their infants at birth. Methods: Fatty acid composition of erythrocyte phosphatidylcholine (PC) and phosphatidylethanolamine (PE) was determined in Spanish (n = 120), German (n = 78) and Hungarian (n = 43) women at the 20th and 30th week of gestation, at delivery and in their newborns. Results: At the 20th week of gestation, the sum of trans fatty acids in PE was significantly (p < 0.01) lower in Hungarian [0.73 (0.51), % wt/wt, median (IQR)] than in Spanish [1.42 (1.36)] and German [1.30 (1.21)] women. Docosahexaenoic acid (DHA) values in PE were significantly (p < 0.01) higher in Hungarian {[}5.65 (2.09)] than in Spanish [4.37 (2.60)] or German [4.39 (3.3.2)] women. The sum of trans fatty acids significantly inversely correlated to DHA in PCs in Spanish (r = -0.37, p < 0.001), German (n = -0.77, p < 0.001) and Hungarian (r = -0.35, p < 0.05) women, and in PEs in Spanish (r = -0.67, p < 0.001) and German (r = -0.71, p < 0.001), but not in Hungarian (r = -0.02) women. Significant inverse correlations were seen between trans fatty acids and DHA in PEs at the 30th week of gestation (n = 241, r = -0.52, p < 0.001), at delivery (n = 241, r = -0.40, p < 0.001) and in cord lipids (n = 218, r = -0.28, p < 0.001). Conclusion: Because humans cannot synthesize trans isomeric fatty acids, the data obtained in the present study support the concept that high maternal trans isomeric fatty acid intake may interfere with the availability of LCPUFA both for the mother and the fetus. Copyright (C) 2011 S. Karger AG, Base