413 resultados para INNOVACION


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Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

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Paper submitted to the 43rd International Symposium on Robotics (ISR2012), Taipei, Taiwan, Aug. 29-31, 2012.

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Analysis of vibrations and displacements is a hot topic in structural engineering. Although there is a wide variety of methods for vibration analysis, direct measurement of displacements in the mid and high frequency range is not well solved and accurate devices tend to be very expensive. Low-cost systems can be achieved by applying adequate image processing algorithms. In this paper, we propose the use of a commercial pocket digital camera, which is able to register more than 420 frames per second (fps) at low resolution, for accurate measuring of small vibrations and displacements. The method is based on tracking elliptical targets with sub-pixel accuracy. Our proposal is demonstrated at a 10 m distance with a spatial resolution of 0.15 mm. A practical application over a simple structure is given, and the main parameters of an attenuated movement of a steel column after an impulsive impact are determined with a spatial accuracy of 4 µm.

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The use of 3D data in mobile robotics provides valuable information about the robot’s environment. Traditionally, stereo cameras have been used as a low-cost 3D sensor. However, the lack of precision and texture for some surfaces suggests that the use of other 3D sensors could be more suitable. In this work, we examine the use of two sensors: an infrared SR4000 and a Kinect camera. We use a combination of 3D data obtained by these cameras, along with features obtained from 2D images acquired from these cameras, using a Growing Neural Gas (GNG) network applied to the 3D data. The goal is to obtain a robust egomotion technique. The GNG network is used to reduce the camera error. To calculate the egomotion, we test two methods for 3D registration. One is based on an iterative closest points algorithm, and the other employs random sample consensus. Finally, a simultaneous localization and mapping method is applied to the complete sequence to reduce the global error. The error from each sensor and the mapping results from the proposed method are examined.

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Catalytically active heterogeneous catalysts have been prepared via microwave deposition of iron oxide nanoparticles (0.5–1.2 wt%) on MCM-41 type silica materials with different morphologies (particles, helical and spheres). This methodology leads to iron oxide nanoparticles composed by a mixture of FeO and Fe2O3 species, being the Fe(II)/Fe(III) peak ratio near to 1.11 by XPS. DRUV spectroscopy indicates the presence of tetrahedral coordinated Fe3+ in the silica framework of the three catalysts as well as some extraframework iron species in the catalysts with particle and sphere-like morphologies. The loading of the nanoparticles does neither affect the mesopore arrangement nor the textural properties of the silica supports, as indicated by SAXS and nitrogen adsorption/desorption isotherms. A detailed investigation of the morphology of the supports in various microwave-assisted catalyzed processes shows that helical mesostructures provide optimum catalytic activities and improved reusabilities in the microwave-assisted redox (selective oxidation of benzyl alcohol) catalyzed process probably due to a combination of lower particle size and higher acidity in comparison with the supports with particle and sphere morphology.

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A heterofunctional support for enzyme immobilization may be defined as that which possesses several distinct functionalities on its surface able to interact with a protein. We will focus on those supports in which a final covalent attachment between the enzyme and the support is achieved. Heterofunctionality sometimes has been featured in very old immobilization techniques, even though in many instances it has been overlooked, giving rise to some misunderstandings. In this respect, glutaraldehyde-activated supports are the oldest multifunctional supports. Their matrix has primary amino groups, the hydrophobic glutaraldehyde chain, and can covalently react with the primary amino groups of the enzyme. Thus, immobilization may start (first event of the immobilization) via different causes and may involve different positions of the enzyme surface depending on the activation degree and immobilization conditions. Other “classical” heterofunctional supports are epoxy commercial supports consisting of reactive covalent epoxy groups on a hydrophobic matrix. Immobilization is performed at high ionic strength to permit protein adsorption, so that covalent attachment may take place at a later stage. Starting from these old immobilization techniques, tailor-made heterofunctional supports have been designed to permit a stricter control of the enzyme immobilization process. The requirement is to find conditions where the main covalent reactive moieties may have very low reactivity toward the enzyme. In this Review we will discuss the suitable properties of the groups able to give the covalent attachment (intending a multipoint covalent attachment), and the groups able to produce the first enzyme adsorption on the support. Prospects, limitations, and likely pathways for the evolution (e.g., coupling of site-directed mutagenesis and thiol heterofunctional supports of enzyme immobilization on heterofunctional supports) will be discussed in this Review.

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The bioelectrocatalytic (oxygen reduction reaction, ORR) properties of the multicopper oxidase CueO immobilized on gold electrodes were investigated. Macroscopic electrochemical techniques were combined with in situ scanning tunneling microscopy (STM) and surface-enhanced Raman spectroscopy at the ensemble and at the single-molecule level. Self-assembled monolayer of mercaptopropionic acid, cysteamine, and p-aminothiophenol were chosen as redox mediators. The highest ORR activity was observed for the protein attached to amino-terminated adlayers. In situ STM experiments revealed that the presence of oxygen causes distinct structure and electronic changes in the metallic centers of the enzyme, which determine the rate of intramolecular electron transfer and, consequently, affect the rate of electron tunneling through the protein. Complementary Raman spectroscopy experiments provided access for monitoring structural changes in the redox state of the type 1 copper center of the immobilized enzyme during the CueO-catalyzed oxygen reduction cycle. These results unequivocally demonstrate the existence of a direct electronic communication between the electrode substrate and the type 1 copper center.

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Improvement of the features of an enzyme is in many instances a pre-requisite for the industrial implementation of these exceedingly interesting biocatalysts. To reach this goal, the researcher may utilize different tools. For example, amination of the enzyme surface produces an alteration of the isoelectric point of the protein along with its chemical reactivity (primary amino groups are the most widely used to obtain the reaction of the enzyme with surfaces, chemical modifiers, etc.) and even its “in vivo” behavior. This review will show some examples of chemical (mainly modifying the carboxylic groups using the carbodiimide route), physical (using polycationic polymers like polyethyleneimine) and genetic amination of the enzyme surface. Special emphasis will be put on cases where the amination is performed to improve subsequent protein modifications. Thus, amination has been used to increase the intensity of the enzyme/support multipoint covalent attachment, to improve the interaction with cation exchanger supports or polymers, or to promote the formation of crosslinkings (both intra-molecular and in the production of crosslinked enzyme aggregates). In other cases, amination has been used to directly modulate the enzyme properties (both in immobilized or free form). Amination of the enzyme surface may also pursue other goals not related to biocatalysis. For example, it has been used to improve the raising of antibodies against different compounds (both increasing the number of haptamers per enzyme and the immunogenicity of the composite) or the ability to penetrate cell membranes. Thus, amination may be a very powerful tool to improve the use of enzymes and proteins in many different areas and a great expansion of its usage may be expected in the near future.

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We address the optimization of discrete-continuous dynamic optimization problems using a disjunctive multistage modeling framework, with implicit discontinuities, which increases the problem complexity since the number of continuous phases and discrete events is not known a-priori. After setting a fixed alternative sequence of modes, we convert the infinite-dimensional continuous mixed-logic dynamic (MLDO) problem into a finite dimensional discretized GDP problem by orthogonal collocation on finite elements. We use the Logic-based Outer Approximation algorithm to fully exploit the structure of the GDP representation of the problem. This modelling framework is illustrated with an optimization problem with implicit discontinuities (diver problem).

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We present an extension of the logic outer-approximation algorithm for dealing with disjunctive discrete-continuous optimal control problems whose dynamic behavior is modeled in terms of differential-algebraic equations. Although the proposed algorithm can be applied to a wide variety of discrete-continuous optimal control problems, we are mainly interested in problems where disjunctions are also present. Disjunctions are included to take into account only certain parts of the underlying model which become relevant under some processing conditions. By doing so the numerical robustness of the optimization algorithm improves since those parts of the model that are not active are discarded leading to a reduced size problem and avoiding potential model singularities. We test the proposed algorithm using three examples of different complex dynamic behavior. In all the case studies the number of iterations and the computational effort required to obtain the optimal solutions is modest and the solutions are relatively easy to find.

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In this work, the WGS performance of a conventional Ni/CeO2 bulk catalyst is compared to that of a carbon-supported Ni-CeO2 catalyst. The carbon-supported sample resulted to be much more active than the bulk one. The higher activity of the Ni-CeO2/C catalyst is associated to its oxygen storage capacity, a parameter that strongly influences the WGS behavior. The stability of the carbon-supported catalyst under realistic operation conditions is also a subject of this paper. In summary, our study represents an approach towards a new generation of Ni-ceria based catalyst for the pure hydrogen production via WGS. The dispersion of ceria nanoparticles on an activated carbon support drives to improved catalytic skills with a considerable reduction of the amount of ceria in the catalyst formulation.

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Supported iron oxide nanoparticles have been incorporated onto hierarchical zeolites by microwave-assisted impregnation and mechanochemical grinding. Nanoparticle-functionalised porous zeolites were characterised by a number of analytical techniques such as XRD, N2 physisorption, TEM, and surface acidity measurements. The catalytic activities of the synthesised nanomaterials were investigated in an alkylation reaction. The results pointed to different species with varying acidity and accessibility in the materials, which provided essentially different catalytic activities in the alkylation of toluene with benzyl chloride under microwave irradiation, selected as the test reaction.

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Las agencias de medios constituyen uno de los sectores publicitarios en el que la aplicación de big data proporciona soluciones innovadoras que debieran ser comunicadas a través, entre otros canales, de sus webs corporativas. Con el propósito de facilitar tal comunicación, las webs deben estar preparadas para ser consultadas por varios dispositivos. Así, este estudio pretende averiguar su uso para comunicar innovaciones relacionadas con big data, cuidando el responsive design, de las 20 primeras agencias de medios españolas, y reflexiona sobre las debilidades, amenazas, fortalezas y oportunidades de tal innovación.

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The mammalian gut microbiota harbors a diverse ecosystem where hundreds of bacterial species interact with each other and their host. Given that bacteria use signals to communicate and regulate group behaviors (quorum sensing), we asked whether such communication between different commensal species can influence the interactions occurring in this environment. We engineered the enteric bacterium, Escherichia coli, to manipulate the levels of the interspecies quorum sensing signal, autoinducer-2 (AI-2), in the mouse intestine and investigated the effect upon antibiotic-induced gut microbiota dysbiosis. E. coli that increased intestinal AI-2 levels altered the composition of the antibiotic-treated gut microbiota, favoring the expansion of the Firmicutes phylum. This significantly increased the Firmicutes/Bacteroidetes ratio, to oppose the strong effect of the antibiotic, which had almost cleared the Firmicutes. This demonstrates that AI-2 levels influence the abundance of the major phyla of the gut microbiota, the balance of which is known to influence human health.

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2000 Mathematics Subject Classification: 60J80, 62M05.