Measurement of wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques

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.

Continuous flow nanocatalysis: reaction pathways in the conversion of levulinic acid to valuable chemicals

The selective production of 2-methyltetrahydrofuran from levulinic acid has been effectively conducted using designed Cu based catalysts and compared with a commercial Pd/C system under microwave irradiation. Optimised conditions for the most active catalysts Cu-MINT (>90% conversion, 75% selectivity to MTHF) and Pd/C (78% conversion, 92% selectivity to MTHF) were further translated into a continuous flow process using the proposed catalysts to find out the deactivation of Cu-MINT under flow conditions (79 vs. 13% conversion with a switch in selectivity to products after 30 min in flow), the high stability of Pd/C (73 vs. 70% conversion at stable selectivity under analogous conditions to those of Cu-MINT) but, most importantly, different relevant pathways to valuable products from levulinic acid depending on the type of catalyst employed.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

Using GNG to improve 3D feature extraction—Application to 6DoF egomotion

Several recent works deal with 3D data in mobile robotic problems, e.g. mapping or egomotion. Data comes from any kind of sensor such as stereo vision systems, time of flight cameras or 3D lasers, providing a huge amount of unorganized 3D data. In this paper, we describe an efficient method to build complete 3D models from a Growing Neural Gas (GNG). The GNG is applied to the 3D raw data and it reduces both the subjacent error and the number of points, keeping the topology of the 3D data. The GNG output is then used in a 3D feature extraction method. We have performed a deep study in which we quantitatively show that the use of GNG improves the 3D feature extraction method. We also show that our method can be applied to any kind of 3D data. The 3D features obtained are used as input in an Iterative Closest Point (ICP)-like method to compute the 6DoF movement performed by a mobile robot. A comparison with standard ICP is performed, showing that the use of GNG improves the results. Final results of 3D mapping from the egomotion calculated are also shown.

GPGPU implementation of growing neural gas: application to 3D scene reconstruction

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.

Portable 3D laser-camera calibration system with color fusion for SLAM

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

Measurement of wide frequency range structural microvibrations with a pocket digital camera and sub-pixel techniques

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.

Combining visual features and Growing Neural Gas networks for robotic 3D SLAM

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.

Microwave-assisted catalysis by iron oxide nanoparticles on MCM-41: Effect of the support morphology

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.

Heterofunctional Supports in Enzyme Immobilization: From Traditional Immobilization Protocols to Opportunities in Tuning Enzyme Properties

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.

Probing the Electrocatalytic Oxygen Reduction Reaction Reactivity of Immobilized Multicopper Oxidase CueO

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.

Amination of enzymes to improve biocatalyst performance: coupling genetic modification and physicochemical tools

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.

Logic-Based Outer Approximation for the Design of Discrete-Continuous Dynamic Systems with Implicit Discontinuities

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).

Logic-Based Outer-Approximation Algorithm for Solving Discrete-Continuous Dynamic Optimization Problems

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.

Ni-CeO2/C Catalysts with Enhanced OSC for the WGS Reaction

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.