Influence of arsenate adsorption to ferrihydrite, goethite, and boehmite on the kinetics of arsenate reduction by Shewanella putrefaciens strain CN-32

The kinetics of As(V) reduction by Shewanella putrefaciens strain CN-32 was investigated in suspensions of 0.2, 2, or 20 g L(-1) ferrihydrite, goethite, or boehmite at low As (10 μM) and lactate (25 μM) concentrations. Experimental data were compared with model predictions based on independently determined sorption isotherms and rates of As(V) desorption, As(III) adsorption, and microbial reduction of dissolved As(V), respectively. The low lactate concentration was chosen to prevent significant Fe(III) reduction, but still allowing complete As(V) reduction. Reduction of dissolved As(V) followed first-order kinetics with a 3 h half-life of As(V). Addition of mineral sorbents resulted in pronounced decreases in reduction rates (32-1540 h As(V) half-life). The magnitude of this effect increased with increasing sorbent concentration and sorption capacity (goethite < boehmite < ferrihydrite). The model consistently underestimated the concentrations of dissolved As(V) and the rates of microbial As(V) reduction after addition of S. putrefaciens (～5 × 10(9) cells mL(-1)), suggesting that attachment of S. putrefaciens cells to oxide mineral surfaces promoted As(V) desorption and thereby facilitated As(V) reduction. The interplay between As(V) sorption to mineral surfaces and bacterially induced desorption may thus be critical in controlling the kinetics of As reduction and release in reducing soils and sediments.     

Dealing with hardware heterogeneity: a new parallel search model

In this article we present Ethane, a parallel heterogeneous metaheuristic model specifically designed for its execution on heterogeneous hardware environments. With Ethane we propose a hybrid parallel search algorithm inspired in the structure of the chemical compound of the same name, implementing a heterogeneous island model based in the structure of the chemical bonds of the ethane compound. Here we also shape a schema for describing a complete family of parallel heterogeneous metaheuristics inspired by the structure of hydrocarbons in nature, HydroCM (HydroCarbon inspired Metaheuristics), establishing a resemblance between atoms and computers, and between chemical bonds and communication links. Our goal is to gracefully match computers of different computing power to algorithms of different behavior (genetic algorithm and simulated annealing in this study), all them collaborating to solve the same problem. In addition to the nice natural metaphor we will show that Ethane, though simple, can solve search problems in a faster and more robust way than well-known panmictic and distributed algorithms very popular in the literature, as well as can achieve a better exploration/exploitation balance during the search process.     

An energy efficient middleware for an ad-hoc AAL wireless sensor network

DIA (Dispositivo Inteligente de Alarma, in Spanish) is an AAL (Ambient Assisted Living) system that allows to infer a potential dangerous action of an elderly person living alone at home. This inference is obtained by a specific sensorisation with sensor nodes (portables and fixes) and a reasoning layer embedded in a PC that learns of the users behaviour patterns and advices when actual one differs significantly of the normal patterns. In AAL systems, energy is a limited resource therefore sensor devices need to be properly managed to conserve energy. In this paper, we introduce the design and implementation of innovative and specific mechanisms at the sensory layer middleware which is capable of, first to discriminate spurious motion detections assuming that these signals do not resemble the patterns of real motion detections and, second to reduce the dynamics of messages by a sensor signal processing in order to compress the whole information in one single event. The middleware achieves power saving by modifying the raw information from sensors and adapting it to the predefined semantic of the reasoning layer. It manages the important task of data processing from sensors (raw information), and transfers the pre-processed information into the top layer of reasoning in a more energy efficient way. We also address the trade-off between reducing power consumption and reducing delay for incoming data. We present results from experiments using our implementation of these mechanisms at the middleware that comprises from node firmware to the PC driver. The number of messages of the proposed method with respect to the raw data is reduced by approximately 98.5%. The resources used in the PIR signal processing is reduced by approximately 85%. The resulting delay introduced is small (10–19 s) but system dynamics is slow enough to avoid contextualisation errors or reduction of system performance. We consider these results as very satisfactory.     

Solid lubricant behavior of MoS2 and WSe2-based nanocomposite coatings

Abstract

Tribological coatings made of MoS₂ and WSe₂ phases and their corresponding combinations with tungsten carbide (WC) were prepared by non-reactive magnetron sputtering of individual targets of similar composition. A comparative tribological analysis of these multiphase coatings was done in both ambient air (30–40% relative humidity, RH) and dry nitrogen (RH<7%) environments using the same tribometer and testing conditions. A nanostructural study using advanced transmission electron microscopy of the initial coatings and examination of the counterfaces after the friction test using different analytical tools helped to elucidate what governs the tribological behavior for each type of environment. This allowed conclusions to be made about the influence of the coating microstructure and composition on the tribological response. The best performance obtained with a WSe_x film (specific wear rate of 2 × 10^?8 mm³ N^–1m^–1 and a friction coefficient of 0.03–0.05) was compared with that of the well-established MoS₂ lubricant material.     

Stability Analysis of a Human Arm Interacting with a Force Augmenting Device

This paper presents a stability analysis of the interaction between a human and a linear moving Force Augmenting Device (FAD). The analysis employs a mathematical model of the human arm, the FAD and their interaction. As a depart from past works, this article presents a stability analysis considering time-delays in the human model. A key ingredient in the analysis is the use of the Rekasius substitution for replacing the time-delay terms. It is proved that the human machine interaction is stable when the human model has no delays. When delays are considered in the human model, the analysis provides an upper bound for the time-delays preserving a stable interaction. Numerical simulations allow to assess the human-FAD interaction. An experiment is performed with a laboratory prototype, where a human operator lifts a load. It is observed that the human machine interaction is stable and the human operator is able to move the load to a desired position by experiencing very little effort.     

Asynchronous distributed state estimation based on a continuous‐time stochastic model

In this paper, the problem of state estimation in an asynchronous distributed multi‐sensor estimation (ADE) system is considered. In such an ADE system, the state of a plant of interest is estimated by a group of local estimators. Each local estimator based, for example, on a Kalman filter, performs fusion of data from its local sensor and other (remote) processors to compute possibly best state estimates. In performing data fusion, however, two important issues need to be addressed, namely, the problem of asynchronism of local processors and the one of unknown correlation between asynchronous data in local processors. Consequently, there are two main contributions proposed in this paper. The first is a method to deal with asynchronous discrete‐time data based on a continuous‐time stochastic plant model. The second contribution is an asynchronous distributed data‐fusion algorithm. Simulated experiments illustrate the effectiveness of the proposed ADE approach. Copyright © 2011 John Wiley & Sons, Ltd.     

In vitro intestinal absorption of amino acid mixtures extracted from codfish (Gadus morhua L.) salting wastewater

This study reports on the intestinal permeability of salt‐containing mixtures of amino acids extracted from codfish salting wastewater. Permeability was evaluated in vitro using the Caco‐2 cell line model; cell integrity during exposure to mixtures of amino acids was estimated by measuring the transepithelial electrical resistance (TEER). The effect of salt (NaCl) on the permeability and on the intestinal cell's integrity was also examined. Permeation rate (i.e. transport) was ≥95% for all amino acids except for creatine, for which it was 6%. Values for apparent permeability coefficients, P_app > 10^?5 cm s^?1, for mixture with isotonic concentration of NaCl suggest that amino acids are very likely to be absorbed in humans. Mixture with a hypertonic level of NaCl exerts a cytotoxic effect in intestinal cells resulting in a loss of epithelium integrity. Results show that isotonic mixture of amino acids extracted from codfish salting wastewater could be used in food, feed, cosmetic and pharmaceutical formulations. These applications could contribute to the fish industry sustainability.     

Isothermal rheokinetic study of a precured resol resin beyond gelation by torsion

The rheokinetics of the curing process of a resol resin was studied through isothermal analysis. The resin was subjected to a curing pretreatment until gelation was reached. Rectangular torsion was chosen as the appropriate strain form to carry out the study of the resin's curing kinetics, because the viscoelastic behavior of the material was closer to an ideal solid than to a Newtonian fluid. Seven operating temperatures were selected for analysis (80–110°C). The Arrhenius and Kiuna rheokinetic models were applied to the resin's complex viscosity (η*) evolution during the crosslinking of polymer. The resol resin had curing activation energies of 62.6 and 65.8 kJ/mol when the Arrhenius model was applied in four‐ and six‐parameter forms, respectively. The Kiuna model was proposed to fit the nonlinear viscosity region found at the highest temperatures. This model was suitable to predict changes in the resin's complex viscosity, obtaining a curing activation energy of 69.5 kJ/mol for the resin. In addition, the evolution of the degree of mechanical curing was obtained from the elastic modulus, rather than from the more common DSC technique. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Physics inspired algorithms for (co)homology computations of three-dimensional combinatorial manifolds with boundary

The issue of computing (co)homology generators of a cell complex is gaining a pivotal role in various branches of science. While this issue may be rigorously solved in polynomial time, it is still overly demanding for large scale problems. Drawing inspiration from low-frequency electrodynamics, this paper presents a physics inspired algorithm for first cohomology group computations on three-dimensional complexes. The algorithm is general and exhibits orders of magnitude speed up with respect to competing ones, allowing to handle problems not addressable before. In particular, when generators are employed in the physical modeling of magneto-quasistatic problems, this algorithm solves one of the most long-lasting problems in low-frequency computational electromagnetics. In this case, the effectiveness of the algorithm and its ease of implementation may be even improved by introducing the novel concept of lazy cohomology generators.