Monitoring of the Aggregation Process of Dense Colloidal Silica Suspensions in a Stirred Tank by Acoustic Spectroscopy

The aim of this study is to analyze the behaviour of dense colloidal suspensions in flow by acoustic spectroscopy. The destabilization and the aggregation of stable colloidal silica dispersions in a stirred tank are obtained by addition of salt. Experiments were made in order to observe the influence of different operating parameters, like silica concentration, temperature and stirring speed, on the behaviour of the suspended particles. The use of online acoustic spectroscopy to analyse the process enables us to evaluate the evolution of the silica suspension properties during the aggregation processes. For example, the influence of physicochemical and hydrodynamics parameters on the aggregation process can be simply explained on the basis of the acoustic attenuation spectra. Thus the direct analysis of the spectra can give information on the evolution of the aggregation process and a fast comparison of the effects of the various operational parameters

An application of artificial neural network classifier for medical diagnosis

In recent year, various models have been proposed for medical diagnosis, which broadly can be classified into physical-based approaches and statistical-based approaches. Uncertainty and imprecision are the most important problems in medical diagnosis, other many problems in medical diagnostic domains need to be represented at varying degrees of diagnosis to be solved. Moreover, classification is very important in computer-aided medical diagnosis. In this respect, Artificial Neural Network (ANN) have been successfully applied and with no doubt, they provide the ability and potentials to diagnose the diseases. Therefore, this research focuses on using ANN to classify medical data. ANN model with two layers of tunable weights were used and trained using four different backpropagation algorithms while are the gradient descent(GD), gradient descent with momentum(GDM), gradient descent with adaptive learning rate(GDA) and gradient descent with momentum and adaptive learning rate(GDX). The network was used to classify three sets of medical data taken from UCI machine learning repository. The ability of all training algorithms tested and compared to each other on all datasets. Simulation results proved the ability of ANN for medical data classification with high accuracy and excellent performance and efficiency. This research provides the possibility of reduce costs and human resources. Increasing speed to find the results of medical analysis by using ANN also contributes in saving time for both physicians and patient

Joint perceptual decision-making: a case study in explanatory pluralism.

Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches

Nanostructured sonogels

Acoustic cavitation effects in sol-gel liquid processing permits to obtain nanostructured materials, with size-dependent properties. The so-called "hot spots" produce very high temperatures and pressures which act as nanoreactors. Ultrasounds force the dissolution and the reaction stars. The products (alcohol, water and silanol) help to continue the dissolution, being catalyst content, temperature bath and alkyl group length dependent. Popular choices used in the preparation of silica-based gels are tetramethoxysilane (TMOS), Si(OCH3)4 and tetraethoxysilane (TEOS), Si(OC 2H5)4. The resultant "sonogels" are denser gels with finer and homogeneous porosity than those of classic ones. They have a high surface/volume ratio and are built by small particles (1 nm radius) and a high cross-linked network with low -OH surface coverage radicals. In this way a cluster model is presented based on randomly-packed spheres in several hierarchical levels that represent the real sonoaerogel. Organic modified silicates (ORMOSIL) were obtained by supercritical drying in ethanol of the corresponding alcogel producing a hybrid organic/inorganic aerogel. The new material takes the advantages of the organic polymers as flexibility, low density, toughness and formability whereas the inorganic part contributes with surface hardness, modulus strength, transparency and high refractive index. The sonocatalytic method has proven to be adequate to prepare silica matrices for fine and uniform dispersion of CdS and PbS quantum dots (QDs), which show exciton quantum confinement. We present results of characterization of these materials, such as nitrogen physisorption, small angle X-ray/neutrons scattering, electron microscopy, uniaxial compression and nanoindentation. Finally these materials find application as biomaterials for tissue engineering and for CO2 sequestration by means the carbonation reaction.Ministerio de Ciencia y Tecnología MAT2005-158

Lattice dynamics of MgSiO3_3 perovskite (bridgmanite) studied by inelastic x-ray scattering and ab initio calculations

We have determined the lattice dynamics of MgSiO$_3$ perovskite (bridgmanite) by a combination of single-crystal inelastic x-ray scattering and ab initio calculations. We observe a remarkable agreement between experiment and theory, and provide accurate results for phonon dispersion relations, phonon density of states and the full elasticity tensor. The present work constitutes an important milestone to extend this kind of combined studies to extreme conditions of pressure and temperature, directly relevant for the physics and the chemistry of Earth's lower mantle

Fiber association and network formation in PLA/lignocellulosic fiber composites.

PLA composites were prepared in an internal mixer with a lignocellulosic fiber having relatively large aspect ratio. Fiber content changed between 0 and 60 vol% and the homogenized material was compression molded to 1 mm thick plates. The composites showed anomalous behavior above certain fiber content. Their modulus and especially their strength decreased drastically and modeling also proved the loss of reinforcement at large fiber contents. Micromechanical testing showed that the mechanism of deformation and failure changes at a critical fiber content. Microscopic analysis indi-cated the formation of a network purely from geometrical reasons. The inherent strength of the network is very small because of the weak forces acting among the fibers. This weak inherent strength makes the structure of the composites very sensitive to pro-cessing conditions, and decreases strength, reproducibility as well as reliability