Study of the hydrolysis and condensation of γ-Aminopropyltriethoxysilane by FT-IR spectroscopy

The hydrolysis and condensation reactions of γ-APS have been studied in different acid content aqueous solution by using Fourier Transform infrared (FT-IR) spectroscopy. The hydrolysis of γ-APS under the studied conditions can be followed by the increase of the ethanol band located at 882 cm⁻¹ and the decrease of the band due to the ρ(CH₃) of γ-APS molecules located at 959 cm⁻¹. Hydrolysis reaction is faster by increasing both H₂O and acid concentrations, and it is completed when 3 moles of H₂O per mole of γ-APS are used. The increase of the vibrational band located at 1146 cm⁻¹ shows that condensation of the hydrolysed γ-APS molecules take place forming linear chains in poorly cross-linked structures. Besides, both 8-membered cyclic siloxane formations and poorly cross-linked structures are formed and increase as the water and acid content are increased. On the other hand, highly connected cross-linked structures do not appear due to the steric hindrance of the non-hydrolysable aminopropyl group. The silanol band shows that hydrolysis is faster than condensation except for samples with the lowest H₂O content.     

Robust trend parameters in a multivariate spatial linear model

This article gives a robust estimator of the trend parameters in multivariate spatial linear models. This estimator is presented as an alternative to the classical one which is obtained by using cokriging. The goal focuses on improving predictions of spatial variables when data contain both atypical and high influence observations. The procedure consists of extending robust methods used in linear regression models to the multivariate spatial context. The resulting estimator belongs to the class of GM-estimators and then, it is a bounded influence estimator and it has good robust properties, in particular, a high breakdown point and a high efficiency. An illustrative example is given to show how the proposed estimator works. Research partially supported by Ministerio de Ciencia y Tecnología, Project AGL2000-0978.     

Image contrast enhancement for two-photon fluorescence microscopy in a turbid medium

Image contrast enhancement is investigated for two-photon excitation fluorescence images of a microscopic sample that is buried underneath a turbid medium. The image contrast, which deteriorates rapidly with sample depth because of scattering loss, is enhanced by an increase in the average excitation power of the focused Gaussian (the TEM(00) mode) beam according to a compensation relation that has been derived by use of a Monte Carlo analysis of the scattering problem. A correct increase in the excitation power results in a detected fluorescence signal that remains invariant with sample depth. The scheme is demonstrated on images of DAPI-stained nuclei cells viewed underneath a suspension of 0.105-mum-diameter polystyrene spheres.     

Scintillation and beam-wander analysis in an optical ground station-satellite uplink

In an optical communication link between an optical ground station and a geostationary satellite the main problems appear in the uplink and are due to beam wander and to scintillation. Reliable methods for modeling both effects simultaneously are needed to provide an accurate tool with which the robustness of the communication channel can be tested. Numerical tools, especially the split-step method (also referred to as the fast-Fourier-transform beam propagation method), have demonstrated their ability to deal with problems of optical propagation during atmospheric turbulence. However, obtaining statistically significant results with this technique is computationally intensive. We present an analytical-numerical hybrid technique that provides good information on the variance in optical irradiance with an important saving of time and computational resources.     

The Estimation of Truncation Error by \tau -Estimation for Chebyshev Spectral Collocation Method

In this paper we show how to accurately estimate the local truncation error of the Chebyshev spectral collocation method using $\tau $ -estimation. This method compares the residuals on a sequence of approximations with different polynomial orders. First, we focus the analysis on one-dimensional scalar linear and non-linear test cases to examine the accuracy of the estimation of the truncation error. Then, we show the validity of the analysis for the incompressible Navier–Stokes equations. First on the Kovasznay flow, where an analytical solution is known, and finally in the lid driven cavity (LDC). We demonstrate that this approach yields a highly accurate estimation of the truncation error if the precision of the approximations increases with the polynomial order.     

Granular computing neural-fuzzy modelling: A neutrosophic approach

Granular computing is a computational paradigm that mimics human cognition in terms of grouping similar information together. Compatibility operators such as cardinality, orientation, density, and multidimensional length act on both in raw data and information granules which are formed from raw data providing a framework for human-like information processing where information granulation is intrinsic. Granular computing, as a computational concept, is not new, however it is only relatively recent when this concept has been formalised computationally via the use of Computational Intelligence methods such as Fuzzy Logic and Rough Sets. Neutrosophy is a unifying field in logics that extents the concept of fuzzy sets into a three-valued logic that uses an indeterminacy value, and it is the basis of neutrosophic logic, neutrosophic probability, neutrosophic statistics and interval valued neutrosophic theory. In this paper we present a new framework for creating Granular Computing Neural-Fuzzy modelling structures via the use of Neutrosophic Logic to address the issue of uncertainty during the data granulation process. The theoretical and computational aspects of the approach are presented and discussed in this paper, as well as a case study using real industrial data. The case study under investigation is the predictive modelling of the Charpy Toughness of heat-treated steel; a process that exhibits very high uncertainty in the measurements due to the thermomechanical complexity of the Charpy test itself. The results show that the proposed approach leads to more meaningful and simpler granular models, with a better generalisation performance as compared to other recent modelling attempts on the same data set.     

Control of attendance applied in higher education through mobile NFC technologies

This paper presents an improved attendance control system, required for continuous evaluation which has become compulsory following the Bologna Process. It provides a solution based on NFC technology and is based on a real project developed and pilot tested at the “Universidad Pontificia de Salamanca, Campus Madrid”.     

Correlation between machining direction,cutter geometry and step-over distance in 3-axis milling: Application to milling by zones

Computer-Aided Manufacturing (CAM) occupies an increasingly important role in engineering with all it has to offer in terms of new possibilities and improving designer/manufacturer productivity. The present study addresses machining of free-form surfaces on a 3-axis NC machine tool. There have recently been a large number of studies devoted to planning tool paths on free-form surfaces with various strategies being adopted. These strategies are intended to increase efficiency by reducing the overall length of machining. Often, the choice of the cutter is arbitrary and the work focuses on planning. In order to boost productivity, the present work offers assistance in choosing the cutting tool, the machining direction and cutting by surface zones, adopting a milling strategy by parallel planes. To do so, a comparison is made between milling using a spherical end milling cutter and a torus end milling cutter with the same outer radius. This comparison relates to the radius of curvature of the trace left by the cutter at the point of contact between the tool and the workpiece in relation to the direction of feed motion.     

Network-aware heuristics for inter-domain meta-scheduling in Grids

Grid computing generally involves the aggregation of geographically distributed resources in the context of a particular application. As such resources can exist within different administrative domains, requirements on the communication network must also be taken into account when performing meta-scheduling, migration or monitoring of jobs. Similarly, coordinating efficient interaction between different domains should also be considered when performing such meta-scheduling of jobs. A strategy to perform peer-to-peer-inspired meta-scheduling in Grids is presented. This strategy has three main goals: (1) it takes the network characteristics into account when performing meta-scheduling; (2) communication and query referral between domains is considered, so that efficient meta-scheduling can be performed; and (3) the strategy demonstrates scalability, making it suitable for many scientific applications that require resources on a large scale. Simulation results are presented that demonstrate the usefulness of this approach, and it is compared with other proposals from literature.