Alternative Techniques of Neural Signal Processing in Neuroengineering

Neural signal processing is a discipline within neuroengineering. This interdisciplinary approach combines principles from machine learning, signal processing theory, and computational neuroscience applied to problems in basic and clinical neuroscience. The ultimate goal of neuroengineering is a technological revolution, where machines would interact in real time with the brain. Machines and brains could interface, enabling normal function in cases of injury or disease, brain monitoring, and/or medical rehabilitation of brain disorders. Much current research in neuroengineering is focused on understanding the coding and processing of information in the sensory and motor systems, quantifying how this processing is altered in the pathological state, and how it can be manipulated through interactions with artificial devices including brain–computer interfaces and neuroprosthetics.

A qualitative analysis of immigrant population health practices in the Girona Healthcare Region

The research we present here forms part of a two-phase project - one quantitative and the other qualitative - assessing the use of primary health care services. This paper presents the qualitative phase of said research, which is aimed at ascertaining the needs, beliefs, barriers to access and health practices of the immigrant population in comparison with the native population, as well as the perceptions of healthcare professionals. Moroccan and sub-Saharan were the immigrants to who the qualitative phase was specifically addressed. The aims of this paper are as follows: to analyse any possible implications of family organisation in the health practices of the immigrant population; to ascertain social practices relating to illness; to understand the significances of sexual and reproductive health practices; and to ascertain the ideas and perceptions of immigrants, local people and professionals regarding health and the health system. Methods: qualitative research based on discursive analysis. Data gathering techniques consisted of discussion groups with health system users and semi-structured individual interviews with healthcare professionals. The sample was taken from the Basic Healthcare Areas of Salt and Banyoles (belonging to the Girona Healthcare Region), the discussion groups being comprised of (a) 6 immigrant Moroccan women, (b) 7 immigrant sub-Saharan African women and (c) 6 immigrant and native population men (2 native men, 2 Moroccan men and 2 sub-Saharan men); and the semi-structured interviews being conducted with the following healthcare professionals: (a) 3 gynaecologists, (b) 3 nurses and 1 administrative staff. Results: use of the healthcare system is linked to the perception of not being well, knowledge of the healthcare system, length of time resident in Spain and interiorization of traditional Western medicine as a cure mechanism. The divergences found among the groups of immigrants, local people and healthcare professionals with regard to healthcare education, use of the healthcare service, sexual and reproductive healthcare and reticence with regard to being attended by healthcare personnel of the opposite sex demonstrate a need to work with the immigrant population as a heterogeneous group. Conclusions: the results we have obtained support the idea that feeling unwell is a psycho-social process, as it takes place within a specific socio-cultural situation and spans a range of beliefs, perceptions and ideas regarding symptomology and how to treat it

Computational Techniques for Spectral Image Analysis

Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.

View-dependent information theory quality measures for pixel sampling and scene discretization in flatland

In this paper, we present view-dependent information theory quality measures for pixel sampling and scene discretization in flatland. The measures are based on a definition for the mutual information of a line, and have a purely geometrical basis. Several algorithms exploiting them are presented and compare well with an existing one based on depth differences

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselvesto operate in unused bands without disturbing licensed users. The detection capability of aradio system can be enhanced if the sensing process is performed jointly by a group of nodesso that the effects of wireless fading and shadowing can be minimized. However, taking acollaborative approach poses new security threats to the system as nodes can report falsesensing data to reach a wrong decision. This paper makes a review of secure cooperativespectrum sensing in cognitive radio networks. The main objective of these protocols is toprovide an accurate resolution about the availability of some spectrum channels, ensuring thecontribution from incapable users as well as malicious ones is discarded. Issues, advantagesand disadvantages of such protocols are investigated and summarized.

Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

Determination of moisture content and water activity in algae and fish by thermoanalytical techniques

The water content in seafoods is very important since it affects their sensorial quality, microbiological stability, physical characteristics and shelf life. In this study, thermoanalytical techniques were employed to develop a simple and accurate method to determine water content (moisture) by thermogravimetry (TG) and water activity from moisture content values and freezing point depression using differential scanning calorimetry (DSC). The precision of the results suggests that TG is a suitable technique to determine moisture content in biological samples. The average water content values for fish samples of Lutjanus synagris and Ocyurus chrysurus species were 76.4 ± 5.7% and 63.3 ± 3.9%, respectively, while that of Ulva lactuca marine algae species was 76.0 ± 4.4%. The method presented here was also successfully applied to determine water activity in two species of fish and six species of marine algae collected in the Atlantic coastal waters of Bahia, in Brazil. Water activity determined in fish samples ranged from 0.946 - 0.960 and was consistent with values reported in the literature, i.e., 0.9 - 1.0. The water activity values determined in marine algae samples lay within the interval of 0.974 - 0.979.

Experimental analysis of optimization techniques on the road passenger transportation problem

Analyzing the state of the art in a given field in order to tackle a new problem is always a mandatory task. Literature provides surveys based on summaries of previous studies, which are often based on theoretical descriptions of the methods. An engineer, however, requires some evidence from experimental evaluations in order to make the appropriate decision when selecting a technique for a problem. This is what we have done in this paper: experimentally analyzed a set of representative state-of-the-art techniques in the problem we are dealing with, namely, the road passenger transportation problem. This is an optimization problem in which drivers should be assigned to transport services, fulfilling some constraints and minimizing some function cost. The experimental results have provided us with good knowledge of the properties of several methods, such as modeling expressiveness, anytime behavior, computational time, memory requirements, parameters, and free downloadable tools. Based on our experience, we are able to choose a technique to solve our problem. We hope that this analysis is also helpful for other engineers facing a similar problem

Simultaneous spectrophotometric determination of ezetimibe and simvastatin in pharmaceutical preparations using chemometric techniques

Two spectrophotometric methods are described for the simultaneous determination of ezetimibe (EZE) and simvastatin (SIM) in pharmaceutical preparations. The obtained data was evaluated by using two different chemometric techniques, Principal Component Regression (PCR) and Partial Least-Squares (PLS-1). In these techniques, the concentration data matrix was prepared by using the mixtures containing these drugs in methanol. The absorbance data matrix corresponding to the concentration data matrix was obtained by the measurements of absorbances in the range of 240 - 300 nm in the intervals with Δλ = 1 nm at 61 wavelengths in their zero order spectra, then, calibration or regression was obtained by using the absorbance data matrix and concentration data matrix for the prediction of the unknown concentrations of EZE and SIM in their mixture. The procedure did not require any separation step. The linear range was found to be 5 - 20 µg mL-1 for EZE and SIM in both methods. The accuracy and precision of the methods were assessed. These methods were successfully applied to a pharmaceutical preparation, tablet; and the results were compared with each other.

Micro- and nanostructuring of poly(ethylene-2,6-naphthalate) surfaces, for biomedical applications, using polymer replication techniques

Here we investigate the formation of superficial micro- and nanostructures in poly(ethylene-2,6-naphthalate) (PEN), with a view to their use in biomedical device applications, and compare its performance with a polymer commonly used for the fabrication of these devices, poly(methyl methacrylate) (PMMA). The PEN is found to replicate both micro- and nanostructures in its surface, albeit requiring more forceful replication conditions than PMMA, producing a slight increase in surface hydrophilicity. This ability to form micro/nanostructures, allied to biocompatibility and good optical transparency, suggests that PEN could be a useful material for production of, or for incorporation into, transparent devices for biomedical applications. Such devices will be able to be autoclaved, due to the polymer's high temperature stability, and will be useful for applications where forceful experimental conditions are required, due to a superior chemical resistance over PMMA.

Readout electronics for low dark count pixel detectors based on geiger mode avalanche photodiodes fabricated in conventional CMOS technologies for future linear colliders

The high sensitivity and excellent timing accuracy of Geiger mode avalanche photodiodes makes them ideal sensors as pixel detectors for particle tracking in high energy physics experiments to be performed in future linear colliders. Nevertheless, it is well known that these sensors suffer from dark counts and afterpulsing noise, which induce false hits (indistinguishable from event detection) as well as an increase of the necessary area of the readout system. In this work, we present a comparison between APDs fabricated in a high voltage 0.35 µm and a high integration 0.13 µm commercially available CMOS technologies that has been performed to determine which of them best fits the particle collider requirements. In addition, a readout circuit that allows low noise operation is introduced. Experimental characterization of the proposed pixel is also presented in this work.

Indicadores químicos de qualidade da matéria orgânica de solo da sub-bacia do Rio das Mortes sob manejos diferenciais de cafeeiro

This work evaluated the chemical quality of organic matter (OM) of a Brazilian Oxisol cultivated with coffee plants, under organic and conventional managements. Total organic C (TOC), light fraction C (LF-C) and C in humic (HA-C) and fulvic (FA-C) acids fractions was measured. Amongst the evaluated indexes, TOC and LF-C discriminated better OM attributes as a function of management. The stratification ratio (TOC5-10cm/TOC10-20cm) did not show differences between the systems studied. The organic system can contribute to the sustainability of coffee plantations in Brazil, because it maintains the chemical attributes of OM closer to the indexes verified under forest conditions.

De fatis scientiae chemicae sub epocha patrum

Invocatio: D.D.

De candela sub aquis ardente

Invocatio: Q.F.F.Q.S.

Avaliação da qualidade de sedimentos - estudo de caso: sub-bacia do Ribeirão Espírito Santo, afluente do Rio São Francisco

This study evaluated the environmental impact resulting from surface water and sediment contamination by metals in a watershed affected by a tailing basin that controls effluents coming from a zinc-ore beneficiation plant. The studies combined assessments of sediment chemistry (exceedances of sediment quality guidelines), benthic assemblage structure and acute and chronic ecotoxicity. The results showed that the levels of metal contamination in sediments are not yet enough to cause deleterious effects to the biota. However, the ecotoxicity tests indicated the occurrence of chronic effects, demonstrating that other factors, as the use of fertilizers, could also be a source of contamination.