Use of the Glasgow Coma Scale and the Jouvet Coma Scale to evaluate the level of consciousness

The Glasgow Coma Scale (GCS) and the Jouvet Coma Scale (JCS) have been evolved for assessing the depth and duration of impaired consciousness and coma. The analysis and the utilization of these scales have showed that they are complementary. The GCS is more sensitive when there is a more intense loss of consciousness, whereas the JCS shows its sensitivity better in the states close to normal. This study was aimed to compare the results obtained from the evaluation of the consciousness level by the utilization of the two scales. The comparison was done within a prospective study with 48 patients, all of them over 18 years old, interned in three intensive care units of different hospitals in the city of S?o Paulo. The evaluations were done daily by the researchers and the scales applied in sequence totaling 5 minutes. Each scale was applied in 106 evaluations, and the results showed a statistically meaningful difference between the GCS and the JCS as to the indication of alteration in the consciousness levels. In 37.74% of the evaluations done with the JCS there was an indication of alteration in the consciousness level, whereas with the GCS the alteration was present in only 23.58% of the evaluations. Another important observation about the utilization of both scales was that people whose scores were between 9 and 10 in the GCS had had an stronger indication of alteration of consciousness level by the same scale, while those with scores between 12 and 15 had a stronger indication of alteration in the consciousness level by JCS. When using GCS there has been the application of the non-testable (NT) in 20% of the evaluations. This did not occur when using the JCS. However it is believed that specific conditions of that particular group might have led to that result as well as specific characteristics of groups of patients might favor the utilization of different scales to evaluate the consciousness level. Therefore the final choice between such scales should consider the conditions and the peculiar characteristics of the clientele to be evaluated and not individual or health department services preferences.     

Nutritive and non-nutritive attributes of washed-up seaweeds from the coast of Ceará, Brazil

This study assesses the nutritive and non-nutritive attributes of washed-up seaweeds from the Brazilian coast. It covers a broad diversity of species (24 red, nine green and four brown) with reasonable levels of proteins (10–14.8%), high ash contents (13–25%), low lipids (below 1%) and high carbohydrate contents (60%). Toxic and/or antinutritional factors were detected, such as low levels of lectins (32 and 64 HU/g of meal for chicken and rabbit trypsin-treated erythrocytes, respectively), tannins (59 mg/100 g), phytic acid (0.45%), high levels of trypsin inhibitors (99.0% inhibition) and -amylase inhibitors (70.5%). The 0/80% fraction showed moderate toxicity to mice (LD₅₀ of 63.8 mg kg⁻¹). The presence of heavy metals such as cadmium (0.29 mg/100 g), chromium (0.23 mg/100 g), nickel (0.26 mg/100 g) and vanadium (3.56 mg/100 g) was also detected. Despite moderate toxicity and antinutritional limitations, washed-up seaweeds represent a potential food alternative for humans after appropriate processing and environmental remediation to guarantee food safety.     

Multivariate Statistical Differences of MRI Samples of the Human Brain

Multivariate statistical discrimination methods are suitable not only for classification but also for characterization of differences between a reference group of patterns and the population under investigation. In the last years, statistical methods have been proposed to classify and analyse morphological and anatomical structures of medical images. Most of these techniques work in high-dimensional spaces of particular features such as shapes or statistical parametric maps and have overcome the difficulty of dealing with the inherent high dimensionality of medical images by analysing segmented structures individually or performing hypothesis tests on each feature separately. In this paper, we present a general multivariate linear framework that addresses the small sample size problem in medical images. The goal is to identify and analyse the most discriminating hyper-plane separating two populations using all the intensity features simultaneously rather than segmented versions of the data separately or feature-by-feature. To demonstrate the performance of the multivariate linear framework we carry out experimental results on artificially generated data set and on a real medical data composed of magnetic resonance images (MRI) of subjects suffering from Alzheimer’s disease (AD) compared to an elderly healthy control group. To our knowledge this is the first multivariate statistical analysis of the human brain in AD that uses the whole features (texture + shapes) simultaneously rather than segmented version of the images. The conceptual and mathematical simplicity of the approach involves the same operations irrespective of the complexity of the experiment or nature of the spatially normalized data, giving multivariate results that are plausible and easy to interpret by the clinicians.     

Potential of lactic acid bacteria to improve the fermentation and quality of coffee during on‐farm processing

This study describes, for the first time, the potential use of selected lactic acid bacteria (LAB) to conduct improved coffee bean fermentation during on‐farm wet processing. Among different strains tested, Lactobacillus plantarum LPBR01 showed a suitable production of organic acids and flavour‐active esters in a coffee‐pulp simulation medium and was used as starter culture under field conditions. The results indicated that L. plantarum LPBR01 was able to establish an accelerated coffee‐pulp acidification process and potentially reduced the fermentation time from 24 to 12 h. The inoculation of LPBR01 strain also increased significantly the formation of volatile aroma compounds during fermentation process (such as ethyl acetate, ethyl isobutyrate and acetaldehyde) and enabled the production of beverage with distinct sensory notes and a remarkable increase in quality compared to the conventional process. Our results suggest that the use of LAB in coffee processing is an ideal alternative way to conduct faster and improved coffee bean fermentation.     

Micrograded ceramic-metal composites

The article shows new designed cermets and processes concerning primary to applications as thermal insulation materials with low emissivity. A new projected microstructure was obtained where dense regions (micropellets) rest inside the main porous pellet. The feature resembles a frozen hypercube, therefore such architecture is called hyper-pellet/ cermet. The processing method to obtain the hyper-cermet is based on sequential tape castings and sintering techniques. Ni-zirconia lamellae were prepared by a special mechanochemical process followed by sintering, which remain inside the main pellets as a dense region. The whole pellet is turned to be porous by employing pore-forming additives. All the constituents and porosity shapes are aligned along the disc/ flake planes. Thermal conductivity is estimated for the materials up to 800 °C by a flash diffusivimeter. Ceramographic analyses show graded density regions with directional constituents and pores. Applications of such materials are foreseen as temperature insulation materials and thermal radiation shields.     

Microstructure design by mechanical alloying

Mixing and coprecipitation processes are, often, not enough in order to reach materials holding several functional components, like selective catalysts that must work simultaneously. Even though when a homogeneous and fine distribution of the constituents is obtained, the affinity between equal phase particles leads to coarsening during the consolidation (sintering) process, as well as on application, such as the material can loose high reactivity. The present work proposes a new consolidation route – sintering by activated surface (SAS) – that employs sacrificial metal layers to avoid coarsening and to increase the diffusion profiles during sintering, once high activity surfaces are exposed during the first sintering step. Regarding limited oxygen potential is established in the sintering atmosphere, the SAS effect is engaged when a specific projected powder microstructure obtained by mechanical alloying (MA) processing is provided. The MA is driven in such a way that yields cermet powders particles with lamellar pod-like like structures, as shown in the SEM image. This projected morphology comprises the ceramic round particles plated by thin metal layers or embedded on them.Porous nickel–zirconia based cermets are studied with Cu and some selected refractory metal additives. The refractory metals are expected to repeal Cu, which remains in pure state at the cermet. By its turn, Cu addition is postulated to prevent coking when fuel-reforming reactions are involved at the application (e.g. in solid oxide fuel cells). Furthermore, Cu is desired since it promotes shrinkage and lower the sintering temperatures. The SAS process running under argon atmospheres with controlled oxygen partial pressure is found to further reduce the sintering temperature by 100–300 °C, for cermets final densities above 60%TD. The sintering behaviour depends on the chosen additive, being Ag, Cu and Mo the most effective ones. The resulted sintered parts attain a suitable density and phase dispersion for catalysis applications.     

A new ranking method for principal components analysis and its application to face image analysis

In this work, we investigate a new ranking method for principal component analysis (PCA). Instead of sorting the principal components in decreasing order of the corresponding eigenvalues, we propose the idea of using the discriminant weights given by separating hyperplanes to select among the principal components the most discriminant ones. The method is not restricted to any particular probability density function of the sample groups because it can be based on either a parametric or non-parametric separating hyperplane approach. In addition, the number of meaningful discriminant directions is not limited to the number of groups, providing additional information to understand group differences extracted from high-dimensional problems. To evaluate the discriminant principal components, separation tasks have been performed using face images and three different databases. Our experimental results have shown that the principal components selected by the separating hyperplanes allow robust reconstruction and interpretation of the data, as well as higher recognition rates using less linear features in situations where the differences between the sample groups are subtle and consequently most difficult for the standard and state-of-the-art PCA selection methods.     

Exploiting social partners in robot learning

Social learning in robotics has largely focused on imitation learning. Here we take a broader view and are interested in the multifaceted ways that a social partner can influence the learning process. We implement four social learning mechanisms on a robot: stimulus enhancement, emulation, mimicking, and imitation, and illustrate the computational benefits of each. In particular, we illustrate that some strategies are about directing the attention of the learner to objects and others are about actions. Taken together these strategies form a rich repertoire allowing social learners to use a social partner to greatly impact their learning process. We demonstrate these results in simulation and with physical robot ‘playmates’.     

An evolutionary approach for combining different sources of evidence in search engines

Modern Web search engines use different strategies to improve the overall quality of their document rankings. Usually the strategy adopted involves the combination of multiple sources of relevance into a single ranking. This work proposes the use of evolutionary techniques to derive good evidence combination functions using three different sources of evidence of relevance: the textual content of documents, the reputation of documents extracted from the connectivity information available in the processed collection and the anchor text concatenation. The combination functions discovered by our evolutionary strategies were tested using a collection containing 368 queries extracted from a real nation-wide search engine query log with over 12 million documents. The experiments performed indicate that our proposal is an effective and practical alternative for combining sources of evidence into a single ranking. We also show that different types of queries submitted to a search engine can require different combination functions and that our proposal is useful for coping with such differences.     

Enhancement of light field disparity maps by reducing the silhouette effect and plane noise

Multidimensional Systems and Signal Processing - During the last decade, there has been an increasing number of applications dealing with multidimensional visual information, either for 3D object...