Combining Support Vector Machines and simulated annealing for stereovision matching with fish eye lenses in forest environments

We present a novel strategy for computing disparity maps from omni-directional stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. Two of them are identified by applying the powerful Support Vector Machines approach. At a second stage, a stereovision matching process is designed based on the application of four stereovision matching constraints: epipolarity, similarity, uniqueness and smoothness. The epipolarity guides the process. The similarity and uniqueness are mapped once again through the Support Vector Machines, but under a different way to the previous case; after this an initial disparity map is obtained. This map is later filtered by applying the Discrete Simulated Annealing framework where the smoothness constraint is conveniently mapped. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies.     

Stronger Lempel-Ziv Based Compressed Text Indexing

Given a text T[1..u] over an alphabet of size σ, the full-text search problem consists in finding the occ occurrences of a given pattern P[1..m] in T. In indexed text searching we build an index on T to improve the search time, yet increasing the space requirement. The current trend in indexed text searching is that of compressed full-text self-indices, which replace the text with a more space-efficient representation of it, at the same time providing indexed access to the text. Thus, we can provide efficient access within compressed space. The Lempel-Ziv index (LZ-index) of Navarro is a compressed full-text self-index able to represent T using 4uH _k (T)+o(ulog?σ) bits of space, where H _k (T) denotes the k-th order empirical entropy of T, for any k=o(log? _σ u). This space is about four times the compressed text size. The index can locate all the occ occurrences of a pattern P in T in O(m ³log?σ+(m+occ)log?u) worst-case time. Although this index has proven very competitive in practice, the O(m ³log?σ) term can be excessive for long patterns. Also, the factor 4 in its space complexity makes it larger than other state-of-the-art alternatives. In this paper we present stronger Lempel-Ziv based indices (LZ-indices), improving the overall performance of the original LZ-index. We achieve indices requiring (2+ε)uH _k (T)+o(ulog?σ) bits of space, for any constant ε>0, which makes them the smallest existing LZ-indices. We simultaneously improve the search time to O(m ²+(m+occ)log?u), which makes our indices very competitive with state-of-the-art alternatives. Our indices support displaying any text substring of length ? in optimal O(?/log? _σ u) time. In addition, we show how the space can be squeezed to (1+ε)uH _k (T)+o(ulog?σ) to obtain a structure with O(m ²) average search time for m≥2log? _σ u. Alternatively, the search time of LZ-indices can be improved to O((m+occ)log?u) with (3+ε)uH _k (T)+o(ulog?σ) bits of space, which is much less than the space needed by other Lempel-Ziv-based indices achieving the same search time. Overall our indices stand out as a very attractive alternative for space-efficient indexed text searching.     

Probabilistic proximity search: Fighting the curse of dimensionality in metric spaces

Proximity searches become very difficult on “high dimensional” metric spaces, that is, those whose histogram of distances has a large mean and/or a small variance. This so-called “curse of dimensionality”, well known in vector spaces, is also observed in metric spaces. The search complexity grows sharply with the dimension and with the search radius. We present a general probabilistic framework applicable to any search algorithm and whose net effect is to reduce the search radius. The higher the dimension, the more effective the technique. We illustrate empirically its practical performance on a particular class of algorithms, where large improvements in the search time are obtained at the cost of a very small error probability.     

Applying EuroWordNet to Cross-Language Text Retrieval

We discuss ways in which EuroWordNet (EWN) can be used in multilingual information retrieval activities, focusing on two approaches to Cross-Language Text Retrieval that use the EWN database as a large-scale multilingual semantic resource. The first approach indexes documents and queries in terms of the EuroWordNet Inter-Lingual-Index, thus turning term weighting and query/document matching into language-independent tasks. The second describes how the information in the EWN database could be integrated with a corpus-based technique, thus allowing retrieval of domain-specific terms that may not be present in our multilingual database. Our objective is to show the potential of EuroWordNet as a promising alternative to existing approaches to Cross-Language Text Retrieval.     

Elastic behaviour of polyvinyl chloride melts

A study has been made of the elastic behaviour of Polyvinylchloride commercial samples at high shear stresses, under similar conditions to those used in the processing industry, by means of an extrusion capillary rheometer.The influence in the die swell of variables as molecular weight, temperature and shear rate has been studied. Results are in agreement with general literature data.Smooth extrudates are obtained only in the zone of intermediate shear rates. In this zone it is observed that the die swell increases with shear rate.     

Two-dimensional phase unwrapping of subsampled phase-shifted interferograms

Abstract

A novel procedure for phase recovery from undersampled phaseshifted interferograms is described. First, synthetic interferograms are used to calculate the wrapped phase differences along two orthogonal directions. Second, they are unwrapped to recover the true Laplacian of the phase. The final step is to integrate the unwrapped phase differences to obtain the required phase. This method may be used with either path-independent or path-dependent phase unwrapping algorithms. The technique overcomes the sensitivity to noise of previous algorithms when low pass filtering techniques are applied during the calculation of the phase differences and least square methods are employed in the final step of phase integration.     

Roles of the Unsaturated Fatty Acid Docosahexaenoic Acid in the Central Nervous System: Molecular and Cellular Insights

Fatty acids (FAs) are essential components of the central nervous system (CNS), where they exert multiple roles in health and disease. Among the FAs, docosahexaenoic acid (DHA) has been widely recognized as a key molecule for neuronal function and cell signaling. Despite its relevance, the molecular pathways underlying the beneficial effects of DHA on the cells of the CNS are still unclear. Here, we summarize and discuss the molecular mechanisms underlying the actions of DHA in neural cells with a special focus on processes of survival, morphological development, and synaptic maturation. In addition, we examine the evidence supporting a potential therapeutic role of DHA against CNS tumor diseases and tumorigenesis. The current results suggest that DHA exerts its actions on neural cells mainly through the modulation of signaling cascades involving the activation of diverse types of receptors. In addition, we found evidence connecting brain DHA and ω-3 PUFA levels with CNS diseases, such as depression, autism spectrum disorders, obesity, and neurodegenerative diseases. In the context of cancer, the existing data have shown that DHA exerts positive actions as a coadjuvant in antitumoral therapy. Although many questions in the field remain only partially resolved, we hope that future research may soon define specific pathways and receptor systems involved in the beneficial effects of DHA in cells of the CNS, opening new avenues for innovative therapeutic strategies for CNS diseases.     

Modafinil Administration to Preadolescent Rat Impairs Non-Selective Attention,Frontal Cortex D2 Expression and Mesolimbic GABA Levels

The misuse of psychostimulants is an increasing behavior among young people, highlighting in some countries the abuse of modafinil (MOD) as a neuropotentiator. However, several clinical trials are investigating MOD as an alternative pharmacological treatment for attentional deficit and hyperactivity disorder (ADHD) in children and adolescents. On the other hand, the early use of psychostimulants and the misdiagnosis rates in ADHD make it crucial to investigate the brain effects of this type of drug in young healthy individuals. The aim of this work was to evaluate the effects of chronic MOD treatment on neurochemicals (γ-aminobutyric acid and glutamate), dopamine receptor 2 (D₂) expression and behavior (non-selective attention “NSA”) in the mesocorticolimbic system of young healthy Sprague–Dawley rats. Preadolescent male rats were injected with MOD (75 mg/kg, i.p.) or a vehicle for 14 days (from postnatal day 22 to 35). At postnatal day 36, we measured the GLU and GABA contents and their extracellular levels in the nucleus accumbens (NAc). In addition, the GLU and GABA contents were measured in the ventral tegmental area (VTA) and D₂ protein levels in the prefrontal cortex (PFC). Chronic use of MOD during adolescence induces behavioral and neurochemical changes associated with the mesocorticolimbic system, such as a reduction in PFC D₂ expression, VTA GABA levels and NSA. These results contribute to the understanding of the neurological effects of chronic MOD use on a young healthy brain.     

A differential inclusion approach for modeling and analysis of dynamical systems under uncertainty

In this paper we deal with the application of differential inclusions to modeling nonlinear dynamical systems under uncertainty in parameters. In this case, differential inclusions seem to be better suited to modeling practical situations under uncertainty and imprecision than formulations by means of fuzzy differential equations. We develop a practical algorithm to approximate the reachable sets of a class of nonlinear differential inclusion, which eludes the computational problems of a previous set-valued version of the Heun’s method. Our algorithm is based on a complete discretization (time and state space) of the differential inclusion and it suits hardware features, handling the memory used by the method in a controlled fashion during all iterations. As a case of study, we formulate a differential inclusion to model an epidemic outbreak of dengue fever under Cuban conditions. The model takes into account interaction of human and mosquito populations as well as vertical transmission in the mosquito population. It is studied from the theoretical point of view to apply the Practical Algorithm. Also, we estimate the temporal evolution of the different human and mosquito populations given by the model in the Dengue 3 epidemic in Havana 2001, through the computation of the reachable sets using the Practical Algorithm.