C(alpha)-HOLDER CLASSICAL SOLUTIONS FOR NON-AUTONOMOUS NEUTRAL DIFFERENTIAL EQUATIONS

In this paper we discuss the existence of alpha-Holder classical solutions for non-autonomous abstract partial neutral functional differential equations. An application is considered.

Identification of novel non-autonomous CemaT transposable elements and evidence of their mobility within the C. elegans genome

We describe here two new transposable elements, CemaT4 and CemaT5, that were identified within the sequenced genome of Caenorhabditis elegans using homology based searches. Five variants of CemaT4 were found, all non-autonomous and sharing 26 bp inverted terminal repeats (ITRs) and segments (152-367 bp) of sequence with similarity to the CemaT1 transposon of C. elegans. Sixteen copies of a short, 30 bp repetitive sequence, comprised entirely of an inverted repeat of the first 15 bp of CemaT4's ITR, were also found, each flanked by TA dinucleotide duplications, which are hallmarks of target site duplications of mariner-Tc transposon transpositions. The CemaT5 transposable element had no similarity to maT elements, except for sharing identical ITR sequences with CemaT3. We provide evidence that CemaT5 and CemaT3 are capable of excising from the C. elegans genome, despite neither transposon being capable of encoding a functional transposase enzyme. Presumably, these two transposons are cross-mobilised by an autonomous transposon that recognises their shared ITRs. The excisions of these and other non-autonomous elements may provide opportunities for abortive gap repair to create internal deletions and/or insert novel sequence within these transposons. The influence of non-autonomous element mobility and structural diversity on genome variation is discussed.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Axon navigation in the mammalian primary olfactory pathway: Where to next?

The process of establishing long-range neuronal connections can be divided into at least three discrete steps. First, axons need to be stimulated to grow and this growth must be towards appropriate targets. Second, after arriving at their target, axons need to be directed to their topographically appropriate position and in some cases, such as in cortical structures, they must grow radially to reach the correct laminar layer Third, axons then arborize and form synaptic connections with only a defined subpopulation of potential post-synaptic partners. Attempts to understand these mechanisms in the visual system have been ongoing since pioneer studies in the 1940s highlighted the specificity of neuronal connections in the retino-tectal pathway. These classical systems-based approaches culminated in the 1990s with the discovery that Eph-ephrin repulsive interactions were involved in topographical mapping. In marked contrast, it was the cloning of the odorant receptor family that quickly led to a better understanding of axon targeting in the olfactory system. The last 10 years have seen the olfactory pathway rise in prominence as a model system for axon guidance. Once considered to be experimentally intractable, it is now providing a wealth of information on all aspects of axon guidance and targeting with implications not only for our understanding of these mechanisms in the olfactory system but also in other regions of the nervous system.

Um algoritmo PSO híbrido para planejamento de caminhos em navegação de veículos utilizando A*

Utilizar robôs autônomos capazes de planejar o seu caminho é um desafio que atrai vários pesquisadores na área de navegação de robôs. Neste contexto, este trabalho tem como objetivo implementar um algoritmo PSO híbrido para o planejamento de caminhos em ambientes estáticos para veículos holonômicos e não holonômicos. O algoritmo proposto possui duas fases: a primeira utiliza o algoritmo A* para encontrar uma trajetória inicial viável que o algoritmo PSO otimiza na segunda fase. Por fim, uma fase de pós planejamento pode ser aplicada no caminho a fim de adaptá-lo às restrições cinemáticas do veículo não holonômico. O modelo Ackerman foi considerado para os experimentos. O ambiente de simulação de robótica CARMEN (Carnegie Mellon Robot Navigation Toolkit) foi utilizado para realização de todos os experimentos computacionais considerando cinco instâncias de mapas geradas artificialmente com obstáculos. O desempenho do algoritmo desenvolvido, A*PSO, foi comparado com os algoritmos A*, PSO convencional e A* Estado Híbrido. A análise dos resultados indicou que o algoritmo A*PSO híbrido desenvolvido superou em qualidade de solução o PSO convencional. Apesar de ter encontrado melhores soluções em 40% das instâncias quando comparado com o A*, o A*PSO apresentou trajetórias com menos pontos de guinada. Investigando os resultados obtidos para o modelo não holonômico, o A*PSO obteve caminhos maiores entretanto mais suaves e seguros.

Preliminary clinical trial in percutaneous nephrolithotomy using a real-time navigation system for percutaneous kidney access

Background: Precise needle puncture of renal calyces is a challenging and essential step for successful percutaneous nephrolithotomy. This work tests and evaluates, through a clinical trial, a real-time navigation system to plan and guide percutaneous kidney puncture. Methods: A novel system, entitled i3DPuncture, was developed to aid surgeons in establishing the desired puncture site and the best virtual puncture trajectory, by gathering and processing data from a tracked needle with optical passive markers. In order to navigate and superimpose the needle to a preoperative volume, the patient, 3D image data and tracker system were previously registered intraoperatively using seven points that were strategically chosen based on rigid bone structures and nearby kidney area. In addition, relevant anatomical structures for surgical navigation were automatically segmented using a multi-organ segmentation algorithm that clusters volumes based on statistical properties and minimum description length criterion. For each cluster, a rendering transfer function enhanced the visualization of different organs and surrounding tissues. Results: One puncture attempt was sufficient to achieve a successful kidney puncture. The puncture took 265 seconds, and 32 seconds were necessary to plan the puncture trajectory. The virtual puncture path was followed correctively until the needle tip reached the desired kidney calyceal. Conclusions: This new solution provided spatial information regarding the needle inside the body and the possibility to visualize surrounding organs. It may offer a promising and innovative solution for percutaneous punctures.

Geostatistical Mapping of Outfall Plume Dispersion Data gathered with an autonomous underwater vehicle

The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron’s classical estimator was used the compute the experimental semivariogram which was fitted to three theoretical models: spherical, exponential and gaussian. The cross-validation procedure suggested the best semivariogram model and ordinary kriging was used to obtain the predictions of salinity at unknown locations. The generated map shows clearly the plume dispersion in the studied area, indicating that the effluent does not reach the near by beaches. Our study suggests that an optimal design for the AUV sampling trajectory from a geostatistical prediction point of view, can help to compute more precise predictions and hence to quantify more accurately dilution. Moreover, since accurate measurements of plume’s dilution are rare, these studies might be very helpful in the future for validation of dispersion models.

A new control strategy with saturation effect compensation for an autonomous induction generator drivenby wide speed range turbines

This paper presents a variable speed autonomous squirrel cage generator excited by a current-controlled voltage source inverter to be used in stand-alone micro-hydro power plants. The paper proposes a system control strategy aiming to properly excite the machine as well as to achieve the load voltage control. A feed-forward control sets the appropriate generator flux by taking into account the actual speed and the desired load voltage. A load voltage control loop is used to adjust the generated active power in order to sustain the load voltage at a reference value. The control system is based on a rotor flux oriented vector control technique which takes into account the machine saturation effect. The proposed control strategy and the adopted system models were validated both by numerical simulation and by experimental results obtained from a laboratory prototype. Results covering the prototype start-up, as well as its steady-state and dynamical behavior are presented. (C) 2011 Elsevier Ltd. All rights reserved.

Symbolic dynamics and renormalization of non-autonomous k periodic dynamical systems

The purpose of this paper was to introduce the symbolic formalism based on kneading theory, which allows us to study the renormalization of non-autonomous periodic dynamical systems.

Construção de um robô trepador com locomoção através de rodas e adesão através de meios magnéticos

Mestrado em Engenharia Electrotécnica e de Computadores

Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos

Pós-graduação em Ciência da Computação - IBILCE

Sistema de visão para percepção e navegação de um UAV Quadrotor

Mestrado em Engenharia Electrotécnica e de Computadores