An optical flow-based sensing system for reactive mobile robot navigation

This work discusses the use of optical flow to generate the sensorial information a mobile robot needs to react to the presence of obstacles when navigating in a non-structured environment. A sensing system based on optical flow and time-to-collision calculation is here proposed and experimented, which accomplishes two important paradigms. The first one is that all computations are performed onboard the robot, in spite of the limited computational capability available. The second one is that the algorithms for optical flow and time-to-collision calculations are fast enough to give the mobile robot the capability of reacting to any environmental change in real-time. Results of real experiments in which the sensing system here proposed is used as the only source of sensorial data to guide a mobile robot to avoid obstacles while wandering around are presented, and the analysis of such results allows validating the proposed sensing system.

ClC-5 chloride channel and kidney stones : what is the link?

Nephrolithiasis is one of the most common diseases in the Western world. The disease manifests itself with intensive pain, sporadic infections, and, sometimes, renal failure. The symptoms are due to the appearance of urinary stones (calculi) which are formed mainly by calcium salts. These calcium salts precipitate in the renal papillae and/or within the collecting ducts. Inherited forms of nephrolithiasis related to chromosome X (X-linked hypercalciuric nephrolithiasis or XLN) have been recently described. Hypercalciuria, nephrocalcinosis, and male predominance are the major characteristics of these diseases. The gene responsible for the XLN forms of kidney stones was cloned and characterized as a chloride channel called ClC-5. The ClC-5 chloride channel belongs to a superfamily of voltage-gated chloride channels, whose physiological roles are not completely understood. The objective of the present review is to identify recent advances in the molecular pathology of nephrolithiasis, with emphasis on XLN. We also try to establish a link between a chloride channel like ClC-5, hypercalciuria, failure in urine acidification and protein endocytosis, which could explain the symptoms exhibited by XLN patients.

Caracterização molecular, formação de biofilme e susceptibilidade a antimicrobianos de isolados de E. coli de aderência difusa Afa/Dr e não Afa/Dr

A Escherichia coli de aderência difusa (DAEC), um patotipo diarreiogênico de E. coli, corresponde a um grupo heterogêneo sem marcador de virulência comum a todos os isolados e de papel controverso na diarreia infantil. O objetivo deste estudo foi caracterizar genotipica e fenotipicamente amostras de DAEC, portadoras e não portadoras de adesinas Afa/Dr, isoladas de crianças com e sem diarreia. Em 70 amostras de DAEC, PCR foi realizado para pesquisa de genes descritos em DAEC, EAEC ou UPEC, que codificam: (i) oito adesinas fimbriais e afimbriais (fimH, papC, sfa, aggA, aafA, agg3A, aidA/aah, afaC); (ii) cinco toxinas (pet, astA, set1A, sat, hlyA); (iii) três proteínas captadoras/receptora de ferro (irp2, iucA, chuA/shuA); (iv) invasina (daaD) e; antígeno 43 (agn43). Ensaio de formação de biofilme foi realizado a partir da bactéria cultivada em caldo Luria-Bertani e inoculada em placas de poliestireno com DMEM suplementado com 0,4% glicose. A leitura da densidade ótica (DO490) foi realizada após coloração com safranina. Soroaglutinação para 23 antígenos O (Probac do Brasil) foi realizada em 50% das DAEC. Método de difusão de disco foi realizado para testar a suscetibilidade a 13 antimicrobianos. A presença de pelo menos um gene que codifica adesinas, toxinas, proteínas captadoras/receptora de ferro, invasina ou antígeno 43 foram encontrados em 58,6%, 51,4%, 80%, 48,6% e 57,1%, respectivamente, com os genes fimH, irp2, agn43, iucA, chuA/shuA, presentes em mais de 50% das amostras. Gene afaC+ (PCR) e/ou sonda afaBC+ (hibridização de colônias) classificou 50% das DAEC como Afa/Dr, sendo pet, sat, irp2, iucA, chuA/shuA e agn43 significantes nessas amostras (p<0,05). Do total das DAEC, 44,3% foram formadoras de biofilme, igualmente distribuídas entre as Afa/Dr e não Afa/Dr, e nenhum gene foi associado com esse fenótipo. Sorologia de 35 amostras evidenciou os seguintes sorogrupos: 1 O29, 2 O125, 2 O127 e 7 O86. Todas as O86 foram de DAEC Afa/Dr. Maiores frequências de resistência antimicrobiana foram encontradas para ampicilina (55,7%), sulfametoxazol/trimetoprim (35,7%) e tetraciclina (28,6%) e o perfil resistente/intermediário para amoxicilina/ácido clavulânico, ampicilina, sulfametoxazol/trimetoprim foi significante nas DAEC Afa/Dr, assim como a multi-droga resistência (p<0,05). Em conclusão, observou-se: (i) alta frequência de fimH e pet e presença de agn43, até então não descrito em DAEC, em frequências similares àquelas encontradas em EAEC, UPEC e EAEC/UPEC, respectivamente; (ii) que as amostras de DAEC Afa/Dr e não Afa/Dr constituíram grupos com perfis genéticos diferenciados entre si; (iii) poucos sorogrupos foram encontrados entre as DAEC; (iv) frequências de resistência menores quando comparado com as poucas descrições em DAEC, sugerindo uma menor pressão seletiva da população do presente estudo e; (v) amostras de DAEC Afa/Dr podem representar um importante reservatório de genes de resistência a antimicrobianos, além de diversos fatores de virulência.

Multi-level governance and social cohesion in the European Union: the assessment of local agents, a study case inside Galicia

Implementing multi-level governance has been a key priority in EU cohesion policy. This study assesses the perceived achievements and shortcomings in implementing European Social Fund by analyzing the deficits and weaknesses as well as the poor participation of local agents who are in direct contact with the beneficiaries in order to design and implement this fund, which is the main financial instrument of EU social policy.

Multi-scale modeling of the mechanical behavior of polymer-based materials

Polymers have become the reference material for high reliability and performance applications. In this work, a multi-scale approach is proposed to investigate the mechanical properties of polymeric based material under strain. To achieve a better understanding of phenomena occurring at the smaller scales, a coupling of a Finite Element Method (FEM) and Molecular Dynamics (MD) modeling in an iterative procedure was employed, enabling the prediction of the macroscopic constitutive response. As the mechanical response can be related to the local microstructure, which in turn depends on the nano-scale structure, the previous described multi-scale method computes the stress-strain relationship at every analysis point of the macro-structure by detailed modeling of the underlying micro- and meso-scale deformation phenomena. The proposed multi-scale approach can enable prediction of properties at the macroscale while taking into consideration phenomena that occur at the mesoscale, thus offering an increased potential accuracy compared to traditional methods.

Coupling Mechanical and Electrical Behavior in the Multi-scale Simulation of Polymer-based CNT Nanocomposites

A numeric model has been proposed to investigate the mechanical and electrical properties of a polymeric/carbon nanotube (CNT) composite material subjected to a deformation force. The reinforcing phase affects the behavior of the polymeric matrix and depends on the nanofiber aspect ratio and preferential orientation. The simulations show that the mechanical behavior of a computer generated material (CGM) depends on fiber length and initial orientation in the polymeric matrix. It is also shown how the conductivity of the polymer/CNT composite can be calculated for each time step of applied stress, effectively providing the ability to simulate and predict strain-dependent electrical behavior of CNT nanocomposites.

Measuring fund performance using multi-factor models: evidence for the Portuguese market

This paper examines the performance of Portuguese equity funds investing in the domestic and in the European Union market, using several unconditional and conditional multi-factor models. In terms of overall performance, we find that National funds are neutral performers, while European Union funds under-perform the market significantly. These results do not seem to be a consequence of management fees. Overall, our findings are supportive of the robustness of conditional multi-factor models. In fact, Portuguese equity funds seem to be relatively more exposed to smallcaps and more value-oriented. Also, they present strong evidence of time-varying betas and, in the case of the European Union funds, of time-varying alphas too. Finally, in terms of market timing, our tests suggest that mutual fund managers in our sample do not exhibit any market timing abilities. Nevertheless, we find some evidence of timevarying conditional market timing abilities but only at the individual fund level.

Predicting the mechanical behavior of amorphous polymeric materials under strain through multi-scale simulation

Polymeric materials have become the reference material for high reliability and performance applications. However, their performance in service conditions is difficult to predict, due in large part to their inherent complex morphology, which leads to non-linear and anisotropic behavior, highly dependent on the thermomechanical environment under which it is processed. In this work, a multiscale approach is proposed to investigate the mechanical properties of polymeric-based material under strain. To achieve a better understanding of phenomena occurring at the smaller scales, the coupling of a finite element method (FEM) and molecular dynamics (MD) modeling, in an iterative procedure, was employed, enabling the prediction of the macroscopic constitutive response. As the mechanical response can be related to the local microstructure, which in turn depends on the nano-scale structure, this multiscale approach computes the stress-strain relationship at every analysis point of the macro-structure by detailed modeling of the underlying micro- and meso-scale deformation phenomena. The proposed multiscale approach can enable prediction of properties at the macroscale while taking into consideration phenomena that occur at the mesoscale, thus offering an increased potential accuracy compared to traditional methods.

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.

Application of Gage R&R methodology for improving the training and evaluation of automatic optical inspection machine operators

The current level of demand by customers in the electronics industry requires the production of parts with an extremely high level of reliability and quality to ensure complete confidence on the end customer. Automatic Optical Inspection (AOI) machines have an important role in the monitoring and detection of errors during the manufacturing process for printed circuit boards. These machines present images of products with probable assembly mistakes to an operator and him decide whether the product has a real defect or if in turn this was an automated false detection. Operator training is an important aspect for obtaining a lower rate of evaluation failure by the operator and consequently a lower rate of actual defects that slip through to the following processes. The Gage R&R methodology for attributes is part of a Six Sigma strategy to examine the repeatability and reproducibility of an evaluation system, thus giving important feedback on the suitability of each operator in classifying defects. This methodology was already applied in several industry sectors and services at different processes, with excellent results in the evaluation of subjective parameters. An application for training operators of AOI machines was developed, in order to be able to check their fitness and improve future evaluation performance. This application will provide a better understanding of the specific training needs for each operator, and also to accompany the evolution of the training program for new components which in turn present additional new difficulties for the operator evaluation. The use of this application will contribute to reduce the number of defects misclassified by the operators that are passed on to the following steps in the productive process. This defect reduction will also contribute to the continuous improvement of the operator evaluation performance, which is seen as a quality management goal.

Use efficiency of variable rate of nitrogen prescribed by optical sensor in corn

ABSTRACT The efficiency of nitrogen fertilizer in corn is usually low, negatively affecting plant nutrition, the economic return, and the environment. In this context, a variable rate of nitrogen, prescribed by crop sensors, has been proposed as an alternative to the uniform rate of nitrogen traditionally used by farmers. This study tested the hypothesis that variable rate of nitrogen, prescribed by optical sensor, increases the nitrogen use efficiency and grain yield as compared to uniform rate of nitrogen. The following treatments were evaluated: 0; 70; 140; and 210 kg ha-1 under uniform rate of nitrogen, and 140 kg ha -1 under variable rate of nitrogen. The nitrogen source was urea applied on the soil surface using a distributor equipped with the crop sensor. In this study, the grain yield ranged from 10.2 to 15.5 Mg ha-1, with linear response to nitrogen rates. The variable rate of nitrogen increased by 11.8 and 32.6% the nitrogen uptake and nitrogen use efficiency, respectively, compared to the uniform rate of nitrogen. However, no significant increase in grain yield was observed, indicating that the major benefit of the variable rate of nitrogen was reducing the risk of environmental impact of fertilizer.

Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets

Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

Fast left ventricle tracking in CMR images using localized anatomical affine optical flow

In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 ± 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction.

Multi-attribute classification of housing conservation status in urban regeneration actions

Urban regeneration is more and more a “universal issue” and a crucial factor in the new trends of urban planning. It is no longer only an area of study and research; it became part of new urban and housing policies. Urban regeneration involves complex decisions as a consequence of the multiple dimensions of the problems that include special technical requirements, safety concerns, socio-economic, environmental, aesthetic, and political impacts, among others. This multi-dimensional nature of urban regeneration projects and their large capital investments justify the development and use of state-of-the-art decision support methodologies to assist decision makers. This research focuses on the development of a multi-attribute approach for the evaluation of building conservation status in urban regeneration projects, thus supporting decision makers in their analysis of the problem and in the definition of strategies and priorities of intervention. The methods presented can be embedded into a Geographical Information System for visualization of results. A real-world case study was used to test the methodology, whose results are also presented.

Simulador multi-agente para o mercado eléctrico

Esta dissertação, apresenta um simulador multi-agente para o mercado eléctrico. Neste simulador agentes heterogéneos, racionalmente limitados e com capacidade de aprendizagem, co-evoluem dinamicamente. O modelo de mercado apresentado é inspirado no mercado diário do MIBEL. É um modelo Pool, gerido por uma entidade operadora de mercado, onde compradores e vendedores podem licitar energia. No lado vendedor, empresas produtoras licitam a energia das suas unidades produtoras em pares quantidadepre ço. Por outro lado, uma vez que o cenário simulado é um mercado de venda, o comprador apresenta uma procura xa, i.e., submete apenas quantidades de energia. Todas as entidades do mercado eléctrico são vistas no sistema multi-agente, modelado através da plataforma INGENIAS, como agentes autónomos. Pelos resultados obtidos nas experiências feitas, confere-se que o simulador é uma ferramenta de apoio à tomada de decisão, pois ajuda a compreender o comportamento emergente do mercado e avalia o impacto das acções escolhidas, manualmente, pelo utilizador ou, automaticamente, atrav és da aprendizagem por reforço. A aprendizagem por reforço visa facilitar a tomada de decisão humana na venda de energia, licitando a energia das unidades produtoras de forma a maximizar os lucros.