995 resultados para focal-plane-array image processors


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Projecte de recerca elaborat a partir d’una estada al Department for Feed and Food Hygiene del National Veterinary Institute, Noruega, entre novembre i desembre del 2006. Els grans de cereal poden estar contaminats amb diferents espècies de Fusarium capaces de produir metabolits secundaris altament tòxics com trichotecenes, fumonisines o moniliformines. La correcta identificació d’aquestes espècies és de gran importància per l’assegurament del risc en l’àmbit de la salut humana i animal. La identificació de Fusarium en base a la seva morfologia requereix coneixements taxonòmics i temps; la majoria dels mètodes moleculars permeten la identificació d’una única espècie diana. Per contra, la tecnologia de microarray ofereix l’anàlisi paral•lel d’un alt nombre de DNA dianes. En aquest treball, s’ha desenvolupat un array per a la identificació de les principals espècies de Fusarium toxigèniques del Nord i Sud d’Europa. S’ha ampliat un array ja existent, per a la detecció de les espècies de Fusarium productores de trichothecene i moniliformina (predominants al Nord d’Europa), amb l’addició de 18 sondes de DNA que permeten identificar les espècies toxigèniques més abundants al Sud d’Europa, les qual produeixen majoritàriament fumonisines. Les sondes de captura han estat dissenyades en base al factor d’elongació translació- 1 alpha (TEF-1alpha). L’anàlisi de les mostres es realitza mitjançant una única PCR que permet amplificar part del TEF-1alpha seguida de la hibridació al xip de Fusarium. Els resultats es visualitzen mitjançant un mètode de detecció colorimètric. El xip de Fusarium desenvolupat pot esdevenir una eina útil i de gran interès per a l’anàlisi de cereals presents en la cadena alimentària.

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After ischemic stroke, the ischemic damage to brain tissue evolves over time and with an uneven spatial distribution. Early irreversible changes occur in the ischemic core, whereas, in the penumbra, which receives more collateral blood flow, the damage is more mild and delayed. A better characterization of the penumbra, irreversibly damaged and healthy tissues is needed to understand the mechanisms involved in tissue death. MRSI is a powerful tool for this task if the scan time can be decreased whilst maintaining high sensitivity. Therefore, we made improvements to a (1) H MRSI protocol to study middle cerebral artery occlusion in mice. The spatial distribution of changes in the neurochemical profile was investigated, with an effective spatial resolution of 1.4 μL, applying the protocol on a 14.1-T magnet. The acquired maps included the difficult-to-separate glutamate and glutamine resonances and, to our knowledge, the first mapping of metabolites γ-aminobutyric acid and glutathione in vivo, within a metabolite measurement time of 45 min. The maps were in excellent agreement with findings from single-voxel spectroscopy and offer spatial information at a scan time acceptable for most animal models. The metabolites measured differed with respect to the temporal evolution of their concentrations and the localization of these changes. Specifically, lactate and N-acetylaspartate concentration changes largely overlapped with the T(2) -hyperintense region visualized with MRI, whereas changes in cholines and glutathione affected the entire middle cerebral artery territory. Glutamine maps showed elevated levels in the ischemic striatum until 8 h after reperfusion, and until 24 h in cortical tissue, indicating differences in excitotoxic effects and secondary energy failure in these tissue types. Copyright © 2011 John Wiley & Sons, Ltd.

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This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

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Candidaemia is the fourth most common cause of bloodstream infection, with a high mortality rate of up to 40%. Identification of host genetic factors that confer susceptibility to candidaemia may aid in designing adjunctive immunotherapeutic strategies. Here we hypothesize that variation in immune genes may predispose to candidaemia. We analyse 118,989 single-nucleotide polymorphisms (SNPs) across 186 loci known to be associated with immune-mediated diseases in the largest candidaemia cohort to date of 217 patients of European ancestry and a group of 11,920 controls. We validate the significant associations by comparison with a disease-matched control group. We observe significant association between candidaemia and SNPs in the CD58 (P = 1.97 × 10(-11); odds ratio (OR) = 4.68), LCE4A-C1orf68 (P = 1.98 × 10(-10); OR = 4.25) and TAGAP (P = 1.84 × 10(-8); OR = 2.96) loci. Individuals carrying two or more risk alleles have an increased risk for candidaemia of 19.4-fold compared with individuals carrying no risk allele. We identify three novel genetic risk factors for candidaemia, which we subsequently validate for their role in antifungal host defence.

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RESUME Durant les dernières années, les méthodes électriques ont souvent été utilisées pour l'investigation des structures de subsurface. L'imagerie électrique (Electrical Resistivity Tomography, ERT) est une technique de prospection non-invasive et spatialement intégrée. La méthode ERT a subi des améliorations significatives avec le développement de nouveaux algorithmes d'inversion et le perfectionnement des techniques d'acquisition. La technologie multicanale et les ordinateurs de dernière génération permettent la collecte et le traitement de données en quelques heures. Les domaines d'application sont nombreux et divers: géologie et hydrogéologie, génie civil et géotechnique, archéologie et études environnementales. En particulier, les méthodes électriques sont souvent employées dans l'étude hydrologique de la zone vadose. Le but de ce travail est le développement d'un système de monitorage 3D automatique, non- invasif, fiable, peu coûteux, basé sur une technique multicanale et approprié pour suivre les variations de résistivité électrique dans le sous-sol lors d'événements pluvieux. En raison des limitations techniques et afin d'éviter toute perturbation physique dans la subsurface, ce dispositif de mesure emploie une installation non-conventionnelle, où toutes les électrodes de courant sont placées au bord de la zone d'étude. Le dispositif le plus approprié pour suivre les variations verticales et latérales de la résistivité électrique à partir d'une installation permanente a été choisi à l'aide de modélisations numériques. Les résultats démontrent que le dispositif pôle-dipôle offre une meilleure résolution que le dispositif pôle-pôle et plus apte à détecter les variations latérales et verticales de la résistivité électrique, et cela malgré la configuration non-conventionnelle des électrodes. Pour tester l'efficacité du système proposé, des données de terrain ont été collectées sur un site d'étude expérimental. La technique de monitorage utilisée permet de suivre le processus d'infiltration 3D pendant des événements pluvieux. Une bonne corrélation est observée entre les résultats de modélisation numérique et les données de terrain, confirmant par ailleurs que le dispositif pôle-dipôle offre une meilleure résolution que le dispositif pôle-pôle. La nouvelle technique de monitorage 3D de résistivité électrique permet de caractériser les zones d'écoulement préférentiel et de caractériser le rôle de la lithologie et de la pédologie de manière quantitative dans les processus hydrologiques responsables d'écoulement de crue. ABSTRACT During the last years, electrical methods were often used for the investigation of subsurface structures. Electrical resistivity tomography (ERT) has been reported to be a useful non-invasive and spatially integrative prospecting technique. The ERT method provides significant improvements, with the developments of new inversion algorithms, and the increasing efficiency of data collection techniques. Multichannel technology and powerful computers allow collecting and processing resistivity data within few hours. Application domains are numerous and varied: geology and hydrogeology, civil engineering and geotechnics, archaeology and environmental studies. In particular, electrical methods are commonly used in hydrological studies of the vadose zone. The aim of this study was to develop a multichannel, automatic, non-invasive, reliable and inexpensive 3D monitoring system designed to follow electrical resistivity variations in soil during rainfall. Because of technical limitations and in order to not disturb the subsurface, the proposed measurement device uses a non-conventional electrode set-up, where all the current electrodes are located near the edges of the survey grid. Using numerical modelling, the most appropriate arrays were selected to detect vertical and lateral variations of the electrical resistivity in the framework of a permanent surveying installation system. The results show that a pole-dipole array has a better resolution than a pole-pole array and can successfully follow vertical and lateral resistivity variations despite the non-conventional electrode configuration used. Field data are then collected at a test site to assess the efficiency of the proposed monitoring technique. The system allows following the 3D infiltration processes during a rainfall event. A good correlation between the results of numerical modelling and field data results can be observed since the field pole-dipole data give a better resolution image than the pole-pole data. The new device and technique makes it possible to better characterize the zones of preferential flow and to quantify the role of lithology and pedology in flood- generating hydrological processes.

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Electroencephalography is mandatory to determine the epilepsy syndrome. However, for the precise localization of the irritative zone in patients with focal epilepsy, costly and sometimes cumbersome imaging techniques are used. Recent small studies using electric source imaging suggest that electroencephalography itself could be used to localize the focus. However, a large prospective validation study is missing. This study presents a cohort of 152 operated patients where electric source imaging was applied as part of the pre-surgical work-up allowing a comparison with the results from other methods. Patients (n = 152) with >1 year postoperative follow-up were studied prospectively. The sensitivity and specificity of each imaging method was defined by comparing the localization of the source maximum with the resected zone and surgical outcome. Electric source imaging had a sensitivity of 84% and a specificity of 88% if the electroencephalogram was recorded with a large number of electrodes (128-256 channels) and the individual magnetic resonance image was used as head model. These values compared favourably with those of structural magnetic resonance imaging (76% sensitivity, 53% specificity), positron emission tomography (69% sensitivity, 44% specificity) and ictal/interictal single-photon emission-computed tomography (58% sensitivity, 47% specificity). The sensitivity and specificity of electric source imaging decreased to 57% and 59%, respectively, with low number of electrodes (<32 channels) and a template head model. This study demonstrated the validity and clinical utility of electric source imaging in a large prospective study. Given the low cost and high flexibility of electroencephalographic systems even with high channel counts, we conclude that electric source imaging is a highly valuable tool in pre-surgical epilepsy evaluation.

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The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

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Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

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Aquest projecte es centra en el disseny d’una antena microstrip per a GNSS. Una antena per a GNSS ha de tenir adaptació de impedància d’entrada i polarització circular a dretes, com a principals especificacions, en el rang de 1.15-1.6 GHz. El tipus d’alimentació d’una antena microstrip amb el major ample de banda d’adaptació és l’alimentació mitjançant acoblament per apertura. Si a l’antena s’introdueixen dos apertures de forma ortogonal, alimentades amb un desfasament de 90º entre elles, s’aconsegueix polarització circular. L’opció de separar les apertures redueix la transferència de potència entre elles, i disminueix el guany de polarització creuada. La xarxa d’alimentació dissenyada és un divisor de Wilkinson amb una línia de λ/4 a la freqüència central, encara que el desfasament als extrems de la banda no sigui de 90º. Com a xarxa d’alimentació es va provar un hibrid de 90º, però l’elevat valor del paràmetre S21 de l’antena impossibilita l’adaptació a l’entrada del hibrid.

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Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.