974 resultados para Learning sequence
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The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.
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Biomphalaria glabrata, B. tenagophila and B. straminea are intermediate hosts of Schistosoma mansoni, in Brazil. The latter is of epidemiological importance in the northwest of Brazil and, due to morphological similarities, has been grouped with B. intermedia and B. kuhniana in a complex named B. straminea. In the current work, we have standardized the simple sequence repeat anchored polymerase chain reaction (SSR-PCR) technique, using the primers (CA)8RY and K7, to study the genetic variability of these species. The similarity level was calculated using the Dice coefficient and genetic distance using the Nei and Li coefficient. The trees were obtained by the UPGMA and neighbor-joining methods. We have observed that the most related individuals belong to the same species and locality and that individuals from different localities, but of the same species, present clear heterogeneity. The trees generated using both methods showed similar topologies. The SSR-PCR technique was shown to be very efficient in intrapopulational and intraspecific studies of the B. straminea complex snails.
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In an uncertain environment, probabilities are key to predicting future events and making adaptive choices. However, little is known about how humans learn such probabilities and where and how they are encoded in the brain, especially when they concern more than two outcomes. During functional magnetic resonance imaging (fMRI), young adults learned the probabilities of uncertain stimuli through repetitive sampling. Stimuli represented payoffs and participants had to predict their occurrence to maximize their earnings. Choices indicated loss and risk aversion but unbiased estimation of probabilities. BOLD response in medial prefrontal cortex and angular gyri increased linearly with the probability of the currently observed stimulus, untainted by its value. Connectivity analyses during rest and task revealed that these regions belonged to the default mode network. The activation of past outcomes in memory is evoked as a possible mechanism to explain the engagement of the default mode network in probability learning. A BOLD response relating to value was detected only at decision time, mainly in striatum. It is concluded that activity in inferior parietal and medial prefrontal cortex reflects the amount of evidence accumulated in favor of competing and uncertain outcomes.
Design of a Control Slide for Cyanoacrylate Polymerization : Application to the CA-Bluestar Sequence
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Casework expercience has shown that, in some cases, long exposures of surfaces subjected to cyanoacrylate (CA) fuming had detrimental effects on the subsequent application of Bluestar. This study aimed to develop a control mechanism to monitor the amount of CA deposited prior to the subsequent treatment. A control slide bearing spots of sodium hydroxide (NaOH) of known concentrations and volume was designed and validated against both scanning electron microscopy (SEM) observations and latent print examiners' assessments of the quality of the developed marks. The control slide allows one to define three levels of development that were used to monitor the Bluestar reaction on depleting footwear marks left in diluted blood. The appropriate conditions for a successful application of both CA and Bluestar were determined.
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Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot
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In fear conditioning, an animal learns to associate an unconditioned stimulus (US), such as a shock, and a conditioned stimulus (CS), such as a tone, so that the presentation of the CS alone can trigger conditioned responses. Recent research on the lateral amygdala has shown that following cued fear conditioning, only a subset of higher-excitable neurons are recruited in the memory trace. Their selective deletion after fear conditioning results in a selective erasure of the fearful memory. I hypothesize that the recruitment of highly excitable neurons depends on responsiveness to stimuli, intrinsic excitability and local connectivity. In addition, I hypothesize that neurons recruited for an initial memory also participate in subsequent memories, and that changes in neuronal excitability affect secondary fear learning. To address these hypotheses, I will show that A) a rat can learn to associate two successive short-term fearful memories; B) neuronal populations in the LA are competitively recruited in the memory traces depending on individual neuronal advantages, as well as advantages granted by the local network. By performing two successive cued fear conditioning experiments, I found that rats were able to learn and extinguish the two successive short-term memories, when tested 1 hour after learning for each memory. These rats were equipped with a system of stable extracellular recordings that I developed, which allowed to monitor neuronal activity during fear learning. 233 individual putative pyramidal neurons could modulate their firing rate in response to the conditioned tone (conditioned neurons) and/or non- conditioned tones (generalizing neurons). Out of these recorded putative pyramidal neurons 86 (37%) neurons were conditioned to one or both tones. More precisely, one population of neurons encoded for a shared memory while another group of neurons likely encoded the memories' new features. Notably, in spite of a successful behavioral extinction, the firing rate of those conditioned neurons in response to the conditioned tone remained unchanged throughout memory testing. Furthermore, by analyzing the pre-conditioning characteristics of the conditioned neurons, I determined that it was possible to predict neuronal recruitment based on three factors: 1) initial sensitivity to auditory inputs, with tone-sensitive neurons being more easily recruited than tone- insensitive neurons; 2) baseline excitability levels, with more highly excitable neurons being more likely to become conditioned; and 3) the number of afferent connections received from local neurons, with neurons destined to become conditioned receiving more connections than non-conditioned neurons. - En conditionnement de la peur, un animal apprend à associer un stimulus inconditionnel (SI), tel un choc électrique, et un stimulus conditionné (SC), comme un son, de sorte que la présentation du SC seul suffit pour déclencher des réflexes conditionnés. Des recherches récentes sur l'amygdale latérale (AL) ont montré que, suite au conditionnement à la peur, seul un sous-ensemble de neurones plus excitables sont recrutés pour constituer la trace mnésique. Pour apprendre à associer deux sons au même SI, je fais l'hypothèse que les neurones entrent en compétition afin d'être sélectionnés lors du recrutement pour coder la trace mnésique. Ce recrutement dépendrait d'un part à une activation facilité des neurones ainsi qu'une activation facilité de réseaux de neurones locaux. En outre, je fais l'hypothèse que l'activation de ces réseaux de l'AL, en soi, est suffisante pour induire une mémoire effrayante. Pour répondre à ces hypothèses, je vais montrer que A) selon un processus de mémoire à court terme, un rat peut apprendre à associer deux mémoires effrayantes apprises successivement; B) des populations neuronales dans l'AL sont compétitivement recrutées dans les traces mnésiques en fonction des avantages neuronaux individuels, ainsi que les avantages consentis par le réseau local. En effectuant deux expériences successives de conditionnement à la peur, des rats étaient capables d'apprendre, ainsi que de subir un processus d'extinction, pour les deux souvenirs effrayants. La mesure de l'efficacité du conditionnement à la peur a été effectuée 1 heure après l'apprentissage pour chaque souvenir. Ces rats ont été équipés d'un système d'enregistrements extracellulaires stables que j'ai développé, ce qui a permis de suivre l'activité neuronale pendant l'apprentissage de la peur. 233 neurones pyramidaux individuels pouvaient moduler leur taux d'activité en réponse au son conditionné (neurones conditionnés) et/ou au son non conditionné (neurones généralisant). Sur les 233 neurones pyramidaux putatifs enregistrés 86 (37%) d'entre eux ont été conditionnés à un ou deux tons. Plus précisément, une population de neurones code conjointement pour un souvenir partagé, alors qu'un groupe de neurones différent code pour de nouvelles caractéristiques de nouveaux souvenirs. En particulier, en dépit d'une extinction du comportement réussie, le taux de décharge de ces neurones conditionné en réponse à la tonalité conditionnée est resté inchangée tout au long de la mesure d'apprentissage. En outre, en analysant les caractéristiques de pré-conditionnement des neurones conditionnés, j'ai déterminé qu'il était possible de prévoir le recrutement neuronal basé sur trois facteurs : 1) la sensibilité initiale aux entrées auditives, avec les neurones sensibles aux sons étant plus facilement recrutés que les neurones ne répondant pas aux stimuli auditifs; 2) les niveaux d'excitabilité des neurones, avec les neurones plus facilement excitables étant plus susceptibles d'être conditionnés au son ; et 3) le nombre de connexions reçues, puisque les neurones conditionné reçoivent plus de connexions que les neurones non-conditionnés. Enfin, nous avons constaté qu'il était possible de remplacer de façon satisfaisante le SI lors d'un conditionnement à la peur par des injections bilatérales de bicuculline, un antagoniste des récepteurs de l'acide y-Aminobutirique.
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The large spatial inhomogeneity in transmit B, field (B-1(+)) observable in human MR images at hi h static magnetic fields (B-0) severely impairs image quality. To overcome this effect in brain T-1-weighted images the, MPRAGE sequence was modified to generate two different images at different inversion times MP2RAGE By combining the two images in a novel fashion, it was possible to create T-1-weigthed images where the result image was free of proton density contrast, T-2* contrast, reception bias field, and, to first order transmit field inhomogeneity. MP2RAGE sequence parameters were optimized using Bloch equations to maximize contrast-to-noise ratio per unit of time between brain tissues and minimize the effect of B-1(+) variations through space. Images of high anatomical quality and excellent brain tissue differentiation suitable for applications such as segmentation and voxel-based morphometry were obtained at 3 and 7 T. From such T-1-weighted images, acquired within 12 min, high-resolution 3D T-1 maps were routinely calculated at 7 T with sub-millimeter voxel resolution (0.65-0.85 mm isotropic). T-1 maps were validated in phantom experiments. In humans, the T, values obtained at 7 T were 1.15 +/- 0.06 s for white matter (WM) and 1.92 +/- 0.16 s for grey matter (GM), in good agreement with literature values obtained at lower spatial resolution. At 3 T, where whole-brain acquisitions with 1 mm isotropic voxels were acquired in 8 min the T-1 values obtained (0.81 +/- 0.03 S for WM and 1.35 +/- 0.05 for GM) were once again found to be in very good agreement with values in the literature. (C) 2009 Elsevier Inc. All rights reserved.
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In the last decade, dengue fever (DF) in Brazil has been recognized as an important public health problem, and an increasing number of dengue haemorrhagic fever (DHF) cases have been reported since the introduction of dengue virus type 2 (DEN-2) into the country in 1990. In order to analyze the complete genome sequence of a DEN-2 Brazilian strain (BR64022/98), we designed primers to amplify contiguous segments of approximately 500 base pairs across the entire sequence of the viral genome. Twenty fragments amplified by reverse transcriptase-PCR were cloned, and the complete nucleotide and the deduced amino acid sequences were determined. This constitutes the first complete genetic characterization of a DEN-2 strain from Brazil. All amino acid changes differentiating strains related to the Asian/American-Asian genotype were observed in BR64022/98, indicating the Asiatic origin of the strain.
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An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method
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Introduction Lesion detection in multiple sclerosis (MS) is an essential part of its clinical diagnosis. In addition, radiological characterisation of MS lesions is an important research field that aims at distinguishing different MS types, monitoring drug response and prognosis. To date, various MR protocols have been proposed to obtain optimal lesion contrast for early and comprehensive diagnosis of the MS disease. In this study, we compare the sensitivity of five different MR contrasts for lesion detection: (i) the DIR sequence (Double Inversion Recovery, [4]), (ii) the Dark-fluid SPACE acquisition schemes, a 3D variant of a 2D FLAIR sequence [1], (iii) the MP2RAGE [2], an MP-RAGE variant that provides homogeneous T1 contrast and quantitative T1-values, and the sequences currently used for clinical MS diagnosis (2D FLAIR, MP-RAGE). Furthermore, we investigate the T1 relaxation times of cortical and sub-cortical regions in the brain hemispheres and the cerebellum at 3T. Methods 10 early-stage female MS patients (age: 31.64.7y; disease duration: 3.81.9y; disability score, EDSS: 1.80.4) and 10 healthy controls (age and gender-matched: 31.25.8y) were included in the study after obtaining informed written consent according to the local ethic protocol. All experiments were performed at 3T (Magnetom Trio a Tim System, Siemens, Germany) using a 32-channel head coil [5]. The imaging protocol included the following sequences, (all except for axial FLAIR 2D with 1x1x1.2 mm3 voxel and 256x256x160 matrix): DIR (TI1/TI2/TR XX/3652/10000 ms, iPAT=2, TA 12:02 min), MP-RAGE (TI/TR 900/2300 ms, iPAT=3, TA 3:47 min); MP2RAGE (TI1/TI2/TR 700/2500/5000 ms, iPAT=3, TA 8:22 min, cf. [2]); 3D FLAIR SPACE (only for patient 4-6, TI/TR 1800/5000 ms, iPAT=2, TA=5;52 min, cf. [1]); Axial FLAIR (0.9x0.9x2.5 mm3, 256x256x44 matrix, TI/TR 2500/9000 ms, iPAT=2, TA 4:05 min). Lesions were identified by two experienced neurologist and radiologist, manually contoured and assigned to regional locations (s. table 1). Regional lesion masks (RLM) from each contrast were compared for number and volumes of lesions. In addition, RLM were merged in a single "master" mask, which represented the sum of the lesions of all contrasts. T1 values were derived for each location from this mask for patients 5-10 (3D FLAIR contrast was missing for patient 1-4). Results & Discussion The DIR sequence appears the most sensitive for total lesions count, followed by the MP2RAGE (table 1). The 3D FLAIR SPACE sequence turns out to be more sensitive than the 2D FLAIR, presumably due to reduced partial volume effects. Looking for sub-cortical hemispheric lesions, the DIR contrast appears to be equally sensitive to the MP2RAGE and SPACE, but most sensitive for cerebellar MS plaques. The DIR sequence is also the one that reveals cortical hemispheric lesions best. T1 relaxation times at 3T in the WM and GM of the hemispheres and the cerebellum, as obtained with the MP2RAGE sequence, are shown in table 2. Extending previous studies, we confirm overall longer T1-values in lesion tissue and higher standard deviations compared to the non-lesion tissue and control tissue in healthy controls. We hypothesize a biological (different degree of axonal loss and demyelination) rather than technical origin. Conclusion In this study, we applied 5 MR contrasts including two novel sequences to investigate the contrast of highest sensitivity for early MS diagnosis. In addition, we characterized for the first time the T1 relaxation time in cortical and sub-cortical regions of the hemispheres and the cerebellum. Results are in agreement with previous publications and meaningful biological interpretation of the data.
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Simple sequence repeat anchored polymerase chain reaction amplification (SSR-PCR) is a genetic typing technique based on primers anchored at the 5' or 3' ends of microsatellites, at high primer annealing temperatures. This technique has already been used in studies of genetic variability of several organisms, using different primer designs. In order to conduct a detailed study of the SSR-PCR genomic targets, we cloned and sequenced 20 unique amplification products of two commonly used primers, CAA(CT)6 and (CA)8RY, using Biomphalaria glabrata genomic DNA as template. The sequences obtained were novel B. glabrata genomic sequences. It was observed that 15 clones contained microsatellites between priming sites. Out of 40 clones, seven contained complex sequence repetitions. One of the repeats that appeared in six of the amplified fragments generated a single band in Southern analysis, indicating that the sequence was not widespread in the genome. Most of the annealing sites for the CAA(CT)6 primer contained only the six repeats found within the primer sequence. In conclusion, SSR-PCR is a useful genotyping technique. However, the premise of the SSR-PCR technique, verified with the CAA(CT)6 primer, could not be supported since the amplification products did not result necessarily from microsatellite loci amplification.