Sea surface temperature of the coastal zones of France

Thermal gradients in French coastal zones for the period of one year were mapped in order to enable a coherent study of certain oceanic features detectable by the variations in the sea surface temperature field and their evolution in time. The phenomena examined were mesoscale thermal features in the English Channel, the Bay of Biscay, and the northwestern Mediterranean; thermal gradients generated by French estuary systems; and diurnal heating in the sea surface layer. The investigation was based on Heat Capacity Mapping Mission imagery

Sea surface temperature of the coastal zones of France

The results of an investigation to map the various thermal gradients in the coastal zones of France are presented. Paricular emphasis is given to the natural phenomena and man made thermal effluents. It is shown that a close correlation exist between wind speed direction and the offshore width of the effluent

Sea surface temperature of the coastal zones of France. Heat Capacity Mapping Mission (HCMM)

The author has identified the following significant results. HCMM data analysis shows some mesoscale features which were previously expected to occur: summer coastal upwellings in the Gulf of Lions, tidal fronts bordering the English Channel, and cooler surface waters at the continental shelf break. The analysis of the spectral variance density spectra show that the interpretation of the data usually is limited by the HCMM radiometric performance (noise levels) at wavenumbers below 5 km in the oceanic areas; from this analysis it may also be concluded that a decrease of the radiometric noise level down to 0.1 k against an increase of the ground resolution up to 2 km would give a better optimum of the radiometric performances in the oceanic areas. HCMM data appear to be useful for analysis of the sea surface temperature field, particularly in the very coastal area by profiting from the ground resolution of 500 m

Trace gas emissions to the atmosphere by biomass burning in the west African savannas

Savanna fires and atmospheric carbon dioxide (CO2) detection and estimating burned area using Advanced Very High Resolution Radiometer_(AVHRR) reflectance data are investigated in this two part research project. The first part involves carbon dioxide flux estimates and a three-dimensional transport model to quantify the effect of north African savanna fires on atmospheric CO2 concentration, including CO2 spatial and temporal variability patterns and their significance to global emissions. The second article describes two methods used to determine burned area from AVHRR data. The article discusses the relationship between the percentage of burned area and AVHRR channel 2 reflectance (the linear method) and Normalized Difference Vegetation Index (NDVI) (the nonlinear method). A comparative performance analysis of each method is described

AVHRR and VISSR satellite instrument calibration results for both Cirrus and marine stratocumulus IFO periods

Accurate characterizations of some cloud parameters are dependent upon the absolute accuracy of satellite radiance measurements. Visible wavelength measurements from both the AVHRR and VISSR instruments are often used to study cloud characteristics. Both of these instruments were radiometrically calibrated prior to launch, but neither has an onboard device to monitor degradation after launch. During the FIRE/SRB cirrus Intensive Field Operation (IFO), a special effort was made to monitor calibration of these two instruments onboard the NOAA-9 and GOES-6 spacecraft. In addition, several research groups have combined their efforts to assess the long-term performance of both instruments. These results are presented, and a limited comparison is made with the ERBE calibration standard

Methodology for Jointly Assessing Myocardial Infarct Extent and Regional Contraction in 3-D CMRI

Automated extraction of quantitative parameters from Cardiac Magnetic Resonance Images (CMRI) is crucial for the management of patients with myocardial infarct. This work proposes a post-processing procedure to jointly analyze Cine and Delayed-Enhanced (DE) acquisitions in order to provide an automatic quantification of myocardial contraction and enhancement parameters and a study of their relationship. For that purpose, the following processes are performed: 1) DE/Cine temporal synchronization and 3D scan alignment, 2) 3D DE/Cine rigid registration in a region about the heart, 3) segmentation of the myocardium on Cine MRI and superimposition of the epicardial and endocardial contours on the DE images, 4) quantification of the Myocardial Infarct Extent (MIE), 5) study of the regional contractile function using a new index, the Amplitude to Time Ratio (ATR). The whole procedure was applied to 10 patients with clinically proven myocardial infarction. The comparison between the MIE and the visually assessed regional function scores demonstrated that the MIE is highly related to the severity of the wall motion abnormality. In addition, it was shown that the newly developed regional myocardial contraction parameter (ATR) decreases significantly in delayed enhanced regions. This largely automated approach enables a combined study of regional MIE and left ventricular function

Multiscale structure description of positon Emission tomography difference images

A method is presented here which aims at analyzing Positon Emission Tomography difference images . This method is based on a explicit description of the structure of the images. Positon Emission Tomography images are used to investigate the functional organisation of the brain, looking at the cerebral blood flow . The differences between two images from the same subject lead to th e changes of activity between two particular states . These differences, called "functional activations", are supposed to be specific o f a particular task . The aim is then to detect functional activations while preserving individual information, unlike classical statistica l methods which look mainly for the average information across several subjects . We then build a 3-dimensional linear scale-spac e from the original image. Objects are extracted at each level of scale in a fully-automatic way. Then they are linked across th e scales to get multi-scale objects in the scale-space . A vector of measures is associated to each of these multi-scale objects in order to characterize functional activations . We present a short study to determine the relevancy of these measures and the way the y can be used .Nous présentons ici une méthode d'analyse d'images de différence issues de la Tomographie par Emission de Positons (TEP) qui repose sur une description explicite de la structure de ces images. Les images TEP permettent, par l'intermédiaire du débit sanguin cérébral, de rendre compte de l'état fonctionnel du cerveau. En utilisant la différence entre deux images d'un même sujet, on essaye de déterminer les différences d'activité cérébrale entre deux états. Ces différences sont supposées être spécifiques d'une tâche isolée par la différence entre les deux états, et nous les appellerons « activations fonctionnelles ». L'objectif est donc de caractériser les activations fonctionnelles dans ces images de différence, tout en préservant l'information individuelle propre au sujet, ce qui n'est pas le cas des méthodes statistiques classiques, qui s'intéressent surtout à l'information moyenne sur l'ensemble des sujets. Un espace d'échelles (« scale-space ») linéaire tri-dimensionnel est d'abord construit à partir de l'image de différence originale, puis des objets sont extraits à chaque niveau d'échelle de manière entièrement automatique. ces objets sont ensuites liés dans les échelles pour former d'autres objets dans le scale-space. Des mesures sont alors définies et associées à chacun d'eux, afin de caractériser les activations fonctionnelles. Une étude sur la pertinence des objets définis et l'utilisation possible des mesures associées est présentée

A mutual reference shape based on information theory

International audienceIn this paper, we propose to consider the estimation of a refer-ence shape from a set of different segmentation results using both active contours and information theory. The reference shape is defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations and called a mutual shape. This energy criterion is here justified using similarities between informa-tion theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the speci-ficity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each term of the criterion and interpreted as an evolution equation of an active contour. Some synthetical examples allow us to cast the light on the difference between our mutual shape and an average shape. Our framework has been considered for the estimation of a mutual shape for the evaluation of cardiac segmentation methods in MRI

Gigwa v2—Extended and improved genotype investigator

The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution. Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data). This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community

Dissecting the heterogeneous cortical anatomy of autism spectrum disorder using normative models

International audienceBACKGROUNDThe neuroanatomical basis of autism spectrum disorder (ASD) has remained elusive, mostly owing to high biological and clinical heterogeneity among diagnosed individuals. Despite considerable effort toward understanding ASD using neuroimaging biomarkers, heterogeneity remains a barrier, partly because studies mostly employ case-control approaches, which assume that the clinical group is homogeneous.METHODS:Here, we used an innovative normative modeling approach to parse biological heterogeneity in ASD. We aimed to dissect the neuroanatomy of ASD by mapping the deviations from a typical pattern of neuroanatomical development at the level of the individual and to show the necessity to look beyond the case-control paradigm to understand the neurobiology of ASD. We first estimated a vertexwise normative model of cortical thickness development using Gaussian process regression, then mapped the deviation of each participant from the typical pattern. For this, we employed a heterogeneous cross-sectional sample of 206 typically developing individuals (127 males) and 321 individuals with ASD (232 males) (6-31 years of age).RESULTS:We found few case-control differences, but the ASD cohort showed highly individualized patterns of deviations in cortical thickness that were widespread across the brain. These deviations correlated with severity of repetitive behaviors and social communicative symptoms, although only repetitive behaviors survived corrections for multiple testing.CONCLUSIONS:Our results 1) reinforce the notion that individuals with ASD show distinct, highly individualized trajectories of brain development and 2) show that by focusing on common effects (i.e., the "average ASD participant"), the case-control approach disguises considerable interindividual variation crucial for precision medicine