Atlas des fermes et villae gallo-romaines de Beauce

2018, était la troisième et dernière année de notre PCR. Le travail s’est poursuivi sur son rythme de croisière. Au cours de cette année 2018, 106 notices ont été ajoutées au corpus, essentiellement issues de l’archéologie aérienne, pour les départements de l’Eure-et-Loir, du Loiret et de l’Essonne. Rémi Ossant et Olivier Marlet ont poursuivi la mise en place du site internet, travail qui a abouti à sa mise en ligne sur la plateforme Huma-Num AERBA. Fig. 1 – Carte des sites en fonction de leu..

Hyperspectral images segmentation: a proposal

Hyper-Spectral Imaging (HIS) also known as chemical or spectroscopic imaging is an emerging technique that combines imaging and spectroscopy to capture both spectral and spatial information from an object. Hyperspectral images are made up of contiguous wavebands in a given spectral band. These images provide information on the chemical make-up profile of objects, thus allowing the differentiation of objects of the same colour but which possess make-up profile. Yet, whatever the application field, most of the methods devoted to HIS processing conduct data analysis without taking into account spatial information.Pixels are processed individually, as an array of spectral data without any spatial structure. Standard classification approaches are thus widely used (k-means, fuzzy-c-means hierarchical classification...). Linear modelling methods such as Partial Least Square analysis (PLS) or non linear approaches like support vector machine (SVM) are also used at different scales (remote sensing or laboratory applications). However, with the development of high resolution sensors, coupled exploitation of spectral and spatial information to process complex images, would appear to be a very relevant approach. However, few methods are proposed in the litterature. The most recent approaches can be broadly classified in two main categories. The first ones are related to a direct extension of individual pixel classification methods using just the spectral dimension (k-means, fuzzy-c-means or FCM, Support Vector Machine or SVM). Spatial dimension is integrated as an additionnal classification parameter (Markov fields with local homogeneity constrainst [5], Support Vector Machine or SVM with spectral and spatial kernels combination [2], geometrically guided fuzzy C-means [3]...). The second ones combine the two fields related to each dimension (spectral and spatial), namely chemometric and image analysis. Various strategies have been attempted. The first one is to rely on chemometrics methods (Principal Component Analysis or PCA, Independant Component Analysis or ICA, Curvilinear Component Analysis...) to reduce the spectral dimension and then to apply standard images processing technics on the resulting score images i.e. data projection on a subspace. Another approach is to extend the definition of basic image processing operators to this new dimensionality (morphological operators for example [1, 4]). However, the approaches mentioned above tend to favour only one description either directly or indirectly (spectral or spatial). The purpose of this paper is to propose a hyperspectral processing approach that strikes a better balance in the treatment of both kinds of information....Cet article présente une stratégie de segmentation d’images hyperspectrales liant de façon symétrique et conjointe les aspects spectraux et spatiaux. Pour cela, nous proposons de construire des variables latentes permettant de définir un sous-espace représentant au mieux la topologie de l’image. Dans cet article, nous limiterons cette notion de topologie à la seule appartenance aux régions. Pour ce faire, nous utilisons d’une part les notions de l’analyse discriminante (variance intra, inter) et les propriétés des algorithmes de segmentation en région liées à celles-ci. Le principe générique théorique est exposé puis décliné sous la forme d’un exemple d’implémentation optimisé utilisant un algorithme de segmentation en région type split and merge. Les résultats obtenus sur une image de synthèse puis réelle sont exposés et commentés

Development of a Pacific oyster (Crassostrea gigas) 31,918-feature microarray: identification of reference genes and tissue-enriched expression patterns

Background: Research using the Pacific oyster Crassostrea gigas as a model organism has experienced rapid growth in recent years due to the development of high-throughput molecular technologies. As many as 56,268 EST sequences have been sequenced to date, representing a genome-wide resource that can be used for transcriptomic investigations. Results: In this paper, we developed a Pacific oyster microarray containing oligonucleotides representing 31,918 transcribed sequences selected from the publicly accessible GigasDatabase. This newly designed microarray was used to study the transcriptome of male and female gonads, mantle, gills, posterior adductor muscle, visceral ganglia, hemocytes, labial palps and digestive gland. Statistical analyses identified genes differentially expressed among tissues and clusters of tissue-enriched genes. These genes reflect major tissue-specific functions at the molecular level, such as tissue formation in the mantle, filtering in the gills and labial palps, and reproduction in the gonads. Hierarchical clustering predicted the involvement of unannotated genes in specific functional pathways such as the insulin/NPY pathway, an important pathway under study in our model species. Microarray data also accurately identified reference genes whose mRNA level appeared stable across all the analyzed tissues. Adp-ribosylation factor 1 9arf1) appeared to be the most robust reference for normalizing gene expression data across different tissues and is therefore proposed as a relevant reference gene for further gene expression analysis in the Pacific oyster. Conclusions: This study provides a new transcriptomic tool for studies of oyster biology, which will help in the annotation of its genome and which identifies candidate reference genes for gene expression analysis

Comparison of the capacity factor of stationary wind turbines and weather-routed energy ships in the far-offshore

International audienceOffshore wind energy technology has developed rapidly over the last decade. It is expected to significantly contribute to the further increase of renewable energy in the global energy production in the future. However, even with floating wind turbines, only a fraction of the global offshore wind energy potential can be harvested because grid-connection, moorings, installation and maintenance costs increase tremendously as the distance to shore and the water depth increase. Thus, new technologies enabling harvesting the far offshore wind energy resource are required. To tackle this challenge, mobile energy ship concepts have been proposed. In those concepts, electricity is produced by a water turbine attached underneath the hull of a ship propelled by the wind using sails. It includes an on-board energy storage system since energy ships are not grid-connected. Thus, the ships route schedules could be dynamically optimized taking into account weather forecast in order to maximize their capacity factors (CF). The aim of this study is to investigate how high the capacity factors of energy ships could be when using weather-routing and compare them to that of stationary wind turbines that would be deployed in the same areas. To that end, a modified version of the weather-routing software QtVlm was used. Velocity and power production polar plots of an energy ship that was designed at LHEEA were used as input to QtVlm. Results show that capacity factors over 80% can be achieved with energy ships and stationary offshore wind turbines deployed in the North Atlantic Ocean

Hyperspectral image segmentation: the butterfly approach

International audienceFew methods are proposed in the litterature for coupling the spectral and the spatial dimension available on hyperspectral images. This paper proposes a generic segmentation scheme named butterfly based on an iterative process and a cross analysis of spectral and spatial information. Indeed, spatial and spatial structures are extracted in spatial and spectral space respectively both taking into account the other one. To apply this layout on hyperspectral imgages, we focus particulary on spatial and spectral structures i.e. topologic concepts and latent variable for the spatial and the spectral space respectively. Moreover, a cooperation scheme with these structures is proposed. Finally, results obtained on real hyperspectral images using this specific implementation of the butterfly approach are presented and discussed

Robust adaptive numerical integration of irregular functions with applications to basket and other multi-dimensional exotic options

International audienceWe improve an adaptive integration algorithm proposed by two of the authors by introducing a new splitting strategy based on a geometrical criterion. This algorithm is tested especially on the pricing of multidimensional vanilla options in the Black–Scholes framework which emphasizes the numerical problems of integrating non-smooth functions. In high dimensions, this new algorithm is used as a control variate after a dimension reduction based on principal component analysis. Numerical tests are performed on the Genz package, on the pricing of basket, put on minimum and digital options in dimensions up to ten

Generation and analysis of a 29,745 unique Expressed Sequence Tags from the Pacific oyster (Crassostrea gigas) assembled into a publicly accessible database: the GigasDatabase

Background: Although bivalves are among the most-studied marine organisms because of their ecological role and economic importance, very little information is available on the genome sequences of oyster species. This report documents three large-scale cDNA sequencing projects for the Pacific oyster Crassostrea gigas initiated to provide a large number of expressed sequence tags that were subsequently compiled in a publicly accessible database. This resource allowed for the identification of a large number of transcripts and provides valuable information for ongoing investigations of tissue-specific and stimulus-dependant gene expression patterns. These data are crucial for constructing comprehensive DNA microarrays, identifying single nucleotide polymorphisms and microsatellites in coding regions, and for identifying genes when the entire genome sequence of C. gigas becomes available. Description: In the present paper, we report the production of 40,845 high-quality ESTs that identify 29,745 unique transcribed sequences consisting of 7,940 contigs and 21,805 singletons. All of these new sequences, together with existing public sequence data, have been compiled into a publicly-available Website http://public-contigbrowser.sigenae.org:9090/Crassostrea_gigas/index.htm l. Approximately 43% of the unique ESTs had significant matches against the SwissProt database and 27% were annotated using Gene Ontology terms. In addition, we identified a total of 208 in silico microsatellites from the ESTs, with 173 having sufficient flanking sequence for primer design. We also identified a total of 7,530 putative in silico, single-nucleotide polymorphisms using existing and newly-generated EST resources for the Pacific oyster. Conclusion: A publicly-available database has been populated with 29,745 unique sequences for the Pacific oyster Crassostrea gigas. The database provides many tools to search cleaned and assembled ESTs. The user may input and submit several filters, such as protein or nucleotide hits, to select and download relevant elements. This database constitutes one of the most developed genomic resources accessible among Lophotrochozoans, an orphan clade of bilateral animals. These data will accelerate the development of both genomics and genetics in a commercially-important species with the highest annual, commercial production of any aquatic organism

Gametogenesis in the Pacific Oyster Crassostrea gigas: A Microarrays-Based Analysis Identifies Sex and Stage Specific Genes

Background: The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa) is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011) representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. Methodology/Principal Findings: Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters. Conclusions/Significance: This study allowed us to identify potential markers of early sex differentiation in the oyster C. gigas, an alternative hermaphrodite mollusk. We also provided new highly valuable information on genes specifically expressed by mature spermatozoids and mature oocytes