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Legeai F.,Campus University Of Beaulieu | Malpel S.,French National Institute for Agricultural Research | Malpel S.,University of Burgundy | Montagne N.,French National Institute for Agricultural Research | And 9 more authors.
BMC Genomics | Year: 2011

Background: Nocturnal insects such as moths are ideal models to study the molecular bases of olfaction that they use, among examples, for the detection of mating partners and host plants. Knowing how an odour generates a neuronal signal in insect antennae is crucial for understanding the physiological bases of olfaction, and also could lead to the identification of original targets for the development of olfactory-based control strategies against herbivorous moth pests. Here, we describe an Expressed Sequence Tag (EST) project to characterize the antennal transcriptome of the noctuid pest model, Spodoptera littoralis, and to identify candidate genes involved in odour/pheromone detection.Results: By targeting cDNAs from male antennae, we biased gene discovery towards genes potentially involved in male olfaction, including pheromone reception. A total of 20760 ESTs were obtained from a normalized library and were assembled in 9033 unigenes. 6530 were annotated based on BLAST analyses and gene prediction software identified 6738 ORFs. The unigenes were compared to the Bombyx mori proteome and to ESTs derived from Lepidoptera transcriptome projects. We identified a large number of candidate genes involved in odour and pheromone detection and turnover, including 31 candidate chemosensory receptor genes, but also genes potentially involved in olfactory modulation.Conclusions: Our project has generated a large collection of antennal transcripts from a Lepidoptera. The normalization process, allowing enrichment in low abundant genes, proved to be particularly relevant to identify chemosensory receptors in a species for which no genomic data are available. Our results also suggest that olfactory modulation can take place at the level of the antennae itself. These EST resources will be invaluable for exploring the mechanisms of olfaction and pheromone detection in S. littoralis, and for ultimately identifying original targets to fight against moth herbivorous pests. © 2011 Legeai et al; licensee BioMed Central Ltd.

Shen L.,Shanghai University | Zhang Z.,Shanghai University | Liu Z.,Shanghai University | Liu Z.,Campus University Of Beaulieu
IEEE Transactions on Circuits and Systems for Video Technology | Year: 2014

High Efficiency Video Coding (HEVC) adopts the quadtree structured coding unit (CU), which allows recursive splitting into four equally sized blocks. At each depth level, it enables SKIP mode, merge mode, inter 2N × 2 N, inter 2N × N, inter N × 2 N, inter 2N × nU, inter 2N × nD, inter nL × N, inter nR × N, inter N × N (only available for the smallest CU), intra 2N × N, and intra N × N (only available for the smallest CU) in inter-frames. Similar to H.264/AVC, the mode decision process in HEVC is performed using all the possible depth levels (or CU sizes) and prediction modes to find the one with the least rate distortion (RD) cost using Lagrange multiplier. This achieves the highest coding efficiency, but leads to a very high computational complexity. Since the optimal prediction mode is highly content dependent, it is not efficient to use all the modes. In this paper, we propose a fast inter-mode decision algorithm for HEVC by jointly using the inter-level correlation of quadtree structure and the spatiotemporal correlation. There exist strong correlations of the prediction mode, the motion vector and RD cost between different depth levels and between spatially temporally adjacent CUs. We statistically analyze the prediction mode distribution at each depth level and the coding information correlation among the adjacent CUs. Based on the analysis results, three adaptive inter-mode decision strategies are proposed including early SKIP mode decision, prediction size correlation-based mode decision and RD cost correlation-based mode decision. Experimental results show that the proposed overall algorithm can save 49%-52% computational complexity on average with negligible loss of coding efficiency, exhibiting applicability to various types of video sequences. © 1991-2012 IEEE.

Tudoran R.,Campus University Of Beaulieu | Costan A.,INSA Rennes | Nano O.,Microsoft | Santos I.,Microsoft | And 2 more authors.
Future Generation Computer Systems | Year: 2016

Scientific and commercial applications operate nowadays on tens of cloud datacenters around the globe, following similar patterns: they aggregate monitoring or sensor data, assess the QoS or run global data mining queries based on inter-site event stream processing. Enabling fast data transfers across geographically distributed sites allows such applications to manage the continuous streams of events in real time and quickly react to changes. However, traditional event processing engines often consider data resources as second-class citizens and support access to data only as a side-effect of computation (i.e. they are not concerned by the transfer of events from their source to the processing site). This is an efficient approach as long as the processing is executed in a single cluster where nodes are interconnected by low latency networks. In a distributed environment, consisting of multiple datacenters, with orders of magnitude differences in capabilities and connected by a WAN, this will undoubtedly lead to significant latency and performance variations. This is namely the challenge we address in this paper, by proposing JetStream, a high performance batch-based streaming middleware for efficient transfers of events between cloud datacenters. JetStream is able to self-adapt to the streaming conditions by modeling and monitoring a set of context parameters. It further aggregates the available bandwidth by enabling multi-route streaming across cloud sites, while at the same time optimizing resource utilization and increasing cost efficiency. The prototype was validated on tens of nodes from US and Europe datacenters of the Windows Azure cloud with synthetic benchmarks and a real-life application monitoring the ALICE experiment at CERN. The results show a 3× increase of the transfer rate using the adaptive multi-route streaming, compared to state of the art solutions. © 2015 Elsevier B.V. All rights reserved.

Liu Z.,Shanghai University | Liu Z.,Campus University Of Beaulieu | Zou W.,INSA Rennes | Li L.,Shanghai University | And 2 more authors.
IEEE Signal Processing Letters | Year: 2014

Co-saliency detection, an emerging and interesting issue in saliency detection, aims to discover the common salient objects in a set of images. This letter proposes a hierarchical segmentation based co-saliency model. On the basis of fine segmentation, regional histograms are used to measure regional similarities between region pairs in the image set, and regional contrasts within each image are exploited to evaluate the intra-saliency of each region. On the basis of coarse segmentation, an object prior for each region is measured based on the connectivity with image borders. Finally, the global similarity of each region is derived based on regional similarity measures, and then effectively integrated with intra-saliency map and object prior map to generate the co-saliency map for each image. Experimental results on two benchmark datasets demonstrate the better co-saliency detection performance of the proposed model compared to the state-of-the-art co-saliency models. © 2013 IEEE.

Poivet E.,French National Institute for Agricultural Research | Gallot A.,French National Institute for Agricultural Research | Gallot A.,Campus University Of Beaulieu | Montagne N.,University Pierre and Marie Curie | And 3 more authors.
PLoS ONE | Year: 2013

To better understand the olfactory mechanisms in a lepidopteran pest model species, the cotton leafworm Spodoptera littoralis, we have recently established a partial transcriptome from adult antennae. Here, we completed this transcriptome using next generation sequencing technologies, namely 454 and Illumina, on both adult antennae and larval tissues, including caterpillar antennae and maxillary palps. All sequences were assembled in 77,643 contigs. Their analysis greatly enriched the repertoire of chemosensory genes in this species, with a total of 57 candidate odorant-binding and chemosensory proteins, 47 olfactory receptors, 6 gustatory receptors and 17 ionotropic receptors. Using RT-PCR, we conducted the first exhaustive comparison of olfactory gene expression between larvae and adults in a lepidopteran species. All the 127 candidate olfactory genes were profiled for expression in male and female adult antennae and in caterpillar antennae and maxillary palps. We found that caterpillars expressed a smaller set of olfactory genes than adults, with a large overlap between these two developmental stages. Two binding proteins appeared to be larvae-specific and two others were adult-specific. Interestingly, comparison between caterpillar antennae and maxillary palps revealed numerous organ-specific transcripts, suggesting the complementary involvement of these two organs in larval chemosensory detection. Adult males and females shared the same set of olfactory transcripts, except two male-specific candidate pheromone receptors, two male-specific and two female-specific odorant-binding proteins. This study identified transcripts that may be important for sex-specific or developmental stage-specific chemosensory behaviors. © 2013 Poivet et al.

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