A Gaussian Approximation of Feature Space for Fast Image Similarity

We introduce a fast technique for the robust computation of image similarity. It builds on a re-interpretation of the recent exemplar-based SVM approach, where a linear SVM is trained at a query point and distance is computed as the dot product with the normal to the separating hyperplane. Although exemplar-based SVM is slow because it requires a new training for each exemplar, the latter approach has shown robustness for image retrieval and object classification, yielding state-of- the-art performance on the PASCAL VOC 2007 detection task despite its simplicity. We re-interpret it by viewing the SVM between a single point and the set of negative examples as the computation of the tangent to the manifold of images at the query. We show that, in a high-dimensional space such as that of image features, all points tend to lie at the periphery and that they are usually separable from the rest of the set. We then use a simple Gaussian approximation to the set of all images in feature space, and fit it by computing the covariance matrix on a large training set. Given the covariance matrix, the computation of the tangent or normal at a point is straightforward and is a simple multiplication by the inverse covariance. This allows us to dramatically speed up image retrieval tasks, going from more than ten minutes to a single second. We further show that our approach is equivalent to feature-space whitening and has links to image saliency

A Dataset of Multi-Illumination Images in the Wild

Collections of images under a single, uncontrolled illumination have enabled the rapid advancement of core computer vision tasks like classification, detection, and segmentation. But even with modern learning techniques, many inverse problems involving lighting and material understanding remain too severely ill-posed to be solved with single-illumination datasets. To fill this gap, we introduce a new multi-illumination dataset of more than 1000 real scenes, each captured under 25 lighting conditions. We demonstrate the richness of this dataset by training state-of-the-art models for three challenging applications: single-image illumination estimation, image relighting, and mixed-illuminant white balance.Comment: ICCV 201

Transform recipes for efficient cloud photo enhancement

Cloud image processing is often proposed as a solution to the limited computing power and battery life of mobile devices: it allows complex algorithms to run on powerful servers with virtually unlimited energy supply. Unfortunately, this overlooks the time and energy cost of uploading the input and downloading the output images. When transfer overhead is accounted for, processing images on a remote server becomes less attractive and many applications do not benefit from cloud offloading. We aim to change this in the case of image enhancements that preserve the overall content of an image. Our key insight is that, in this case, the server can compute and transmit a description of the transformation from input to output, which we call a transform recipe. At equivalent quality, our recipes are much more compact than JPEG images: this reduces the client's download. Furthermore, recipes can be computed from highly compressed inputs which significantly reduces the data uploaded to the server. The client reconstructs a high-fidelity approximation of the output by applying the recipe to its local high-quality input. We demonstrate our results on 168 images and 10 image processing applications, showing that our recipes form a compact representation for a diverse set of image filters. With an equivalent transmission budget, they provide higher-quality results than JPEG-compressed input/output images, with a gain of the order of 10 dB in many cases. We demonstrate the utility of recipes on a mobile phone by profiling the energy consumption and latency for both local and cloud computation: a transform recipe-based pipeline runs 2--4x faster and uses 2--7x less energy than local or naive cloud computation.Qatar Computing Research InstituteUnited States. Defense Advanced Research Projects Agency (Agreement FA8750-14-2-0009)Stanford University. Stanford Pervasive Parallelism LaboratoryAdobe System

Genetic dissection of MHC-associated susceptibility to Lepeophtheirus salmonis in Atlantic salmon

Background: Genetic variation has been shown to play a significant role in determining susceptibility to the salmon louse, Lepeophtheirus salmonis. However, the mechanisms involved in differential response to infection remain poorly understood. Recent findings in Atlantic salmon (Salmo salar) have provided evidence for a potential link between marker variation at the major histocompatibility complex (MHC) and differences in lice abundance among infected siblings, suggesting that MHC genes can modulate susceptibility to the parasite. In this study, we used quantitative trait locus (QTL) analysis to test the effect of genomic regions linked to MHC class I and II on linkage groups (LG) 15 and 6, respectively. Results: Significant QTL effects were detected on both LG 6 and LG 15 in sire-based analysis but the QTL regions remained unresolved due to a lack of recombination between markers. In dam-based analysis, a significant QTL was identified on LG 6, which accounted for 12.9% of within-family variance in lice abundance. However, the QTL was located at the opposite end of DAA, with no significant overlap with the MHC class II region. Interestingly, QTL modelling also revealed evidence of sex-linked differences in lice abundance, indicating that males and females may have different susceptibility to infection. Conclusion: Overall, QTL analysis provided relatively weak support for a proximal effect of classical MHC regions on lice abundance, which can partly be explained by linkage to other genes controlling susceptibility to L. salmonis on the same chromosom

The Nucleosome Remodelling and Deacetylation complex suppresses transcriptional noise during lineage commitment.

Multiprotein chromatin remodelling complexes show remarkable conservation of function amongst metazoans, even though components present in invertebrates are often found as multiple paralogous proteins in vertebrate complexes. In some cases, these paralogues specify distinct biochemical and/or functional activities in vertebrate cells. Here, we set out to define the biochemical and functional diversity encoded by one such group of proteins within the mammalian Nucleosome Remodelling and Deacetylation (NuRD) complex: Mta1, Mta2 and Mta3. We find that, in contrast to what has been described in somatic cells, MTA proteins are not mutually exclusive within embryonic stem (ES) cell NuRD and, despite subtle differences in chromatin binding and biochemical interactions, serve largely redundant functions. ES cells lacking all three MTA proteins exhibit complete NuRD loss of function and are viable, allowing us to identify a previously unreported function for NuRD in reducing transcriptional noise, which is essential for maintaining a proper differentiation trajectory during early stages of lineage commitment.Funding to the BH and MV labs was provided through EU FP7 Integrated Project “4DCellFate” (277899). The BH lab further benefitted from a Wellcome Trust Senior Fellowship (098021/Z/11/Z) and from core funding to the Cambridge Stem Cell Institute from the Wellcome Trust and Medical Research Council (097922/Z/11/Z and 203151/Z/16/Z). The Vermeulen lab is part of the Oncode Institute, which is partly funded by the Dutch Cancer Society (KWF)

Field cricket genome reveals the footprint of recent, abrupt adaptation in the wild.

Evolutionary adaptation is generally thought to occur through incremental mutational steps, but large mutational leaps can occur during its early stages. These are challenging to study in nature due to the difficulty of observing new genetic variants as they arise and spread, but characterizing their genomic dynamics is important for understanding factors favoring rapid adaptation. Here, we report genomic consequences of recent, adaptive song loss in a Hawaiian population of field crickets (Teleogryllus oceanicus). A discrete genetic variant, flatwing, appeared and spread approximately 15 years ago. Flatwing erases sound-producing veins on male wings. These silent flatwing males are protected from a lethal, eavesdropping parasitoid fly. We sequenced, assembled and annotated the cricket genome, produced a linkage map, and identified a flatwing quantitative trait locus covering a large region of the X chromosome. Gene expression profiling showed that flatwing is associated with extensive genome-wide effects on embryonic gene expression. We found that flatwing male crickets express feminized chemical pheromones. This male feminizing effect, on a different sexual signaling modality, is genetically associated with the flatwing genotype. Our findings suggest that the early stages of evolutionary adaptation to extreme pressures can be accompanied by greater genomic and phenotypic disruption than previously appreciated, and highlight how abrupt adaptation might involve suites of traits that arise through pleiotropy or genomic hitchhiking

Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array

Background The genetic architecture of complex traits in farmed animal populations is of interest from a scientific and practical perspective. The use of genetic markers to predict the genetic merit (breeding values) of individuals is commonplace in modern farm animal breeding schemes. Recently, high density SNP arrays have become available for Atlantic salmon, which facilitates genomic prediction and association studies using genome-wide markers and economically important traits. The aims of this study were (i) to use a high density SNP array to investigate the genetic architecture of weight and length in juvenile Atlantic salmon; (ii) to assess the utility of genomic prediction for these traits, including testing different marker densities; (iii) to identify potential candidate genes underpinning variation in early growth. Results A pedigreed population of farmed Atlantic salmon (n = 622) were measured for weight and length traits at one year of age, and genotyped for 111,908 segregating SNP markers using a high density SNP array. The heritability of both traits was estimated using pedigree and genomic relationship matrices, and was comparable at around 0.5 and 0.6 respectively. The results of the GWA analysis pointed to a polygenic genetic architecture, with no SNPs surpassing the genome-wide significance threshold, and one SNP associated with length at the chromosome-wide level. SNPs surpassing an arbitrary threshold of significance (P < 0.005, ~ top 0.5 % of markers) were aligned to an Atlantic salmon reference transcriptome, identifying 109 SNPs in transcribed regions that were annotated by alignment to human, mouse and zebrafish protein databases. Prediction of breeding values was more accurate when applying genomic (GBLUP) than pedigree (PBLUP) relationship matrices (accuracy ~ 0.7 and 0.58 respectively) and 5,000 SNPs were sufficient for obtaining this accuracy increase over PBLUP in this specific population. Conclusions The high density SNP array can effectively capture the additive genetic variation in complex traits. However, the traits of weight and length both appear to be very polygenic with only one SNP surpassing the chromosome-wide threshold. Genomic prediction using the array is effective, leading to an improvement in accuracy compared to pedigree methods, and this improvement can be achieved with only a small subset of the markers in this population. The results have practical relevance for genomic selection in salmon and may also provide insight into variation in the identified genes underpinning body growth and development in salmonid species

The CCAP knowledgebase:Linking protistan and cyanobacterial biological resources with taxonomic and molecular data

Peer reviewedPublisher PD

Design and implementation of the European-Mediterranean Postgraduate Programme on Organ Donation and Transplantation (EMPODaT) for Middle East/North Africa countries

This prospective study reports the design and results obtained after the EMPODaT project implementation. This project was funded by the Tempus programme of the European Commission with the objective to implement a common postgraduate programme on organ donation and transplantation (ODT) in six selected universities from Middle East/North Africa (MENA) countries (Egypt, Lebanon and Morocco). The consortium, coordinated by the University of Barcelona, included universities from Spain, Germany, Sweden and France. The first phase of the project was to perform an analysis of the current situation in the beneficiary countries, including existing training programmes on ODT, Internet connection, digital facilities and competences, training needs, and ODT activity and accreditation requirements. A total of 90 healthcare postgraduate students participated in the 1-year training programme (30 ECTS academic credits). The methodology was based on e-learning modules and face-to-face courses in English and French. Training activities were evaluated through pre- and post-tests, self-assessment activities and evaluation charts. Quality was assessed through questionnaires and semi-structured interviews. The project results on a reproducible and innovative international postgraduate programme, improvement of knowledge, satisfaction of the participants and confirms the need on professionalizing the activity as the cornerstone to ensure organ transplantation self-sufficiency in MENA countries