Improving rotation behaviour of robotic structures for micro-assembly.

International audienceSerial micro-assembly requires high precision robots able to produce translations and rotations to position and orient objects during assembly. In micro-scale, the translation ranges required are typically up to the millimeter and can be obtained with smart devices (piezomotor, etc...). In the other hand, the rotation ranges stay identical to the macroscale (eg. 90°) and require standard guidings like ball bearings which induce disturbances on the linear position. Thus, the ability to produce high precision robots where translations and rotations are découpled is currently one of the major stake in microassembly. This paper deals with an original modeling of the coupling between rotation and linear position. The geometrical model is presented and two calibration methods are discussed. Our method were tested on a 3 DOF planar robotic systems and the coupling was reduced by 93 %

ExPASy: SIB bioinformatics resource portal

ExPASy (http://www.expasy.org) has worldwide reputation as one of the main bioinformatics resources for proteomics. It has now evolved, becoming an extensible and integrative portal accessing many scientific resources, databases and software tools in different areas of life sciences. Scientists can henceforth access seamlessly a wide range of resources in many different domains, such as proteomics, genomics, phylogeny/evolution, systems biology, population genetics, transcriptomics, etc. The individual resources (databases, web-based and downloadable software tools) are hosted in a ‘decentralized' way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions. Specifically, a single web portal provides a common entry point to a wide range of resources developed and operated by different SIB groups and external institutions. The portal features a search function across ‘selected' resources. Additionally, the availability and usage of resources are monitored. The portal is aimed for both expert users and people who are not familiar with a specific domain in life sciences. The new web interface provides, in particular, visual guidance for newcomers to ExPAS

A collaborative model to implement flexible, accessible and efficient oncogenetic services for hereditary breast and ovarian cancer : the C-MOnGene study

Medical genetic services are facing an unprecedented demand for counseling and testing for hereditary breast and ovarian cancer (HBOC) in a context of limited resources. To help resolve this issue, a collaborative oncogenetic model was recently developed and implemented at the CHU de Québec-Université Laval; Quebec; Canada. Here, we present the protocol of the C-MOnGene (Collaborative Model in OncoGenetics) study, funded to examine the context in which the model was implemented and document the lessons that can be learned to optimize the delivery of oncogenetic services. Within three years of implementation, the model allowed researchers to double the annual number of patients seen in genetic counseling. The average number of days between genetic counseling and disclosure of test results significantly decreased. Group counseling sessions improved participants' understanding of breast cancer risk and increased knowledge of breast cancer and genetics and a large majority of them reported to be overwhelmingly satisfied with the process. These quality and performance indicators suggest this oncogenetic model offers a flexible, patient-centered and efficient genetic counseling and testing for HBOC. By identifying the critical facilitating factors and barriers, our study will provide an evidence base for organizations interested in transitioning to an oncogenetic model integrated into oncology care; including teams that are not specialized but are trained in genetics

PaCTS 1.0: a crowdsourced reporting standard for paleoclimate data

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate datasets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new vs. legacy datasets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate datasets. Since such goals are at odds with present practices, we discuss a transparent path towards implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches

L\u27analyse krigeante pour le classement d\u27observations spatiales et multivariées

Lorsque l'ingénieur, le chercheur ... désire classer des observations multivariées, un certain nombre de méthodes statistiques sont mises à sa disposition. Lorsque, en outre, les observations sont disposées dans un espace géographique et que l'information spatiale est riche de sens et doit donc être prise en compte, les méthodes adéquates sont beaucoup moins nombreuses. L'article propose une méthodologie d'analyse pour obtenir des groupes de sites ayant les mêmes caractéristiques. Basée sur les techniques d'analyses de données et de géostatistique elle permet également à l'utilisateur de choisir le niveau de perception (échelle) pour le classement. (Résumé d'auteur