A K-nearest neighbours method based on imprecise probabilities

K-nearest neighbours algorithms are among the most popular existing classification methods, due to their simplicity and good performances. Over the years, several extensions of the initial method have been proposed. In this paper, we propose a K-nearest neighbours approach that uses the theory of imprecise probabilities, and more specifically lower previsions. We show that the proposed approach has several assets: it can handle uncertain data in a very generic way, and decision rules developed within this theory allow us to deal with conflicting information between neighbours or with the absence of close neighbour to the instance to classify. We show that results of the basic k-NN and weighted k-NN methods can be retrieved by the proposed approach. We end with some experiments on the classical data sets.     

Partitioned and Implicit–Explicit General Linear Methods for Ordinary Differential Equations

Implicit–explicit (IMEX) time stepping methods can efficiently solve differential equations with both stiff and nonstiff components. IMEX Runge–Kutta methods and IMEX linear multistep methods have been studied in the literature. In this paper we study new implicit–explicit methods of general linear type. We develop an order conditions theory for high stage order partitioned general linear methods (GLMs) that share the same abscissae, and show that no additional coupling order conditions are needed. Consequently, GLMs offer an excellent framework for the construction of multi-method integration algorithms. Next, we propose a family of IMEX schemes based on diagonally-implicit multi-stage integration methods and construct practical schemes of order up to three. Numerical results confirm the theoretical findings.     

OCEAN,a flexible adaptive Network-On-Chip for dynamic applications

The dynamic and partial reconfiguration of FPGAs enables the dynamic placement of applicatives tasks in reconfigurable zones. However, the dynamic management of the tasks impacts the communications since they are not present in the FPGA during all computation time. So, the task manager should ensure the allocation of each new task and their interconnection which is performed by a flexible interconnection network. In this article, various interconnection networks are studied. Each architecture is evaluated with respect to its suitability for the paradigm of the dynamic and partial reconfiguration in FPGA implementations. This study leads us to propose the OCEAN network that supports the communication constraints into the context of dynamic reconfigurations. Thanks to a generic platform allowing in situ characterizations of network performances, fair comparisons of various Networks-On-Chip can be realized. The FPGA and ASICs implementations of the OCEAN network are also discussed.     

Ultra-low noise single-photon detector based on Si avalanche photodiode

We report operation and characterization of a lab-assembled single-photon detector based on commercial silicon avalanche photodiodes (PerkinElmer C30902SH, C30921SH). Dark count rate as low as 5 Hz was achieved by cooling the photodiodes down to -80 °C. While afterpulsing increased as the photodiode temperature was decreased, total afterpulse probability did not become significant due to detector's relatively long deadtime in a passively-quenched scheme. We measured photon detection efficiency >50% at 806 nm.     

Generic remeshing of 3D triangular meshes with metric-dependent discrete voronoi diagrams

In this paper, we propose a generic framework for 3D surface remeshing. Based on a metric-driven Discrete Voronoi Diagram construction, our output is an optimized 3D triangular mesh with a user defined vertex budget. Our approach can deal with a wide range of applications, from high quality mesh generation to shape approximation. By using appropriate metric constraints the method generates isotropic or anisotropic elements. Based on point-sampling, our algorithm combines the robustness and theoretical strength of Delaunay criteria with the efficiency of entirely discrete geometry processing . Besides the general described framework, we show experimental results using isotropic, quadric-enhanced isotropic and anisotropic metrics which prove the efficiency of our method on large meshes, for a low computational cost.     

Real-time monitoring of morphological changes in living cells by electronic cell sensor arrays: an approach to study G protein-coupled receptors

G protein-coupled receptors (GPCRs) constitute important targets for drug discovery against a wide range of ailments including cancer, inflammatory, and cardiovascular diseases. Efforts are underway to screen selective modulators of GPCRs and also to deorphanize GPCRs with unidentified natural ligands. Most GPCR-based cellular screens depend on labeling or recombinant expression of receptor or reporter proteins, which may not capture the true physiology or pharmacology of the GPCRs. In this paper, we describe a noninvasive and label-free assay for GPCRs that can be used with both engineered and nonengineered cell lines. The assay is based on using cell-electrode impedance to measure minute changes in cellular morphology as a result of ligand-dependent GPCR activation. We have used this technology to assay the functional activation of GPCRs coupled to different signaling pathways and have compared it to standard assays. We have used pharmacological modulators of GPCR signaling pathways to demonstrate the specificity of impedance-based measurements. Our data indicate that cell-electrode impedance measurements offer a convenient, sensitive, and quantitative method for assessing GPCR function. Moreover, the noninvasive nature of the readout offers the added advantage of performing multiple treatments in the same well to study events such as desensitization and receptor cross-talk.     

Genetic Dissection of Light-Regulated Adventitious Root Induction in Arabidopsis thaliana Hypocotyls

Photomorphogenic responses of etiolated seedlings include the inhibition of hypocotyl elongation and opening of the apical hook. In addition, dark-grown seedlings respond to light by the formation of adventitious roots (AR) on the hypocotyl. How light signaling controls adventitious rooting is less well understood. Hereto, we analyzed adventitious rooting under different light conditions in wild type and photomorphogenesis mutants in Arabidopsis thaliana. Etiolation was not essential for AR formation but raised the competence to form AR under white and blue light. The blue light receptors CRY1 and PHOT1/PHOT2 are key elements contributing to the induction of AR formation in response to light. Furthermore, etiolation-controlled competence for AR formation depended on the COP9 signalosome, E3 ubiquitin ligase CONSTITUTIVELY PHOTOMORPHOGENIC (COP1), the COP1 interacting SUPPRESSOR OF PHYA-105 (SPA) kinase family members (SPA1,2 and 3) and Phytochrome-Interacting Factors (PIF). In contrast, ELONGATED HYPOCOTYL5 (HY5), suppressed AR formation. These findings provide a genetic framework that explains the high and low AR competence of Arabidopsis thaliana hypocotyls that were treated with dark, and light, respectively. We propose that light-induced auxin signal dissipation generates a transient auxin maximum that explains AR induction by a dark to light switch.     

Carbon‐Nanotube–PDMS Composite Coatings on Optical Fibers for All‐Optical Ultrasound Imaging

Polymer–carbon nanotube composite coatings have properties that are desirable for a wide range of applications. However, fabrication of these coatings onto submillimeter structures with the efficient use of nanotubes has been challenging. Polydimethylsiloxane (PDMS)–carbon nanotube composite coatings are of particular interest for optical ultrasound transmission, which shows promise for biomedical imaging and therapeutic applications. In this study, methods for fabricating composite coatings comprising PDMS and multiwalled carbon nanotubes (MWCNTs) with submicrometer thickness are developed and used to coat the distal ends of optical fibers. These methods include creating a MWCNT organogel using two solvents, dip coating of this organogel, and subsequent overcoating with PDMS. These coated fibers are used as all‐optical ultrasound transmitters that achieve high ultrasound pressures (up to 21.5 MPa peak‐to‐peak) and broad frequency bandwidths (up to 39.8 MHz). Their clinical potential is demonstrated with all‐optical pulse‐echo ultrasound imaging of an aorta. The fabrication methods in this paper allow for the creation of thin, uniform carbon nanotube composites on miniature or temperature‐sensitive surfaces, to enable a wide range of advanced sensing capabilities.