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.     

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.     

IL-17A in Human Liver: Significant Source of Inflammation and Trigger of Liver Fibrosis Initiation

IL-17A is considered to guide liver inflammation and fibrosis. From twenty-two human liver samples of different fibrosis stages (F0 to F4), IL-17A, IL-22, and TGFβ1 protein expression in liver tissue lysates were analyzed. Ten paired samples of liver tissue (F0–F1 stage) and blood from the same patient were used to analyze intrahepatic and blood T-lymphoid IL-17A⁺ cells by flow cytometry. The analyses have been performed regardless of pathology, considering the stage of fibrosis. Human liver tissue was used for the primary human liver slice cultures, followed by subsequent cytokine stimulation and fibrotic markers’ analysis by ELISA. IL-17A production in human liver tissue was significantly higher in the early fibrotic stage compared with the advanced stage. Th17 T cells and, to a lesser extent, MAIT cells were the main sources of IL-17A in both compartments, the liver and the blood. Moreover, the presence of liver Th17IL-17A⁺INFγ⁺ cells was detected in the liver. IL-17A stimulation of human liver slice culture increased the expression of profibrotic and pro-inflammatory markers. IL-17A, secreted by Th17 and MAIT cells in the liver, triggered fibrosis by inducing the expression of IL-6 and profibrotic markers and could be a target for antifibrotic treatment. Further amplitude studies are needed to confirm the current results.     

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.     

Planetary exploration by robotic aerovehicles

Planetary aerobots are a new type of telerobotic science platform that can fly and navigate in a dynamic 3-dimensional atmospheric environment, thus enabling the global in situ exploration of planetary atmospheres and surfaces. Aerobots are enabled by a new concept in planetary balloon altitude control, developed at JPL, which employs reversible-fluid changes to permit repeated excursions in altitude. The essential physics and thermodynamics ofreversible-fluid altitude control have been demonstrated in a series of altitude-control experiments conducted in the Earth's atmosphere, which are described. Aerobot altitude-control technology will be important in the exploration of seven planets and satellites in our solar system. Three of these objects—Venus, Mars, and the Saturnian satellite Titan—have accessible solid surfaces and atmospheres dominated by the dense gases nitrogen or carbon dioxide. They will be explored with aerobots using helium or hydrogen as their primary means of buoyancy. The other four planets—Jupiter, Saturn, Uranus, and Neptune—have deep atmospheres that are predominantly hydrogen. It may be possible to explore these atmospheres with aerobots inflated with atmospheric gas that is then radiatively heated from the hotter gaseous depths below. To fulfill their potential, aerobots to explore the planets will need autonomous state estimators to guide their observations and provide information to the altitude-control systems. The techniques of acquiring these data remotely are outlined. Aerobots will also use on board altitude control and navigation systems to execute complex flight paths including descent to the surface and exploiting differential wind velocities to access different latitude belts. Approaches to control of these systems are examined. The application of aerobots to Venus exploration is explored in some detail: The most ambitious mission described, the Venus Flyer Robot (VFR), would have the capability to make repeated short excursions to the high-temperature surface environment of Venus to acquire data and then return to the Earth-like upper atmosphere to communicate and recool its electronic systems. Finally a Planetary Aerobot Testbed is discussed which will conduct Earth atmospheric flights to validate autonomous-state-estimator techniques and flight-path-control techniques needed for future planetary missions.     

Optimization of algal lipid extraction by mixture of ethyl acetate and ethanol via response surface methodology for biodiesel production

The effects of extraction time, extraction temperature, solvent to biomass ratio and solvent composition on lipid yield from lyophilized Chlorococcum sp. biomass using a mixture of ethyl acetate and ethanol (EAE), a new proposed solvent, were studied. Subsequently, the process conditions of extraction by EAE were optimized using Box-Behnken design (BBD). The results revealed that the extraction temperature had the greatest effect on lipid extraction efficiency, followed by volume ratio of ethyl acetate to ethanol (EA/E) and extraction time. The largest lipid extraction yield of 15.74% was obtained under the following extraction conditions: 40mL solvents per gram of biomass for 270 min with gentle stirring at 80 °C by EAE with an EA/E of 1.0. Furthermore, palmitic acid, stearic acid, oleic acid, and linoleic acid were the most abundant fatty acids in the lipids extracted, indicating the great potential of the proposed lipid extraction procedure for microalgae-based biodiesel production.     

Soft Somatosensitive Actuators via Embedded 3D Printing

Humans possess manual dexterity, motor skills, and other physical abilities that rely on feedback provided by the somatosensory system. Herein, a method is reported for creating soft somatosensitive actuators (SSAs) via embedded 3D printing, which are innervated with multiple conductive features that simultaneously enable haptic, proprioceptive, and thermoceptive sensing. This novel manufacturing approach enables the seamless integration of multiple ionically conductive and fluidic features within elastomeric matrices to produce SSAs with the desired bioinspired sensing and actuation capabilities. Each printed sensor is composed of an ionically conductive gel that exhibits both long‐term stability and hysteresis‐free performance. As an exemplar, multiple SSAs are combined into a soft robotic gripper that provides proprioceptive and haptic feedback via embedded curvature, inflation, and contact sensors, including deep and fine touch contact sensors. The multimaterial manufacturing platform enables complex sensing motifs to be easily integrated into soft actuating systems, which is a necessary step toward closed‐loop feedback control of soft robots, machines, and haptic devices.