Analog-to-digital conversion system Patent

Conversion system for increasing resolution of analog to digital converter

Jet-hadron correlations relative to the event plane at the LHC with ALICE

The hot, dense and strongly interacting medium known as the Quark Gluon Plasma (QGP) is produced in relativistic heavy-ion collisions at the Large Hadron Collider (LHC). Early in the collisions, quarks and gluons from the incoming nuclei collide to produce high momentum partons which fragment into collimated sprays of hadrons called "jets". In pp collisions, jet production is well understood within the framework of perturbative QCD and acts as a rigorous baseline measurement for jet quenching measurements. Using pp as a reference, we can compare to heavy-ion collision systems, and study the modification of the $p_{T}$ or angular distributions of jet fragments. A recently developed background subtraction method to remove the complex, flow dominated, heavy-ion background will be used in this analysis. Azimuthal angular correlations of charged hadrons with respect to the axis of a full (charged + neutral) reconstructed 'trigger' jet in Pb--Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV in ALICE will be presented here. The analysis of angular correlations for different orientations of the trigger relative to the event plane allows for the study of the path length dependence of medium modifications to jets. The status of studies of the event plane dependence of angular correlations will be presented.Comment: 4 pages, 4 figures, Hot Quarks 2016 conferenc

Topological solution of bilateral switching networks

Topological method uses the eye as pattern detector to trace path of transmission on truth table. Pathway selection is continually supervised by logician, allowing him to seek planar iterative solution desirable for fabrication of monolithic circuits. Method applies to parity generators, multiple output functions, full adders, and bit comparators

Heteranthery in Clarkia: pollen performance of dimorphic anthers contradicts expectations.

Premise of the studyWild plant species that require the services of pollen-feeding insects for reliable pollination may evolve features that attract and reward their mutualistic partners. Heterantherous species have been proposed to exhibit a "division of labor" whereby "feeding anthers" (which produce pollen that may be consumed by an insect) are distinguished from "reproductive anthers" (which produce pollen more likely to contribute to reproduction). In some heterantherous species, including Clarkia unguiculata (Onagraceae), these two anther types differ with respect to stamen length, anther size, pollen production, and pollen color.MethodsThe primary goal of this study was to test one component of the "division of labor" hypothesis by comparing the performance of the pollen produced by each type of anther in C. unguiculata. To achieve this goal, under greenhouse conditions, we hand pollinated and assessed pollen performance (using epifluorescence microscopy) within ~228 flowers.Key resultsThe pollen produced by the two anther types differed significantly with respect to both stigma and style penetration. The inner series of anthers produce pollen with higher performance than the outer series of longer, dark red anthers.ConclusionsThese findings contradict previous descriptions of the genus, reporting that the inner diminutive series of anthers in Clarkia produce "abortive and nonfunctional" pollen. We outline the future research required to demonstrate the ecological function of heteranthery in this iconic wildflower group

The Ariadne's Clew Algorithm

We present a new approach to path planning, called the "Ariadne's clew algorithm". It is designed to find paths in high-dimensional continuous spaces and applies to robots with many degrees of freedom in static, as well as dynamic environments - ones where obstacles may move. The Ariadne's clew algorithm comprises two sub-algorithms, called Search and Explore, applied in an interleaved manner. Explore builds a representation of the accessible space while Search looks for the target. Both are posed as optimization problems. We describe a real implementation of the algorithm to plan paths for a six degrees of freedom arm in a dynamic environment where another six degrees of freedom arm is used as a moving obstacle. Experimental results show that a path is found in about one second without any pre-processing

Using Bayesian Programming for Multisensor Multi-Target Tracking in Automative Applications

A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. Carsense is a European project whose purpose is to develop such a new sensing system. It will combine different sensors (laser, radar and video) and will rely on the fusion of the information coming from these sensors in order to achieve better accuracy, robustness and an increase of the information content. This paper demonstrates the interest of using probabilistic reasoning techniques to address this challenging multi-sensor data fusion problem. The approach used is called Bayesian Programming. It is a general approach based on an implementation of the Bayesian theory. It was introduced rst to design robot control programs but its scope of application is much broader and it can be used whenever one has to deal with problems involving uncertain or incomplete knowledge

Obstacle Avoidance and Proscriptive Bayesian Programming

Unexpected events and not modeled properties of the robot environment are some of the challenges presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a probabilistic approach called Bayesian Programming, which aims to deal with the uncertainty, imprecision and incompleteness of the information handled to solve the obstacle avoidance problem. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. A video illustration of the developed experiments can be found at http://www.inrialpes.fr/sharp/pub/laplac

Bayesian robot Programming

We propose a new method to program robots based on Bayesian inference and learning. The capacities of this programming method are demonstrated through a succession of increasingly complex experiments. Starting from the learning of simple reactive behaviors, we present instances of behavior combinations, sensor fusion, hierarchical behavior composition, situation recognition and temporal sequencing. This series of experiments comprises the steps in the incremental development of a complex robot program. The advantages and drawbacks of this approach are discussed along with these different experiments and summed up as a conclusion. These different robotics programs may be seen as an illustration of probabilistic programming applicable whenever one must deal with problems based on uncertain or incomplete knowledge. The scope of possible applications is obviously much broader than robotics