124 research outputs found

    Choosing choices: Agenda selection with uncertain issues

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    This paper studies selection rules i.e. the procedures committees use to choose whether to place an issue on their agenda. The main ingredient of the model is that committee members are uncertain about their final preferences at the selection stage: they only know the probability that they will eventually prefer the proposal to the status quo at the decision stage. This probability is private information. We find that a more stringent selection rule makes the voters more conservative. Hence individual behavior reinforces the effect of the rule instead of balancing it. For a voter, conditional on being pivotal, the probability that the proposal is adopted depends on which option she eventually favors. The probability that the proposal is adopted if she eventually prefers the proposal increases at a higher rate with the selection rule than if she eventually prefers the status quo. In order to compensate for that, the voters become more selective. The decision rule has the opposite effect. We describe optimal rules when there is a fixed cost of organizing the final election.selection rules ; strategic voting ; asymmetric information ; agenda setting ; large deviations ; petitions ; citizens' initiative

    Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels

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    Supervised learning has recently garnered significant attention in the field of computational physics due to its ability to effectively extract complex patterns for tasks like solving partial differential equations, or predicting material properties. Traditionally, such datasets consist of inputs given as meshes with a large number of nodes representing the problem geometry (seen as graphs), and corresponding outputs obtained with a numerical solver. This means the supervised learning model must be able to handle large and sparse graphs with continuous node attributes. In this work, we focus on Gaussian process regression, for which we introduce the Sliced Wasserstein Weisfeiler-Lehman (SWWL) graph kernel. In contrast to existing graph kernels, the proposed SWWL kernel enjoys positive definiteness and a drastic complexity reduction, which makes it possible to process datasets that were previously impossible to handle. The new kernel is first validated on graph classification for molecular datasets, where the input graphs have a few tens of nodes. The efficiency of the SWWL kernel is then illustrated on graph regression in computational fluid dynamics and solid mechanics, where the input graphs are made up of tens of thousands of nodes

    Design and implementation of a soft-decision decoder for Cortex codes

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    International audienceCortex codes are a family of rate-1/2 self-dual systematic linear block codes with good distance properties. This paper investigates the challenging issue of designing an efficient soft-decision decoder for Cortex codes. A dedicated algorithm is introduced that takes advantage of the particular structure of the code to simplify the decoding. Simulation results show that the proposed algorithm achieves an excellent trade-off between performance and complexity for short Cortex codes. A decoder architecture for the (32,16,8) Cortex code based on the (4,2,2) Hadamard code has been successfully designed and implemented on FPGA device. To our knowledge, this is the first efficient digital implementation of a soft-decision Cortex decoder

    Building a Database of Plant Species for Bioengineering in the Mediterranean context

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    The building of database on mediterranean plants suited for soil and water bioengeneering interventions is presente

    A new variational approach to the stability of gravitational systems

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    We consider the three dimensional gravitational Vlasov Poisson system which describes the mechanical state of a stellar system subject to its own gravity. A well-known conjecture in astrophysics is that the steady state solutions which are nonincreasing functions of their microscopic energy are nonlinearly stable by the flow. This was proved at the linear level by several authors based on the pioneering work by Antonov in 1961. Since then, standard variational techniques based on concentration compactness methods as introduced by P.-L. Lions in 1983 have led to the nonlinear stability of subclasses of stationary solutions of ground state type. In this paper, inspired by pioneering works from the physics litterature (Lynden-Bell 94, Wiechen-Ziegler-Schindler MNRAS 88, Aly MNRAS 89), we use the monotonicity of the Hamiltonian under generalized symmetric rearrangement transformations to prove that non increasing steady solutions are local minimizer of the Hamiltonian under equimeasurable constraints, and extract compactness from suitable minimizing sequences. This implies the nonlinear stability of nonincreasing anisotropic steady states under radially symmetric perturbations

    Genetic and environmental dissection of biomass accumulation in multi-genotype maize canopies

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    International audienceMulti-genotype canopies are frequent in phenotyping experiments and are of increasing interest in agriculture. Radiation interception efficiency (RIE) and radiation use efficiency (RUE) have low heritabilities in such canopies. We propose a revised Monteith equation that identifies environmental and genetic components of RIE and RUE. An environmental term, a component of RIE, characterizes the effect of the presence or absence of neighbours on light interception. The ability of a given plant to compete with its neighbours is then identified, which accounts for the genetic variability of RIE of plants having similar leaf areas. This method was used in three experiments in a phenotyping platform with 765 plants of 255 maize hybrids. As expected, the heritability of the environmental term was near zero, whereas that of the competitiveness term increased with phenological stage, resulting in the identification of quantitative trait loci. In the same way, RUE was dissected as an effect of intercepted light and a genetic term. This approach was used for predicting the behaviour of individual genotypes in virtual multi-genotype canopies. A large effect of competitiveness was observed in multi-genotype but not in single-genotype canopies, resulting in a bias for genotype comparisons in breeding fields

    The RING-CH ligase K5 antagonizes restriction of KSHV and HIV-1 particle release by mediating ubiquitin-dependent endosomal degradation of tetherin

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    Tetherin (CD317/BST2) is an interferon-induced membrane protein that inhibits the release of diverse enveloped viral particles. Several mammalian viruses have evolved countermeasures that inactivate tetherin, with the prototype being the HIV-1 Vpu protein. Here we show that the human herpesvirus Kaposi's sarcoma-associated herpesvirus (KSHV) is sensitive to tetherin restriction and its activity is counteracted by the KSHV encoded RING-CH E3 ubiquitin ligase K5. Tetherin expression in KSHV-infected cells inhibits viral particle release, as does depletion of K5 protein using RNA interference. K5 induces a species-specific downregulation of human tetherin from the cell surface followed by its endosomal degradation. We show that K5 targets a single lysine (K18) in the cytoplasmic tail of tetherin for ubiquitination, leading to relocalization of tetherin to CD63-positive endosomal compartments. Tetherin degradation is dependent on ESCRT-mediated endosomal sorting, but does not require a tyrosine-based sorting signal in the tetherin cytoplasmic tail. Importantly, we also show that the ability of K5 to substitute for Vpu in HIV-1 release is entirely dependent on K18 and the RING-CH domain of K5. By contrast, while Vpu induces ubiquitination of tetherin cytoplasmic tail lysine residues, mutation of these positions has no effect on its antagonism of tetherin function, and residual tetherin is associated with the trans-Golgi network (TGN) in Vpu-expressing cells. Taken together our results demonstrate that K5 is a mechanistically distinct viral countermeasure to tetherin-mediated restriction, and that herpesvirus particle release is sensitive to this mode of antiviral inhibition

    Fiber Optic Sensing System for Temperature and Gas Monitoring in Coal Waste Pile Combustion Environments

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    International audienceIt is presented an optical fiber sensing system projected to operate in the demanding conditions associated with coal waste piles in combustion. Distributed temperature measurement and spot gas sensing are requirements for such a system. A field prototype has been installed and is continuously gathering data, which will input a geological model of the coal waste piles in combustion aiming to understand their dynamics and evolution. Results are presented on distributed temperature and ammonia measurement, being noticed any significant methane emission in the short time period considered. Carbon dioxide is also a targeted gas for measurement, with validated results available soon. The assessment of this technology as an effective and reliable tool to address the problem of monitoring coal waste piles in combustion opens the possibility of its widespread application in view of the worldwide presence of coal related fires
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