29,773 research outputs found

    KLAIM: A Kernel Language for Agents Interaction and Mobility

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    We investigate the issue of designing a kernel programming language for mobile computing and describe KLAIM, a language that supports a programming paradigm where processes, like data, can be moved from one computing environment to another. The language consists of a core Linda with multiple tuple spaces and of a set of operators for building processes. KLAIM naturally supports programming with explicit localities. Localities are first-class data (they can be manipulated like any other data), but the language provides coordination mechanisms to control the interaction protocols among located processes. The formal operational semantics is useful for discussing the design of the language and provides guidelines for implementations. KLAIM is equipped with a type system that statically checks access rights violations of mobile agents. Types are used to describe the intentions (read, write, execute, etc.) of processes in relation to the various localities. The type system is used to determine the operations that processes want to perform at each locality, and to check whether they comply with the declared intentions and whether they have the necessary rights to perform the intended operations at the specific localities. Via a series of examples, we show that many mobile code programming paradigms can be naturally implemented in our kernel language. We also present a prototype implementaton of KLAIM in Java

    Synaptic Wnt/GSK3β Signaling Hub in Autism

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    Indexación: ScopusHundreds of genes have been associated with autism spectrum disorders (ASDs) and the interaction of weak and de novo variants derive from distinct autistic phenotypes thus making up the "spectrum." The convergence of these variants in networks of genes associated with synaptic function warrants the study of cell signaling pathways involved in the regulation of the synapse. The Wnt/β-catenin signaling pathway plays a central role in the development and regulation of the central nervous system and several genes belonging to the cascade have been genetically associated with ASDs. In the present paper, we review basic information regarding the role of Wnt/β-catenin signaling in excitatory/inhibitory balance (E/I balance) through the regulation of pre-and postsynaptic compartments. Furthermore, we integrate information supporting the role of the glycogen synthase kinase 3β (GSK3β) in the onset/development of ASDs through direct modulation of Wnt/β-catenin signaling. Finally, given GSK3β activity as key modulator of synaptic plasticity, we explore the potential of this kinase as a therapeutic target for ASD.https://www.hindawi.com/journals/np/2016/9603751

    Optimizing Neural Architecture Search using Limited GPU Time in a Dynamic Search Space: A Gene Expression Programming Approach

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    Efficient identification of people and objects, segmentation of regions of interest and extraction of relevant data in images, texts, audios and videos are evolving considerably in these past years, which deep learning methods, combined with recent improvements in computational resources, contributed greatly for this achievement. Although its outstanding potential, development of efficient architectures and modules requires expert knowledge and amount of resource time available. In this paper, we propose an evolutionary-based neural architecture search approach for efficient discovery of convolutional models in a dynamic search space, within only 24 GPU hours. With its efficient search environment and phenotype representation, Gene Expression Programming is adapted for network's cell generation. Despite having limited GPU resource time and broad search space, our proposal achieved similar state-of-the-art to manually-designed convolutional networks and also NAS-generated ones, even beating similar constrained evolutionary-based NAS works. The best cells in different runs achieved stable results, with a mean error of 2.82% in CIFAR-10 dataset (which the best model achieved an error of 2.67%) and 18.83% for CIFAR-100 (best model with 18.16%). For ImageNet in the mobile setting, our best model achieved top-1 and top-5 errors of 29.51% and 10.37%, respectively. Although evolutionary-based NAS works were reported to require a considerable amount of GPU time for architecture search, our approach obtained promising results in little time, encouraging further experiments in evolutionary-based NAS, for search and network representation improvements.Comment: Accepted for presentation at the IEEE Congress on Evolutionary Computation (IEEE CEC) 202

    Perron's solutions for two-phase free boundary problems with distributed sources

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    We use Perron method to construct a weak solution to a two-phase free boundary problem with right-hand-side. We thus extend the results of the pioneer work of Caffarelli for the homogeneous case

    Central Limit Theorem for a Tagged Particle in Asymmetric Simple Exclusion

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    We prove a Functional Central Limit Theorem for the position of a Tagged Particle in the one-dimensional Asymmetric Simple Exclusion Process in the hyperbolic scaling, starting from a Bernoulli product measure conditioned to have a particle at the origin. We also prove that the position of the Tagged Particle at time tt depends on the initial configuration, by the number of empty sites in the interval [0,(p−q)αt][0,(p-q)\alpha t] divided by α\alpha in the hyperbolic and in a longer time scale, namely N4/3N^{4/3}.Comment: 28 pages, no figure

    Symmetric simple exclusion process with free boundaries

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    We consider the one dimensional symmetric simple exclusion process (SSEP) with additional births and deaths restricted to a subset of configurations where there is a leftmost hole and a rightmost particle. At a fixed rate birth of particles occur at the position of the leftmost hole and at the same rate, independently, the rightmost particle dies. We prove convergence to a hydrodynamic limit and discuss its relation with a free boundary problem.Comment: 29 pages, 4 figure
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