88 research outputs found

    Eric Lenneberg and Motor Control

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    Eric Lenneberg and Motor Control

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    Eric Lenneberg and Motor Control

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    CPU-less robotics: distributed control of biomorphs

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    Traditional robotics revolves around the microprocessor. All well-known demonstrations of sensory guided motor control, such as jugglers and mobile robots, require at least one CPU. Recently, the availability of fast CPUs have made real-time sensory-motor control possible, however, problems with high power consumption and lack of autonomy still remain. In fact, the best examples of real-time robotics are usually tethered or require large batteries. We present a new paradigm for robotics control that uses no explicit CPU. We use computational sensors that are directly interfaced with adaptive actuation units. The units perform motor control and have learning capabilities. This architecture distributes computation over the entire body of the robot, in every sensor and actuator. Clearly, this is similar to biological sensory- motor systems. Some researchers have tried to model the latter in software, again using CPUs. We demonstrate this idea in with an adaptive locomotion controller chip. The locomotory controller for walking, running, swimming and flying animals is based on a Central Pattern Generator (CPG). CPGs are modeled as systems of coupled non-linear oscillators that control muscles responsible for movement. Here we describe an adaptive CPG model, implemented in a custom VLSI chip, which is used to control an under-actuated and asymmetric robotic leg

    CPU-less robotics: distributed control of biomorphs

    Get PDF
    Traditional robotics revolves around the microprocessor. All well-known demonstrations of sensory guided motor control, such as jugglers and mobile robots, require at least one CPU. Recently, the availability of fast CPUs have made real-time sensory-motor control possible, however, problems with high power consumption and lack of autonomy still remain. In fact, the best examples of real-time robotics are usually tethered or require large batteries. We present a new paradigm for robotics control that uses no explicit CPU. We use computational sensors that are directly interfaced with adaptive actuation units. The units perform motor control and have learning capabilities. This architecture distributes computation over the entire body of the robot, in every sensor and actuator. Clearly, this is similar to biological sensory- motor systems. Some researchers have tried to model the latter in software, again using CPUs. We demonstrate this idea in with an adaptive locomotion controller chip. The locomotory controller for walking, running, swimming and flying animals is based on a Central Pattern Generator (CPG). CPGs are modeled as systems of coupled non-linear oscillators that control muscles responsible for movement. Here we describe an adaptive CPG model, implemented in a custom VLSI chip, which is used to control an under-actuated and asymmetric robotic leg

    Random perfect lattices and the sphere packing problem

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    Motivated by the search for best lattice sphere packings in Euclidean spaces of large dimensions we study randomly generated perfect lattices in moderately large dimensions (up to d=19 included). Perfect lattices are relevant in the solution of the problem of lattice sphere packing, because the best lattice packing is a perfect lattice and because they can be generated easily by an algorithm. Their number however grows super-exponentially with the dimension so to get an idea of their properties we propose to study a randomized version of the algorithm and to define a random ensemble with an effective temperature in a way reminiscent of a Monte-Carlo simulation. We therefore study the distribution of packing fractions and kissing numbers of these ensembles and show how as the temperature is decreased the best know packers are easily recovered. We find that, even at infinite temperature, the typical perfect lattices are considerably denser than known families (like A_d and D_d) and we propose two hypotheses between which we cannot distinguish in this paper: one in which they improve Minkowsky's bound phi\sim 2^{-(0.84+-0.06) d}, and a competitor, in which their packing fraction decreases super-exponentially, namely phi\sim d^{-a d} but with a very small coefficient a=0.06+-0.04. We also find properties of the random walk which are suggestive of a glassy system already for moderately small dimensions. We also analyze local structure of network of perfect lattices conjecturing that this is a scale-free network in all dimensions with constant scaling exponent 2.6+-0.1.Comment: 19 pages, 22 figure

    Black hole collision with a scalar particle in three dimensional anti-de Sitter spacetime

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    We study the collision between a BTZ black hole and a test particle coupled to a scalar field. We compute the power spectrum, the energy radiated and the plunging waveforms for this process. We show that for late times the signal is dominated by the quasinormal ringing. In terms of the AdS/CFT correspondence the bulk gravity process maps into a thermal state, an expanding bubble and gauge particles decaying into bosons of the associated operator. These latter thermalize in a timescale predicted by the bulk theory.Comment: 5 pages, 3 figures;minor improvements; references adde

    Can depression be a menopause-associated risk?

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    There is little doubt that women experience a heightened psychiatric morbidity compared to men. A growing body of evidence suggests that, for some women, the menopausal transition and early postmenopausal years may represent a period of vulnerability associated with an increased risk of experiencing symptoms of depression, or for the development of an episode of major depressive disorder. Recent research has begun to shed some light on potential mechanisms that influence this vulnerability. At the same time, a number of studies and clinical trials conducted over the past decade have provided important data regarding efficacy and safety of preventative measures and treatment strategies for midlife women; some of these studies have caused a shift in the current thinking of how menopausal symptoms should be appropriately managed

    The immune gene repertoire encoded in the purple sea urchin genome

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    Echinoderms occupy a critical and largely unexplored phylogenetic vantage point from which to infer both the early evolution of bilaterian immunity and the underpinnings of the vertebrate adaptive immune system. Here we present an initial survey of the purple sea urchin genome for genes associated with immunity. An elaborate repertoire of potential immune receptors, regulators and effectors is present, including unprecedented expansions of innate pathogen recognition genes. These include a diverse array of 222 Toll-like receptor (TLR) genes and a coordinate expansion of directly associated signaling adaptors. Notably, a subset of sea urchin TLR genes encodes receptors with structural characteristics previously identified only in protostomes. A similarly expanded set of 203 NOD/NALP-like cytoplasmic recognition proteins is present. These genes have previously been identified only in vertebrates where they are represented in much lower numbers. Genes that mediate the alternative and lectin complement pathways are described, while gene homologues of the terminal pathway are not present. We have also identified several homologues of genes that function in jawed vertebrate adaptive immunity. The most striking of these is a gene cluster with similarity to the jawed vertebrate Recombination Activating Genes 1 and 2 (RAG1/2). Sea urchins are long-lived, complex organisms and these findings reveal an innate immune system of unprecedented complexity. Whether the presumably intense selective processes that molded these gene families also gave rise to novel immune mechanisms akin to adaptive systems remains to be seen. The genome sequence provides immediate opportunities to apply the advantages of the sea urchin model toward problems in developmental and evolutionary immunobiology

    The Impact of Advocacy Organizations on Low-Income Housing Policy in U.S. Cities

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    Financial support for affordable housing competes with many other municipal priorities. This work seeks to explain the variation in support for affordable housing among U.S. cities with populations of 100,000 or more. Using multivariate statistical analysis, this research investigates political explanations for the level of city expenditures on housing and community with a particular interest in the influence of housing advocacy organizations (AOs). Data for the model were gathered from secondary sources, including the U.S. Census and the National Center for Charitable Statistics. Among other results, the analysis indicates that, on average, the political maturity of AOs has a statistically significant, positive effect on local housing and community development expenditures
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