998 resultados para 13368-014


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The purpose of this project is the creation of a graphical "programming" interface for a sensor network tasking language called STEP. The graphical interface allows the user to specify a program execution graphically from an extensible pallet of functionalities and save the results as a properly formatted STEP file. Moreover, the software is able to load a file in STEP format and convert it into the corresponding graphical representation. During both phases a type-checker is running on the background to ensure that both the graphical representation and the STEP file are syntactically correct. This project has been motivated by the Sensorium project at Boston University. In this technical report we present the basic features of the software, the process that has been followed during the design and implementation. Finally, we describe the approach used to test and validate our software.

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The combinatorial Dirichlet problem is formulated, and an algorithm for solving it is presented. This provides an effective method for interpolating missing data on weighted graphs of arbitrary connectivity. Image processing examples are shown, and the relation to anistropic diffusion is discussed.

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Under natural viewing conditions small movements of the eye, head, and body prevent the maintenance of a steady direction of gaze. It is known that stimuli tend to fade when they a restabilized on the retina for several seconds. However; it is unclear whether the physiological motion of the retinal image serves a visual purpose during the brief periods of natural visual fixation. This study examines the impact of fixational instability on the statistics of the visua1 input to the retina and on the structure of neural activity in the early visual system. We show that fixational instability introduces a component in the retinal input signals that in the presence of natural images, lacks spatial correlations. This component strongly influences neural activity in a model of the LGN. It decorrelates cell responses even if the contrast sensitivity functions of simulated cells arc not perfectly tuned to counterbalance the power-law spectrum of natural images. A decorrelation of neural activity at the early stages of the visual system has been proposed to be beneficial for discarding statistical redundancies in the input signals. The results of this study suggest that fixational instability might contribute to establishing efficient representations of natural stimuli.

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When brain mechanism carry out motion integration and segmentation processes that compute unambiguous global motion percepts from ambiguous local motion signals? Consider, for example, a deer running at variable speeds behind forest cover. The forest cover is an occluder that creates apertures through which fragments of the deer's motion signals are intermittently experienced. The brain coherently groups these fragments into a trackable percept of the deer in its trajectory. Form and motion processes are needed to accomplish this using feedforward and feedback interactions both within and across cortical processing streams. All the cortical areas V1, V2, MT, and MST are involved in these interactions. Figure-ground processes in the form stream through V2, such as the seperation of occluding boundaries of the forest cover from the boundaries of the deer, select the motion signals which determine global object motion percepts in the motion stream through MT. Sparse, but unambiguous, feauture tracking signals are amplified before they propogate across position and are intergrated with far more numerous ambiguous motion signals. Figure-ground and integration processes together determine the global percept. A neural model predicts the processing stages that embody these form and motion interactions. Model concepts and data are summarized about motion grouping across apertures in response to a wide variety of displays, and probabilistic decision making in parietal cortex in response to random dot displays.

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A nonparametric probability estimation procedure using the fuzzy ARTMAP neural network is here described. Because the procedure does not make a priori assumptions about underlying probability distributions, it yields accurate estimates on a wide variety of prediction tasks. Fuzzy ARTMAP is used to perform probability estimation in two different modes. In a 'slow-learning' mode, input-output associations change slowly, with the strength of each association computing a conditional probability estimate. In 'max-nodes' mode, a fixed number of categories are coded during an initial fast learning interval, and weights are then tuned by slow learning. Simulations illustrate system performance on tasks in which various numbers of clusters in the set of input vectors mapped to a given class.

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Working memory neural networks are characterized which encode the invariant temporal order of sequential events. Inputs to the networks, called Sustained Temporal Order REcurrent (STORE) models, may be presented at widely differing speeds, durations, and interstimulus intervals. The STORE temporal order code is designed to enable all emergent groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system. Such a competence is needed in neural architectures which self-organize learned codes for variable-rate speech perception, sensory-motor planning, or 3-D visual object recognition. Using such a working memory, a self-organizing architecture for invariant 3-D visual object recognition is described. The new model is based on the model of Seibert and Waxman (1990a), which builds a 3-D representation of an object from a temporally ordered sequence of its 2-D aspect graphs. The new model, called an ARTSTORE model, consists of the following cascade of processing modules: Invariant Preprocessor --> ART 2 --> STORE Model --> ART 2 --> Outstar Network.

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This paper studies several applications of genetic algorithms (GAs) within the neural networks field. After generating a robust GA engine, the system was used to generate neural network circuit architectures. This was accomplished by using the GA to determine the weights in a fully interconnected network. The importance of the internal genetic representation was shown by testing different approaches. The effects in speed of optimization of varying the constraints imposed upon the desired network were also studied. It was observed that relatively loose constraints provided results comparable to a fully constrained system. The type of neural network circuits generated were recurrent competitive fields as described by Grossberg (1982).

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Recent years have witnessed a rapid growth in the demand for streaming video over the Internet and mobile networks, exposes challenges in coping with heterogeneous devices and varying network throughput. Adaptive schemes, such as scalable video coding, are an attractive solution but fare badly in the presence of packet losses. Techniques that use description-based streaming models, such as multiple description coding (MDC), are more suitable for lossy networks, and can mitigate the effects of packet loss by increasing the error resilience of the encoded stream, but with an increased transmission byte cost. In this paper, we present our adaptive scalable streaming technique adaptive layer distribution (ALD). ALD is a novel scalable media delivery technique that optimises the tradeoff between streaming bandwidth and error resiliency. ALD is based on the principle of layer distribution, in which the critical stream data are spread amongst all packets, thus lessening the impact on quality due to network losses. Additionally, ALD provides a parameterised mechanism for dynamic adaptation of the resiliency of the scalable video. The Subjective testing results illustrate that our techniques and models were able to provide levels of consistent high-quality viewing, with lower transmission cost, relative to MDC, irrespective of clip type. This highlights the benefits of selective packetisation in addition to intuitive encoding and transmission.

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The potential value of baseline health-related quality-of-life (HRQOL) and clinical factors in predicting prognosis was examined using data from an international randomised phase III trial which compared doxorubicin and paclitaxel with doxorubicin and cylophosphamide as first line chemotherapy in 275 women with metastatic breast cancer. The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 and the related breast module (QLQ-BR23) were used to assess baseline HRQOL data. The Cox proportional-hazards regression model was used for both univariate and multivariate analyses of survival. In the univariate analyses, performance status (P<0.001) and number of sites involved (P=0.001) were the most important clinical prognostic factors. The HRQOL variables at baseline most strongly associated with longer survival were better appetite, physical and role functioning, as well as less fatigue (P<0.001). The final multivariate model retained performance status (P<0.001) and appetite loss (P=0.005) as the variables best predicting survival. Substantial loss of appetite was the only independent HRQOL factor predicting poor survival and was strongly correlated (/r/>0.5) with fatigue, role and physical functioning. In addition to known clinical factors, appetite loss appears to be a significant prognostic factor for survival in women with metastatic breast cancer. However, the mechanism underlying this association remains to be precisely defined in future studies.

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In spectra of jet-cooled C2H2 recorded with an FTIR spectrometer, the ν5, ν4 + ν5, ν3 and ν2 + ν4 + ν5 bands all exhibit an intensity distribution corresponding to ∼6 K for rotation, with no evidence of nuclear spin conversion. Spectra of C2H2 isolated in solid p-H2 show no evidence of rotation of C2H2. The strong interaction between ν3 and ν2 + ν4 + ν5 in the gas phase is diminished in solid p-H2. Lines associated with dimer, trimer and tetramer of C2H2 are identified. Spectral features characteristic of solid state acetylene are observed under jet-cooled conditions. © 2007 Elsevier B.V. All rights reserved.

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Earth's surface is rapidly urbanizing, resulting in dramatic changes in the abundance, distribution and character of surface water features in urban landscapes. However, the scope and consequences of surface water redistribution at broad spatial scales are not well understood. We hypothesized that urbanization would lead to convergent surface water abundance and distribution: in other words, cities will gain or lose water such that they become more similar to each other than are their surrounding natural landscapes. Using a database of more than 1 million water bodies and 1 million km of streams, we compared the surface water of 100 US cities with their surrounding undeveloped land. We evaluated differences in areal (A WB) and numeric densities (N WB) of water bodies (lakes, wetlands, and so on), the morphological characteristics of water bodies (size), and the density (D C) of surface flow channels (that is, streams and rivers). The variance of urban A WB, N WB, and D C across the 100 MSAs decreased, by 89, 25, and 71%, respectively, compared to undeveloped land. These data show that many cities are surface water poor relative to undeveloped land; however, in drier landscapes urbanization increases the occurrence of surface water. This convergence pattern strengthened with development intensity, such that high intensity urban development had an areal water body density 98% less than undeveloped lands. Urbanization appears to drive the convergence of hydrological features across the US, such that surface water distributions of cities are more similar to each other than to their surrounding landscapes. © 2014 The Author(s).

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© 2014, Springer-Verlag Berlin Heidelberg.This study assesses the skill of advanced regional climate models (RCMs) in simulating southeastern United States (SE US) summer precipitation and explores the physical mechanisms responsible for the simulation skill at a process level. Analysis of the RCM output for the North American Regional Climate Change Assessment Program indicates that the RCM simulations of summer precipitation show the largest biases and a remarkable spread over the SE US compared to other regions in the contiguous US. The causes of such a spread are investigated by performing simulations using the Weather Research and Forecasting (WRF) model, a next-generation RCM developed by the US National Center for Atmospheric Research. The results show that the simulated biases in SE US summer precipitation are due mainly to the misrepresentation of the modeled North Atlantic subtropical high (NASH) western ridge. In the WRF simulations, the NASH western ridge shifts 7° northwestward when compared to that in the reanalysis ensemble, leading to a dry bias in the simulated summer precipitation according to the relationship between the NASH western ridge and summer precipitation over the southeast. Experiments utilizing the four dimensional data assimilation technique further suggest that the improved representation of the circulation patterns (i.e., wind fields) associated with the NASH western ridge substantially reduces the bias in the simulated SE US summer precipitation. Our analysis of circulation dynamics indicates that the NASH western ridge in the WRF simulations is significantly influenced by the simulated planetary boundary layer (PBL) processes over the Gulf of Mexico. Specifically, a decrease (increase) in the simulated PBL height tends to stabilize (destabilize) the lower troposphere over the Gulf of Mexico, and thus inhibits (favors) the onset and/or development of convection. Such changes in tropical convection induce a tropical–extratropical teleconnection pattern, which modulates the circulation along the NASH western ridge in the WRF simulations and contributes to the modeled precipitation biases over the SE US. In conclusion, our study demonstrates that the NASH western ridge is an important factor responsible for the RCM skill in simulating SE US summer precipitation. Furthermore, the improvements in the PBL parameterizations for the Gulf of Mexico might help advance RCM skill in representing the NASH western ridge circulation and summer precipitation over the SE US.

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BACKGROUND: While effective population size (Ne) and life history traits such as generation time are known to impact substitution rates, their potential effects on base composition evolution are less well understood. GC content increases with decreasing body mass in mammals, consistent with recombination-associated GC biased gene conversion (gBGC) more strongly impacting these lineages. However, shifts in chromosomal architecture and recombination landscapes between species may complicate the interpretation of these results. In birds, interchromosomal rearrangements are rare and the recombination landscape is conserved, suggesting that this group is well suited to assess the impact of life history on base composition. RESULTS: Employing data from 45 newly and 3 previously sequenced avian genomes covering a broad range of taxa, we found that lineages with large populations and short generations exhibit higher GC content. The effect extends to both coding and non-coding sites, indicating that it is not due to selection on codon usage. Consistent with recombination driving base composition, GC content and heterogeneity were positively correlated with the rate of recombination. Moreover, we observed ongoing increases in GC in the majority of lineages. CONCLUSIONS: Our results provide evidence that gBGC may drive patterns of nucleotide composition in avian genomes and are consistent with more effective gBGC in large populations and a greater number of meioses per unit time; that is, a shorter generation time. Thus, in accord with theoretical predictions, base composition evolution is substantially modulated by species life history.

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BACKGROUND: Mammalian genomes commonly harbor endogenous viral elements. Due to a lack of comparable genome-scale sequence data, far less is known about endogenous viral elements in avian species, even though their small genomes may enable important insights into the patterns and processes of endogenous viral element evolution. RESULTS: Through a systematic screening of the genomes of 48 species sampled across the avian phylogeny we reveal that birds harbor a limited number of endogenous viral elements compared to mammals, with only five viral families observed: Retroviridae, Hepadnaviridae, Bornaviridae, Circoviridae, and Parvoviridae. All nonretroviral endogenous viral elements are present at low copy numbers and in few species, with only endogenous hepadnaviruses widely distributed, although these have been purged in some cases. We also provide the first evidence for endogenous bornaviruses and circoviruses in avian genomes, although at very low copy numbers. A comparative analysis of vertebrate genomes revealed a simple linear relationship between endogenous viral element abundance and host genome size, such that the occurrence of endogenous viral elements in bird genomes is 6- to 13-fold less frequent than in mammals. CONCLUSIONS: These results reveal that avian genomes harbor relatively small numbers of endogenous viruses, particularly those derived from RNA viruses, and hence are either less susceptible to viral invasions or purge them more effectively.

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BACKGROUND: Vertebrate skin appendages are constructed of keratins produced by multigene families. Alpha (α) keratins are found in all vertebrates, while beta (β) keratins are found exclusively in reptiles and birds. We have studied the molecular evolution of these gene families in the genomes of 48 phylogenetically diverse birds and their expression in the scales and feathers of the chicken. RESULTS: We found that the total number of α-keratins is lower in birds than mammals and non-avian reptiles, yet two α-keratin genes (KRT42 and KRT75) have expanded in birds. The β-keratins, however, demonstrate a dynamic evolution associated with avian lifestyle. The avian specific feather β-keratins comprise a large majority of the total number of β-keratins, but independently derived lineages of aquatic and predatory birds have smaller proportions of feather β-keratin genes and larger proportions of keratinocyte β-keratin genes. Additionally, birds of prey have a larger proportion of claw β-keratins. Analysis of α- and β-keratin expression during development of chicken scales and feathers demonstrates that while α-keratins are expressed in these tissues, the number and magnitude of expressed β-keratin genes far exceeds that of α-keratins. CONCLUSIONS: These results support the view that the number of α- and β-keratin genes expressed, the proportion of the β-keratin subfamily genes expressed and the diversification of the β-keratin genes have been important for the evolution of the feather and the adaptation of birds into multiple ecological niches.