126 resultados para Stream Network
Resumo:
Trabajo de final de carrera enfocado a la simulación de una WSN (Wireless Sensors Networks) mediante el programa Contiki 2.7 y el SO Ubuntu. La idea global del proyecto es conseguir simular un entorno con nodos sensores y, a posteriori, comprobar su correcto funcionamiento en motas reales, comprobando los resultados obtenidos en ambos entornos. De esta manera se puede facilitar la puesta en marcha de este tipo de redes inalámbricas en una aplicación real.
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A mathematical model of the voltage drop which arises in on-chip power distribution networks is used to compare the maximum voltage drop in the case of different geometric arrangements of the pads supplying power to the chip. These include the square or Manhattan power pad arrangement, which currently predominates, as well as equilateral triangular and hexagonal arrangements. In agreement with the findings in the literature and with physical and SPICE models, the equilateral triangular power pad arrangement is found to minimize the maximum voltage drop. This headline finding is a consequence of relatively simple formulas for the voltage drop, with explicit error bounds, which are established using complex analysis techniques, and elliptic functions in particular.
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El principal objectiu d'aquest treball és implementar i exposar una descripció teòrica per a diferents esquemes de Physical Layer Network Coding. Utilitzant un esquema bàsic com a punt de partida, el projecte presenta la construcció i l'anàlisis de diferents esquemes de comunicació on la complexitat va augmentant a mesura que anem avançant en el projecte. El treball està estructurat en diferents parts: primer, es presenta una introducció a Physical Layer Network Coding i a Lattice Network Codes. A continuació, s'introdueixen les eines matemàtiques necessàries per entendre el CF System. Després, s'analitza i implementa el primer esquema bàsic. A partir del qual, implementem una versió vectorial del CF System i una versió codificada amb un Hamming q-ari. Finalment, s'estudien i implementen diferents estratègies per millorar la matriu de coeficients A.
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Background: The G1-to-S transition of the cell cycle in the yeast Saccharomyces cerevisiae involves an extensive transcriptional program driven by transcription factors SBF (Swi4-Swi6) and MBF (Mbp1-Swi6). Activation of these factors ultimately depends on the G1 cyclin Cln3. Results: To determine the transcriptional targets of Cln3 and their dependence on SBF or MBF, we first have used DNA microarrays to interrogate gene expression upon Cln3 overexpression in synchronized cultures of strains lacking components of SBF and/or MBF. Secondly, we have integrated this expression dataset together with other heterogeneous data sources into a single probabilistic model based on Bayesian statistics. Our analysis has produced more than 200 transcription factor-target assignments, validated by ChIP assays and by functional enrichment. Our predictions show higher internal coherence and predictive power than previous classifications. Our results support a model whereby SBF and MBF may be differentially activated by Cln3. Conclusions: Integration of heterogeneous genome-wide datasets is key to building accurate transcriptional networks. By such integration, we provide here a reliable transcriptional network at the G1-to-S transition in the budding yeast cell cycle. Our results suggest that to improve the reliability of predictions we need to feed our models with more informative experimental data.
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Background: Reconstruction of genes and/or protein networks from automated analysis of the literature is one of the current targets of text mining in biomedical research. Some user-friendly tools already perform this analysis on precompiled databases of abstracts of scientific papers. Other tools allow expert users to elaborate and analyze the full content of a corpus of scientific documents. However, to our knowledge, no user friendly tool that simultaneously analyzes the latest set of scientific documents available on line and reconstructs the set of genes referenced in those documents is available. Results: This article presents such a tool, Biblio-MetReS, and compares its functioning and results to those of other user-friendly applications (iHOP, STRING) that are widely used. Under similar conditions, Biblio-MetReS creates networks that are comparable to those of other user friendly tools. Furthermore, analysis of full text documents provides more complete reconstructions than those that result from using only the abstract of the document. Conclusions: Literature-based automated network reconstruction is still far from providing complete reconstructions of molecular networks. However, its value as an auxiliary tool is high and it will increase as standards for reporting biological entities and relationships become more widely accepted and enforced. Biblio- MetReS is an application that can be downloaded from http://metres.udl.cat/. It provides an easy to use environment for researchers to reconstruct their networks of interest from an always up to date set of scientific documents.
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This article explores how to enrich scaffolding processes among university students using specific Computer Supported Collaborative Learning –CSCL- software. A longitudinal case study was designed, in which eighteen students participated in a twelve-month learning project. During this period the students followed an instructional process, using the CSCL software to support and improve the students’ interaction processes, in particular the processes of giving and receiving assistance. Our research analyzed the evolution of the quality of the students’ interaction processes and the students’ learning results. The effects of the students’ participation in the CSCL environment have been described in terms of their development of affective, cognitive and metacognitive learning processes. Our results showed that the specific activities that students performed while working with the CSCL system triggered specific learning processes, which had a positive incidence on their learning results.
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Activity decreases, or deactivations, of midline and parietal cortical brain regions are routinely observed in human functional neuroimaging studies that compare periods of task-based cognitive performance with passive states, such as rest. It is now widely held that such task-induced deactivations index a highly organized"default-mode network" (DMN): a large-scale brain system whose discovery has had broad implications in the study of human brain function and behavior. In this work, we show that common task-induced deactivations from rest also occur outside of the DMN as a function of increased task demand. Fifty healthy adult subjects performed two distinct functional magnetic resonance imaging tasks that were designed to reliably map deactivations from a resting baseline. As primary findings, increases in task demand consistently modulated the regional anatomy of DMN deactivation. At high levels of task demand, robust deactivation was observed in non-DMN regions, most notably, the posterior insular cortex. Deactivation of this region was directly implicated in a performance-based analysis of experienced task difficulty. Together, these findings suggest that task-induced deactivations from rest are not limited to the DMN and extend to brain regions typically associated with integrative sensory and interoceptive processes.
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Behavioral consequences of a brain insult represent an interaction between the injury and the capacity of the rest of the brain to adapt to it. We provide experimental support for the notion that genetic factors play a critical role in such adaptation. We induced a controlled brain disruption using repetitive transcranial magnetic stimulation (rTMS) and show that APOE status determines its impact on distributed brain networks as assessed by functional MRI (fMRI).Twenty non-demented elders exhibiting mild memory dysfunction underwent two fMRI studies during face-name encoding tasks (before and after rTMS). Baseline task performance was associated with activation of a network of brain regions in prefrontal, parietal, medial temporal and visual associative areas. APOE ε4 bearers exhibited this pattern in two separate independent components, whereas ε4-non carriers presented a single partially overlapping network. Following rTMS all subjects showed slight ameliorations in memory performance, regardless of APOE status. However, after rTMS APOE ε4-carriers showed significant changes in brain network activation, expressing strikingly similar spatial configuration as the one observed in the non-carrier group prior to stimulation. Similarly, activity in areas of the default-mode network (DMN) was found in a single component among the ε4-non bearers, whereas among carriers it appeared disaggregated in three distinct spatiotemporal components that changed to an integrated single component after rTMS. Our findings demonstrate that genetic background play a fundamental role in the brain responses to focal insults, conditioning expression of distinct brain networks to sustain similar cognitive performance.
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Biological water quality changes in two Mediterranean river basins from a network of 42 sampling sites assessed since 1979 are presented. In order to characterize the biological quality, the index FBILL, designed to characterize these rivers" quality using aquatic macroinvertebrates, is used. When comparing the data from recent years to older ones, only two headwater sites from the 42 had improved their water quality to good or very good conditions. In the middle or low river basin sites or even in headwater localities were river flow is reduced, the important investment to build up sewage water treatment systems and plants (more than 70 in 15 years) allowed for a small recovery from poor or very poor conditions to moderate water quality. Nevertheless still a significant number (25 %) of the localities remain in poor conditions. The evolution of the quality in several points of both basins shows how the main problems for the recovery of the biological quality is due to the water diverted for small hydraulic plants, the presence of saline pollution in the Llobregat River, and the insufficient water depuration. In the smaller rivers, and specially the Besòs the lack of dilution flows from the treatment plants is the main problem for water quality recovery.
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Se ha realizado una prospección geoquímica táctica de sedimentos aluviales en el Brea de Cánoves-St. Pere de Vilamajor (Macizo del Montseny, Barcelona), como consecuencia de una exploración geoquimica estratégica de sedimentos aluviales previa, en la que se localizó un Brea anómala en Pb, Zn, Cu, As, Cd, Ni, y Co. El Brea estudiada tiene 35 km2 y esta constituida por materiales sedimentarios y volcánicos del Paleozoico, metamorfizados en mayor o menor grado e intruidos por el granito de Vallfornés, y materiales detríticos terciarios...
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[spa] En este artículo, analizamos la volatilidad agregada de una economía estilizada donde los agentes estann conectados en redes. Si hay relaciones estratégicas entre las acciones de los agentes, choques idiosincráticos pueden generar fluctuaciones agregadas. Demonstramos que la volatilidad agregada depende de la estructura de redes de la economía de dos maneras. Por un lado, si hay más conexiones en la economía en su conjunto, la volatilidad agregada es más baja. Por otro lado, si las conexiones están más concentradas, la volatilidad agregada es más alta. Presentamos una aplicación de nuestras predicciones teóricas que utiliza datos de EEUU de conexiones intrasectoriales y de diversificación de las empresas.
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[spa] En este artículo, analizamos la volatilidad agregada de una economía estilizada donde los agentes estann conectados en redes. Si hay relaciones estratégicas entre las acciones de los agentes, choques idiosincráticos pueden generar fluctuaciones agregadas. Demonstramos que la volatilidad agregada depende de la estructura de redes de la economía de dos maneras. Por un lado, si hay más conexiones en la economía en su conjunto, la volatilidad agregada es más baja. Por otro lado, si las conexiones están más concentradas, la volatilidad agregada es más alta. Presentamos una aplicación de nuestras predicciones teóricas que utiliza datos de EEUU de conexiones intrasectoriales y de diversificación de las empresas.
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Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.
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Social interactions are a very important component in people"s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times" Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links" weights are a measure of the"influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
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Short-term synaptic depression (STD) is a form of synaptic plasticity that has a large impact on network computations. Experimental results suggest that STD is modulated by cortical activity, decreasing with activity in the network and increasing during silent states. Here, we explored different activity-modulation protocols in a biophysical network model for which the model displayed less STD when the network was active than when it was silent, in agreement with experimental results. Furthermore, we studied how trains of synaptic potentials had lesser decay during periods of activity (UP states) than during silent periods (DOWN states), providing new experimental predictions. We next tackled the inverse question of what is the impact of modifying STD parameters on the emergent activity of the network, a question difficult to answer experimentally. We found that synaptic depression of cortical connections had a critical role to determine the regime of rhythmic cortical activity. While low STD resulted in an emergent rhythmic activity with short UP states and long DOWN states, increasing STD resulted in longer and more frequent UP states interleaved with short silent periods. A still higher synaptic depression set the network into a non-oscillatory firing regime where DOWN states no longer occurred. The speed of propagation of UP states along the network was not found to be modulated by STD during the oscillatory regime; it remained relatively stable over a range of values of STD. Overall, we found that the mutual interactions between synaptic depression and ongoing network activity are critical to determine the mechanisms that modulate cortical emergent patterns.