995 resultados para Weather radar networks


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Ground-penetrating radar (GPR) and microgravimetric surveys have been conducted in the southern Jura mountains of western Switzerland in order to map subsurface karstic features. The study site, La Grande Rolaz cave, is an extensive system in which many portions have been mapped. By using small station spacing and careful processing for the geophysical data, and by modeling these data with topographic information from within the cave, accurate interpretations have been achieved. The constraints on the interpreted geologic models are better when combining the geophysical methods than when using only one of the methods, despite the general limitations of two-dimensional (2D) profiling. For example, microgravimetry can complement GPR methods for accurately delineating a shallow cave section approximately 10 X 10 mt in size. Conversely, GPR methods can be complementary in determining cavity depths and in verifying the presence of off-line features and numerous areas of small cavities and fractures, which may be difficult to resolve in microgravimetric data.

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Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain's anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.

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O GPR utiliza técnica indireta para investigação das estruturas de subsuperfície, sendo caracterizado como método não-invasivo, o qual permite extrair informações ao longo do perfil de solo sem perfurar, sondar ou escavar. Este trabalho teve o objetivo de avaliar a utilização do GPR no estabelecimento de atributos físicos do solo em área de cultivo com cana-de-açúcar, além de estabelecer sua correlação com o método do cilindro volumétrico. A área de estudo está localizada no município de Bom Sucesso - PR, sendo utilizada com cultura da cana há mais de 20 anos. Foram obtidas amostras de solos indeformadas com cilindro volumétrico nas profundidades de 0-0,1, 0,1-0,2, 0,2-0,3, 0,3-0,4 e 0,4-0,5 m, ao longo de três transeptos paralelos, sendo o central referente à linha de plantio (transepto 2) e os outros dois correspondentes às entrelinhas laterais (transeptos 1 e 3). Os valores de densidade e porosidade total, obtidos por meio das amostras físicas, foram inicialmente interpretados para verificar o estado do solo nas linhas e nas entrelinhas de cana, nas cinco profundidades. Posteriormente, foram correlacionados com os valores das constantes dielétricas (K) adquiridos pelo georradar, porém apenas para a camada de 0,4-0,5 m, uma vez que as camadas superficiais até a profundidade de 0,4 m não puderam ser avaliadas devido às limitações técnicas do equipamento, aliadas às condições físicas e químicas do solo, que acabaram por prejudicar as reflexões. A densidade mostrou-se menor nas linhas, quando comparada às entrelinhas, para as camadas de 0-0,1 e 0,2-0,3 m. A porosidade total foi menor nas entrelinhas do que nas linhas na camada de 0-0,1 m. Os valores de K foram maiores nas linhas, onde a umidade e a porosidade total foram maiores, e menores nas entrelinhas, onde as densidades encontravam se próximas ao limite crítico. A correlação de K com a densidade e porosidade total não foi significativa. Pequenas modificações na porosidade do solo em função do aumento da densidade foram suficientes para diminuir o valor de K nas entrelinhas, devido à redução na quantidade de água nos poros. Esse fato pode ser confirmado pela correlação de K com a umidade. Assim, pode-se dizer que o georradar foi extremamente sensível à variação de umidade no solo, apresentando melhores resultados para esta variável do que para a densidade e porosidade total determinada por meio do cilindro volumétrico.

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Capital intensive industries in specialized niches of production have constituted solid ground for family firms in Spain , as evidenced by the experience of the iron and steel wire industries between 1870 and 2000. The embeddedness of these firms in their local and regional environments have allowed the creation of networks that, together with favourable institutional conditions, significantly explain the dominance of family entrepreneurship in iron and steel wire manufacturing in Spain, until the end of the 20 th century. Dominance of family firms at the regional level has not been not an obstacle for innovation in wire manufacturing in Spain, which has taken place even when institutional conditions blocked innovation and traditional networking. Therefore, economic theories about the difficulties dynastic family firms may have to perform appropriately in science-based industries must be questioned

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Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy control subjects at no-task, eyes-closed condition. The cross-correlation of artifact-free EEGs was used to construct brain functional networks. The extracted networks were then tested for their synchronization properties by calculating the eigenratio of the Laplacian matrix of the connection graph, i.e., the largest eigenvalue divided by the second smallest one. In AD patients, we found an increase in the eigenratio, i.e., a decrease in the synchronizability of brain networks across delta, alpha, beta, and gamma EEG frequencies within the wide range of network costs. The finding indicates the destruction of functional brain networks in early AD.

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In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

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Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

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Highway agencies spend millions of dollars to ensure safe and efficient winter travel. However, the effectiveness of winter weather maintenance practices on safety and mobility are somewhat difficult to quantify. Phase I of this project investigated opportunities for improving traffic safety on state-maintained roads in Iowa during winter weather conditions. The primary objective was to develop several preliminary means for the Iowa Department of Transportation (DOT) to identify locations of possible interest systematically with respect to winter weather-related safety performance based on crash history. Specifically, metrics were developed to assist in identifying possible habitual, winter weather-related crash sites on state-maintained rural highways in Iowa. In addition, the current state of practice, for both domestic and international highway agency practices, regarding integration of traffic safety- and mobility-related data in winter maintenance activities and performance measures were investigated. This investigation also included previous research efforts. Finally, a preliminary work plan, focusing on systematic use of safety-related data in support of winter maintenance activities and site evaluation, was prepared.

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Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdepen- dencies across individuals' transition to parenthood and its timing we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics regarding age, intended education and parity. Agents endogenously form their network based on social closeness. Network members then may influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social inter- actions can explain the shift of first-birth probabilities in Austria over the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Iowa Secretary of Agriculture Bill Northey today commented on the Iowa Crops and Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Iowa Secretary of Agriculture Bill Northey today commented on the Iowa Crops and Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Iowa Secretary of Agriculture Bill Northey today commented on the Iowa Crops and Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Iowa Secretary of Agriculture Bill Northey today commented on the Iowa Crops and Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Iowa Secretary of Agriculture Bill Northey today commented on the Iowa Crops and Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October.