996 resultados para Fortification--Virginia--Petersburg Region--Maps.


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A detailed study is presented of the decaying solar-active region NOAA 10103 observed with the Coronal Diagnostic Spectrometer (CDS), the Michelson Doppler Imager (MDI) and the Extreme-ultraviolet Imaging Telescope (EIT) onboard the Solar and Heliospheric Observatory (SOHO). Electron-density maps formed using Si x (356.03 angstrom/347.41 angstrom) show that the density varies from similar to 10(10) cm(-3) in the active-region core to similar to 7 x 108 cm-3 at the region boundaries. Over the 5 d of observations, the average electron density fell by similar to 30 per cent. Temperature maps formed using Fe XVI (335.41 angstrom)/Fe XIV (334.18 angstrom) show electron temperatures of similar to 2.34 x 10(6) K in the active-region core and similar to 2.10 x 10(6) K at the region boundaries. Similarly to the electron density, there was a small decrease in the average electron temperature over the 5-d period. The radiative, conductive and mass-flow losses were calculated and used to determine the resultant heating rate (P-H). Radiative losses were found to dominate the active-region cooling process. As the region decayed, the heating rate decreased by almost a factor of 5 between the first and last day of observations. The heating rate was then compared to the total unsigned magnetic flux (Phi(tot) = integral dA vertical bar B-z vertical bar), yielding a power law of the form P-H similar to Phi(0.81 +/- 0.32)(tot) This result suggests that waves rather than nanoflares may be the dominant heating mechanism in this active region.

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Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.

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Saliency maps determine the likelihood that we focus on interesting areas of scenes or images. These maps can be built using several low-level image features, one of which having a particular relevance: colour. In this paper we present a new computational model, based only on colour features, which provides a sound basis for saliency maps for static images and video, plus region segregation and cues for local gist vision.

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First described more that 150 years ago, the systematics of the genera Geomalacus and Letourneuxia (Arionidae, Gastropoda, Pulmonata) is still challenging. The taxonomic classification of arionid species is based on extremely labile characters such as body size or color that depends both on diet and environment, as well as age. Moreover, there is little information on the genetic diversity and population structure of the Iberian slugs that could provide extra clues to disentangle their problematic classification. The present work uses different analytical tools such as habitat suitability (Ecological Niche Modeling - ENM), cytogenetic analysis and phylogeography to establish the geographical distribution and evolutionary history of these pulmonate slugs. The potential distribution of the four Geomalacus species was modeled using ENM, which allowed the identification of new locations for G. malagensis, including a first report in Portugal. Also, it was predicted a much wider distribution for G. malagensis and G. oliveirae than previously known. Classical cytogenetic analyses were assayed with reproductive and a novel use of somatic tissues (mouth and tentacles) returning the number of chromosomes for the four Geomalacus species and L. numidica (n = 31, 2n = 62) and the respective karyotypes. G. malagensis and L. numidica present similar chromosome morphologies and karyotypic formulae, being more similar to each other than the Geomalacus among themselves. We further reconstructed the phylogeny of the genera Geomalacus and Letourneuxia using partial sequences of the mitochondrial cytochrome oxidase subunit I (COI) and the nuclear ribosomal small subunit (18S rRNA), and applied an independent evolutionary rate method, the indicator vectors correlation, to evaluate the existence of cryptic diversity within species. The five nominal species of Geomalacus and Letourneuxia comprise 14 well-supported cryptic lineages. Letourneuxia numidica was retrieved as a sister group of G. malagensis. G. oliveirae is paraphyletic with respect to G. anguiformis. According to our dating estimates, the most recent common ancestor of Geomalacus dates back to the Middle Miocene (end of the Serravallian stage). The major lineage splitting events within Geomalacus occurred during the dry periods of the Zanclean stage (5.3-3.6 million years) and some lineages were confined to more humid mountain areas of the Iberian Peninsula, which lead to a highly geographically structured mitochondrial genetic diversity. The major findings of this are the following: (1) provides updated species distribution maps for the Iberian Geomalacus expanding the known geographic distribution of the concerned species, (2) unravels the cryptic diversity within the genera Geomalacus and Letourneuxia, (3) Geomalacus oliveirae is paraphyletic with G. anguiformis and (4) Letourneuxia numidica is sister group of G. malagensis.

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Regional knowledge map is a tool recently demanded by some actors in an institutional level to help regional policy and innovation in a territory. Besides, knowledge maps facilitate the interaction between the actors of a territory and the collective learning. This paper reports the work in progress of a research project which objective is to define a methodology to efficiently design territorial knowledge maps, by extracting information of big volumes of data contained in diverse sources of information related to a region. Knowledge maps facilitate management of the intellectual capital in organisations. This paper investigates the value to apply this tool to a territorial region to manage the structures, infrastructures and the resources to enable regional innovation and regional development. Their design involves the identification of information sources that are required to find which knowledge is located in a territory, which actors are involved in innovation, and which is the context to develop this innovation (structures, infrastructures, resources and social capital). This paper summarizes the theoretical background and framework for the design of a methodology for the construction of knowledge maps, and gives an overview of the main challenges for the design of regional knowledge maps.

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Regional Innovation Systems describe the relations between actors, structures and infrastructures in a region in order to stimulate innovation and regional development. For these systems the collection and organization of information is crucial. In the present paper we investigate the possibilities to extract information from websites of companies. First we describe regional innovation systems and the information types that are necessary to create them. Then we discuss the possibilities of text mining and keyword extraction techniques to extract this information from company websites. Finally, we describe a small scale experiment in which keywords related to economic sectors and commodities are extracted from the websites of over 200 companies. This experiment shows what the main challenges are for information extraction from websites for regional innovation systems.

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Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.

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Cells recruited by the innate immune response rely on surface-expressed molecules in order to receive signals from the local environment and to perform phagocytosis, cell adhesion, and others processes linked to host defense. Hundreds of surface antigens designated through a cluster of differentiation (CD) number have been used to identify particular populations of leukocytes. Surprisingly, we verified that the genes that encode Cd36 and Cd83 are constitutively expressed in specific neuronal cells. For instance, Cd36 mRNA is expressed in some regions related to circuitry involved in pheromone responses and reproductive behavior. Cd44 expression, reanalyzed and detailed here, is associated with the laminar formation and midline thalamic nuclei in addition to striatum, extended amygdala, and a few hypothalamic, cortical, and hippocampal regions. A systemic immune challenge was able to increase Cd44 expression quickly in the area postrema and motor nucleus of the vagus but not in regions presenting expressive constitutive expression. In contrast to Cd36 and Cd44, Cd83 message was widely distributed from the olfactory bulb to the brain stem reticular formation, sparing the striatopallidum, olivary region, and cerebellum. Its pattern of expression nevertheless remained strongly associated with hypothalamic, thalamic, and hindbrain nuclei. Unlike the other transcripts, Cd83 mRNA was rapidly modulated by restraint stress. Our results indicate that these molecules might play a role in specific neural circuits and present functions other than those attributed to leukocyte biology. The data also suggest that these surface proteins, or their associated mRNA, could be used to label neurons in specific circuits/regions. J. Comp. Neurol. 517:906-924, 2009. (C) 2009 Wiley-Liss, Inc.

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From the geotechnical standpoint, it is interesting to analyse the soil texture in regions with rough terrain due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this paper is to present a methodology that provides the soil texture spatialization by using Fuzzy logic and Geostatistic. The results were correlated with maps drawn specifically for the study area. The knowledge of the spatialization of soil properties, such as the texture, can be an important tool for land use planning in order to reduce the potential soil losses during rain seasons. (c) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Spatial Statistics 2011

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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A study on the presence of herbicides, namely simazine, metribuzin, metolachlor, trifluralin, atrazine and two metabolites, deisopropylatrazine (DIA) and deethylatrazine (DEA), was performed in ground and surface waters from Primavera do Leste region, Mato Grosso state (Middle West of Brazil). The analytical procedure was based on solid-phase extraction (SPE) with Sep-Pak C18 disposable cartridges and ethyl acetate for elution solvent. Residue levels were determined by gas chromatography with nitrogen-phosphorus detection. For most of the pesticides average recoveries at different fortification levels were >with relative standard deviation < The recoveries of DIA and trifluralin in water were 25% and 56%, respectively, which were attributed to the incomplete retention of DIA and strong retention on the sorbing material and high volatility of trifluralin. Detection limits ranged from 0.023 to 0.088 μg L-1. This method was applied for the analysis of 5 superficial water samples and 28 groundwater samples, in places used for human consumption without previous treatment, collected in Primavera do Leste, Mato Grosso, Brazil. Results indicated that the highest level of contamination in a water sample was 1.732 μg L-1 for metolachlor, while metribuzin was the most frequently detected herbicide with maximum concentration of 0.351 μg L-1. ©2006 Sociedade Brasileira de Química.

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Includes bibliography