872 resultados para heterogeneous data sources
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The present data set includes 268,127 vertical in situ fluorescence profiles obtained from several available online databases and from published and unpublished individual sources. Metadata about each profiles are given in the file provided here in further details. The majority of profiles comes from the National Oceanographic Data Center (NODC) and the fluorescence profiles acquired by Bio-Argo floats available on the Oceanographic Autonomous Observations (OAO) platform (63.7% and 12.5% respectively).
Different modes of acquisition were used to collect the data presented in this study: (1) CTD profiles are acquired using a fluorometer mounted on a CTD-rosette; (2) OSD (Ocean Station Data) profiles are derived from water samples and are defined as low resolution profiles; (3) the UOR (Undulating Oceanographic Recorder) profiles are acquired by a
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Chiefly tables.
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Cover title.
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"Original guide published in 1964."
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"National Water-Quality Assessment Program"
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Mode of access: Internet.
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Includes indexes.
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"Distribution category UC-2."
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Dissolved organic matter (DOM) is one of the largest carbon reservoirs on this planet and is present in aquatic environments as a highly complex mixture of organic compounds. The Florida coastal Everglades (FCE) is one of the largest wetlands in the world. DOM in this system is an important biogeochemical component as most of the nitrogen (N) and phosphorous (P) are in organic forms. Achieving a better understanding of DOM dynamics in large coastal wetlands is critical, and a particularly important issue in the context of Everglades restoration. In this work, the environmental dynamics of surface water DOM on spatial and temporal scales was investigated. In addition, photo- and bio-reactivity of this DOM was determined, surface-to-groundwater exchange of DOM was investigated, and the size distribution of freshwater DOM in Everglades was assessed. The data show that DOM dynamics in this ecosystem are controlled by both hydrological and ecological drivers and are clearly different on spatial scales and variable seasonally. The DOM reactivity data, modeled with a multi-pool first order degradation kinetics model, found that fluorescent DOM in FCE is generally photo-reactive and bio-refractory. Yet the sequential degradation proved a “priming effect” of sunlight on the bacterial uptake and reworking of this subtropical wetland DOM. Interestingly, specific PARAFAC components were found to have different photo- and bio-degradation rates, suggesting a highly heterogeneous nature of fluorophores associated with the DOM. Surface-to-groundwater exchange of DOM was observed in different regions of the system, and compositional differences were associated with source and photo-reactivity. Lastly, the high degree of heterogeneity of DOM associated fluorophores suggested based on the degradation studies was confirmed through the EEM-PARAFAC analysis of DOM along a molecular size continuum, suggesting that the fluorescence characteristics of DOM are highly controlled by different size fractions and as such can exhibit significant differences in reactivity.
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Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.
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MEGAGEO - Moving megaliths in the Neolithic is a project that intends to find the provenience of lithic materials in the construction of tombs. A multidisciplinary approach is carried out, with researchers from several of the knowledge fields involved. This work presents a spatial data warehouse specially developed for this project that comprises information from national archaeological databases, geographic and geological information and new geochemical and petrographic data obtained during the project. The use of the spatial data warehouse proved to be essential in the data analysis phase of the project. The Redondo Area is presented as a case study for the application of the spatial data warehouse to analyze the relations between geochemistry, geology and the tombs in this area.
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Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.
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Giardia duodenalis is a flagellate protozoan that parasitizes humans and several other mammals. Protozoan contamination has been regularly documented at important environmental sites, although most of these studies were performed at the species level. There is a lack of studies that correlate environmental contamination and clinical infections in the same region. The aim of this study is to evaluate the genetic diversity of a set of clinical and environmental samples and to use the obtained data to characterize the genetic profile of the distribution of G. duodenalis and the potential for zoonotic transmission in a metropolitan region of Brazil. The genetic assemblages and subtypes of G. duodenalis isolates obtained from hospitals, a veterinary clinic, a day-care center and important environmental sites were determined via multilocus sequence-based genotyping using three unlinked gene loci. Cysts of Giardia were detected at all of the environmental sites. Mixed assemblages were detected in 25% of the total samples, and an elevated number of haplotypes was identified. The main haplotypes were shared among the groups, and new subtypes were identified at all loci. Ten multilocus genotypes were identified: 7 for assemblage A and 3 for assemblage B. There is persistent G. duodenalis contamination at important environmental sites in the city. The identified mixed assemblages likely represent mixed infections, suggesting high endemicity of Giardia in these hosts. Most Giardia isolates obtained in this study displayed zoonotic potential. The high degree of genetic diversity in the isolates obtained from both clinical and environmental samples suggests that multiple sources of infection are likely responsible for the detected contamination events. The finding that many multilocus genotypes (MLGs) and haplotypes are shared by different groups suggests that these sources of infection may be related and indicates that there is a notable risk of human infection caused by Giardia in this region.
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The purpose of this study was to compare the polymerization shrinkage stress of composite resins (microfilled, microhybrid and hybrid) photoactivated by quartz-tungsten halogen light (QTH) and light-emitting diode (LED). Glass rods (5.0 mm x 5.0 cm) were fabricated and had one of the surfaces air-abraded with aluminum oxide and coated with a layer of an adhesive system, which was photoactivated with the QTH unit. The glass rods were vertically assembled, in pairs, to a universal testing machine and the composites were applied to the lower rod. The upper rod was placed closer, at 2 mm, and an extensometer was attached to the rods. The 20 composites were polymerized by either QTH (n=10) or LED (n=10) curing units. Polymerization was carried out using 2 devices positioned in opposite sides, which were simultaneously activated for 40 s. Shrinkage stress was analyzed twice: shortly after polymerization (t40s) and 10 min later (t10min). Data were analyzed statistically by 2-way ANOVA and Tukey's test (a=5%). The shrinkage stress for all composites was higher at t10min than at t40s, regardless of the activation source. Microfilled composite resins showed lower shrinkage stress values compared to the other composite resins. For the hybrid and microhybrid composite resins, the light source had no influence on the shrinkage stress, except for microfilled composite at t10min. It may be concluded that the composition of composite resins is the factor with the strongest influence on shrinkage stress.
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OBJECTIVE: This study evaluated the influence of light sources and immersion media on the color stability of a nanofilled composite resin. MATERIAL AND METHODS: Conventional halogen, high-power-density halogen and high-power-density light-emitting diode (LED) units were used. There were 4 immersion media: coffee, tea, Coke® and artificial saliva. A total of 180 specimens (10 mm x 2 mm) were prepared, immersed in artificial saliva for 24 h at 37±1ºC, and had their initial color measured with a spectrophotometer according to the CIELab system. Then, the specimens were immersed in the 4 media during 60 days. Data from the color change and luminosity were collected and subjected to statistical analysis by the Kruskall-Wallis test (p<0.05). For immersion time, the data were subjected to two-way ANOVA test and Fisher's test (p<0.05). RESULTS: High-power-density LED (ΔE=1.91) promoted similar color stability of the composite resin to that of the tested halogen curing units (Jet Lite 4000 plus - ΔE=2.05; XL 3000 - ΔE=2.28). Coffee (ΔE=8.40; ΔL=-5.21) showed the highest influence on color stability of the studied composite resin. CONCLUSION: There was no significant difference in color stability regardless of the light sources, and coffee was the immersion medium that promoted the highest color changes on the tested composite resin.