942 resultados para categorical and mix datasets


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We introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and from biomass burning aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostics include the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between the simulated biomass burning aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM(2.5)) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosondes and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained.

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Context. Two main scenarios for the formation of the Galactic bulge are invoked, the first one through gravitational collapse or hierarchical merging of subclumps, the second through secular evolution of the Galactic disc. Aims. We aim to constrain the formation of the Galactic bulge through studies of the correlation between kinematics and metallicities in Baade's Window (l = 1 degrees, b = -4 degrees) and two other fields along the bulge minor axis (l = 0 degrees, b = -6 degrees and b = -12 degrees). Methods. We combine the radial velocity and the [Fe/H] measurements obtained with FLAMES/GIRAFFE at the VLT with a spectral resolution of R = 20 000, plus for the Baade's Window field the OGLE-II proper motions, and compare these with published N-body simulations of the Galactic bulge. Results. We confirm the presence of two distinct populations in Baade's Window found in Hill et al. (2010, A&A, submitted): the metal-rich population presents bar-like kinematics while the metal-poor population shows kinematics corresponding to an old spheroid or a thick disc. In this context the metallicity gradient along the bulge minor axis observed by Zoccali et al. (2008, A&A, 486, 177), visible also in the kinematics, can be related to a varying mix of these two populations as one moves away from the Galactic plane, alleviating the apparent contradiction between the kinematic evidence of a bar and the existence of a metallicity gradient. Conclusions. We show evidence that the two main scenarios for the bulge formation co-exist within the Milky Way bulge.

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Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2)' = 0.3760.10, mean 6 SD) and similar nestedness (NODF = 0.5660.12) than pollination networks. All networks were modular (M=0.32 +/- 0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55 +/- 0.10) and plants (R = 0.68 +/- 0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

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Tropical countries face special specific problems in implementing sustainable forest management (SFM). In many countries, questions are raised on whether tropical forests should be publicly, commonly or privately owned and managed in order to enhance sustainability. Other debates also focus on whether small-scale enterprises are better positioned than large-scale industrial concessions to reduce poverty and attain sustainable management. In countries where large tracts of forest are state-owned, concessions are viewed as a means of delivering services of public and collective interest through an association of private investment and public regulation. However, the success of an industrial concession model in countries with large forest resource endowment to achieve multiple goals such as sustainable forest management and local/regional development depends on two critical assumptions. First, forest functions and services should be managed and maintained as public goods. In many cases, additional uses - and corresponding rights - can take place alongside logging activities. Industrial concessions can be more efficient than other tenure models (such as community-based forest management and small-scale enterprises) in achieving SFM, add value to raw material and comply with growing environmental norms. This is especially the case in market-remote areas with low population density and poor infrastructure. Secondly, to achieve these different outcomes, any concession system needs to be monitored and regulated, especially in contexts dominated by asymmetrical information between regulating authorities and concessionaires. New institutional responses have recently been put forward in several countries, providing valuable materials to design a renewed policy mix which associates public and private incentives. This paper provides a survey of the experience of forest concessions in several Central African and South American countries. The concession system is examined in order to clarify the issues involved, the problems encountered, and what can be learned from the shared experience of these countries in the last decade. This paper argues that despite a sometimes patchy record, concessions can help promote SFM so long as they are packaged with a certain number of specific measures. (C) 2008 Elsevier B.V. All rights reserved.

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Silicon carbide ceramics are very interesting materials to engineering applications because of their properties. These ceramics are produced by liquid phase sintering (LPS), where elevated temperature and time are necessary, and generally form volatile products that promote defects and damage their mechanical properties. In this work was studied the infiltration process to produce SiC ceramics, using shorter time and temperature than LPS, thereby reducing the undesirable chemical reactions. SiC powder was pressed at 300 MPa and pre-sintered at 1550 degrees C for 30 min. Unidirectional and spontaneous infiltration of this preform by Al2O3/Y2O3 liquid was done at 1850 degrees C for 5, 10, 30 and 60 min. The kinetics of infiltration was studied, and the infiltration equilibrium happened when the liquid infiltrated 12 mm into perform. The microstructures show grains of the SiC surrounded by infiltrated additives. The hardness and fracture toughness are similar to conventional SiC ceramics obtained by LPS. (c) 2007 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

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An experimental laboratory was designed and assembled at the Botanical Institute of So Paulo, Brazil, in order to research atmosphere-plant interactions through the use of a system of fumigation chambers. A system of three ""closed"" fumigation chambers was designed to be used inside or outside the laboratory. The system was built to be used with a single pollutant or a mix of them. The innovation in this system is to allow chemical reactions inside the chambers that simulate atmospheric chemistry, especially photochemical processes involving high levels of ozone. Assessment of the performance and applicability of the system was based on the response of Nicotiana tabacum Bel W3 exposed to ozone produced alternatively by a generator and inside the chamber by reactions of its precursors. The results showed that the system can be well applied to the study of atmospheric chemistry interactions and the effects on plants.

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Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

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Cementitious stabilization of aggregates and soils is an effective technique to increase the stiffness of base and subbase layers. Furthermore, cementitious bases can improve the fatigue behavior of asphalt surface layers and subgrade rutting over the short and long term. However, it can lead to additional distresses such as shrinkage and fatigue in the stabilized layers. Extensive research has tested these materials experimentally and characterized them; however, very little of this research attempts to correlate the mechanical properties of the stabilized layers with their performance. The Mechanistic Empirical Pavement Design Guide (MEPDG) provides a promising theoretical framework for the modeling of pavements containing cementitiously stabilized materials (CSMs). However, significant improvements are needed to bring the modeling of semirigid pavements in MEPDG to the same level as that of flexible and rigid pavements. Furthermore, the MEPDG does not model CSMs in a manner similar to those for hot-mix asphalt or portland cement concrete materials. As a result, performance gains from stabilized layers are difficult to assess using the MEPDG. The current characterization of CSMs was evaluated and issues with CSM modeling and characterization in the MEPDG were discussed. Addressing these issues will help designers quantify the benefits of stabilization for pavement service life.

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We describe in this paper a new genus and species of cricetid rodent from the Atlantic Forest of Brazil, one of the most endangered eco-regions of the world. The new form displays some but not all synapomorphies of the tribe Oryzomyini, but a suite of unique characteristics is also observed. This new forest rat possesses anatomical characteristics of arboreal taxa, such as very developed plantar pads, but was collected almost exclusively in pitfall traps. Phylogenetic analyses of morphological (integument, soft tissue, cranial, and dental characters) and molecular [nuclear - Interphotoreceptor retinoid binding protein (Irbp) - and mitochondrial - cytochrome b - genes] datasets using maximum likelihood and cladistic parsimony approaches corroborate the inclusion of the new taxon within oryzomyines. The analyses also place the new form as sister species to Eremoryzomys polius, an Andean rat endemic to the Maranon valley. This biogeographical pattern is unusual amongst small terrestrial vertebrates, as a review of the literature points to few other similar examples of Andean-Atlantic Forest pairings, in hylid frogs, Pionus parrots, and other sigmodontine rodents. (C) 2011 The Linnean Society of London, Zoological Journal of the Linnean Society, 2011, 161, 357-390. doi:10.1111/j.1096-3642.2010.00643.x

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The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

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The present article describes an L-amino acid oxidase from Bothrops atrox snake venom as with antiprotozoal activities in Trypanosoma cruzi and in different species of Leishmania (Leishmania braziliensis, Leishmania donovani and Leishmania major). Leishmanicidal effects were inhibited by catalase, suggesting that they are mediated by H(2)O(2) production. Leishmania spp. cause a spectrum of diseases, ranging from self-healing ulcers to disseminated and often fatal infections, depending on the species involved and the host`s immune response. BatroxLAAO also displays bactericidal activity against both Gram-positive and Gram-negative bacteria. The apoptosis induced by BatroxLAAO on HL-60 cell lines and PBMC cells was determined by morphological cell evaluation using a mix of fluorescent dyes. As revealed by flow cytometry analysis, suppression of cell proliferation with BatroxLAAO was accompanied by the significant accumulation of cells in the G0/G1 phase boundary in HL-60 cells. BatroxLAAO at 25 mu g/mL and 50 mu g/mL blocked G0-G1 transition, resulting in G0/G1 phase cell cycle arrest, thereby delaying the progression of cells through S and G2/M phase in HL-60 cells. This was shown by an accentuated decrease in the proportion of cells in S phase, and the almost absence of G2/M phase cell population. BatroxLAAO is an interesting enzyme that provides a better understanding of the ophidian envenomation mechanism, and has biotechnological potential as a model for therapeutic agents. (C) 2011 Elsevier Masson SAS. All rights reserved.

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Modern lifestyle markedly changed eating habits worldwide, with an increasing demand for ready-to-eat foods, such as minimally processed fruits and leafy greens. Packaging and storage conditions of those products may favor the growth of psychrotrophic bacteria, including the pathogen Listeria monocytogenes. In this work, minimally processed leafy vegetables samples (n = 162) from retail market from Ribeirao Preto, Sao Paulo, Brazil, were tested for the presence or absence of Listeria spp. by the immunoassay Listeria Rapid Test, Oxoid. Two L. monocytogenes positive and six artificially contaminated samples of minimally processed leafy vegetables were evaluated by the Most Probable Number (MPN) with detection by classical culture method and also culture method combined with real-time PCR (RTi-PCR) for 16S rRNA genes of L monocytogenes. Positive MPN enrichment tubes were analyzed by RTi-PCR with primers specific for L. monocytogenes using the commercial preparation ABSOLUTET (TM) QPCR SYBR (R) Green Mix (ABgene, UK). Real-time PCR assay presented good exclusivity and inclusivity results and no statistical significant difference was found in comparison with the conventional culture method (p < 0.05). Moreover, RTi-PCR was fist and easy to perform, with MPN results obtained in ca. 48 h for RTi-PCR in comparison to 7 days for conventional method. (C) 2009 Elsevier Ltd. All rights reserved.

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One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

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This study describes the pedagogical impact of real-world experimental projects undertaken as part of an advanced undergraduate Fluid Mechanics subject at an Australian university. The projects have been organised to complement traditional lectures and introduce students to the challenges of professional design, physical modelling, data collection and analysis. The physical model studies combine experimental, analytical and numerical work in order to develop students’ abilities to tackle real-world problems. A first study illustrates the differences between ideal and real fluid flow force predictions based upon model tests of buildings in a large size wind tunnel used for research and professional testing. A second study introduces the complexity arising from unsteady non-uniform wave loading on a sheltered pile. The teaching initiative is supported by feedback from undergraduate students. The pedagogy of the course and projects is discussed with reference to experiential, project-based and collaborative learning. The practical work complements traditional lectures and tutorials, and provides opportunities which cannot be learnt in the classroom, real or virtual. Student feedback demonstrates a strong interest for the project phases of the course. This was associated with greater motivation for the course, leading in turn to lower failure rates. In terms of learning outcomes, the primary aim is to enable students to deliver a professional report as the final product, where physical model data are compared to ideal-fluid flow calculations and real-fluid flow analyses. Thus the students are exposed to a professional design approach involving a high level of expertise in fluid mechanics, with sufficient academic guidance to achieve carefully defined learning goals, while retaining sufficient flexibility for students to construct there own learning goals. The overall pedagogy is a blend of problem-based and project-based learning, which reflects academic research and professional practice. The assessment is a mix of peer-assessed oral presentations and written reports that aims to maximise student reflection and development. Student feedback indicated a strong motivation for courses that include a well-designed project component.