846 resultados para C53 - Forecasting and Other Model Applications
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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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Objective: To assess the frequency of drug use among Brazilian college students and its relationship to gender and age. Methods: A nationwide sample of 12,721 college students completed a questionnaire concerning the use of drugs and other behaviors. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST-WHO) criteria were used to assess were used to assess hazardous drug use. A multivariate logistic regression model tested the associations of ASSIST-WHO scores with gender and age. The same analyses were carried out to measure drug use in the last 30 days. Results: After controlling for other sociodemographic, academic and administrative variables, men were found to be more likely to use and engage in the hazardous use of anabolic androgenic steroids than women across all age ranges. Conversely, women older than 34 years of age were more likely to use and engage in the hazardous use of amphetamines. Conclusions: These findings are consistent with results that have been reported for the general Brazilian population. Therefore, these findings should be taken into consideration when developing strategies at the prevention of drug use and the early identification of drug abuse among college students.
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[EN]This paper describes a wildfi re forecasting application based on a 3D virtual environment and a fi re simulation engine. A novel open source framework is presented for the development of 3D graphics applications over large geographic areas, off ering high performance 3D visualization and powerful interaction tools for the Geographic Information Systems (GIS) community. The application includes a remote module that allows simultaneous connection of several users for monitoring a real wildfi re event.
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Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.
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Plasma polymerization technique is widely accepted as an effective and simple method for the preparation of functional thin films. By careful choice of precursors and deposition parameters, plasma polymers bearing various functional groups could be easily obtained. In this work, I explored the deposition of four kinds of plasma polymerised functional thin films, including the protein-resistant coatings, the thermosensitive coatings, as well as, the coatings bearing amine or epoxide groups. The deposited plasma polymers were characterized by various techniques, such as X-ray photoelectron spectroscopy, atom force microscopy, Fourier transform infrared spectroscopy, surface plasmon resonance spectroscopy, optical waveguide spectroscopy, and so on. As expected, high retention of various functional groups could be achieved either at low plasma input power or at low duty cycle (duty cycle = Ton/(Ton+Toff)). The deposited functional thin films were found to contain some soluble materials, which could be removed simply by extraction treatment. Besides the thermosentive plasma polymer (see Chapter 9), other plasma polymers were used for developing DNA sensors. DNA sensing in this study was achieved using surface plasmon enhanced fluorescence spectroscopy. The nonfouling thin films (i.e., ppEO2, plasma polymerization of di(ethylene glycol) monovinyl ether) were used to make a multilayer protein-resistant DNA sensor (see Chapter 5). The resulted DNA sensors show good anti-fouling properties towards either BSA or fibrinogen. This sensor was successfully employed to discriminate different DNA sequences from protein-containing sample solutions. In Chapter 6, I investigated the immobilization of DNA probes onto the plasma polymerized epoxide surfaces (i.e., ppGMA, plasma polymerization of glycidyl methacrylate). The ppGMA prepared at a low duty cycle showed good reactivity with amine-modified DNA probes in a mild basic environment. A DNA sensor based on the ppGMA was successfully used to distinguish different DNA sequences. While most DNA detection systems rely on the immobilization of DNA probes onto sensor surfaces, a new homogeneous DNA detection method was demonstrated in Chapter 8. The labeled PNA serves not only as the DNA catcher recognizing a particular target DNA, but also as a fluorescent indicator. Plasma polymerized allylamine (ppAA) films were used here to provide a positively charged surface.
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Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.
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This thesis is divided in three chapters. In the first chapter we analyse the results of the world forecasting experiment run by the Collaboratory for the Study of Earthquake Predictability (CSEP). We take the opportunity of this experiment to contribute to the definition of a more robust and reliable statistical procedure to evaluate earthquake forecasting models. We first present the models and the target earthquakes to be forecast. Then we explain the consistency and comparison tests that are used in CSEP experiments to evaluate the performance of the models. Introducing a methodology to create ensemble forecasting models, we show that models, when properly combined, are almost always better performing that any single model. In the second chapter we discuss in depth one of the basic features of PSHA: the declustering of the seismicity rates. We first introduce the Cornell-McGuire method for PSHA and we present the different motivations that stand behind the need of declustering seismic catalogs. Using a theorem of the modern probability (Le Cam's theorem) we show that the declustering is not necessary to obtain a Poissonian behaviour of the exceedances that is usually considered fundamental to transform exceedance rates in exceedance probabilities in the PSHA framework. We present a method to correct PSHA for declustering, building a more realistic PSHA. In the last chapter we explore the methods that are commonly used to take into account the epistemic uncertainty in PSHA. The most widely used method is the logic tree that stands at the basis of the most advanced seismic hazard maps. We illustrate the probabilistic structure of the logic tree, and then we show that this structure is not adequate to describe the epistemic uncertainty. We then propose a new probabilistic framework based on the ensemble modelling that properly accounts for epistemic uncertainties in PSHA.
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Granular matter, also known as bulk solids, consists of discrete particles with sizes between micrometers and meters. They are present in many industrial applications as well as daily life, like in food processing, pharmaceutics or in the oil and mining industry. When handling granular matter the bulk solids are stored, mixed, conveyed or filtered. These techniques are based on observations in macroscopic experiments, i.e. rheological examinations of the bulk properties. Despite the amply investigations of bulk mechanics, the relation between single particle motion and macroscopic behavior is still not well understood. For exploring the microscopic properties on a single particle level, 3D imaging techniques are required.rnThe objective of this work was the investigation of single particle motions in a bulk system in 3D under an external mechanical load, i.e. compression and shear. During the mechanical load the structural and dynamical properties of these systems were examined with confocal microscopy. Therefor new granular model systems in the wet and dry state were designed and prepared. As the particles are solid bodies, their motion is described by six degrees of freedom. To explore their entire motion with all degrees of freedom, a technique to visualize the rotation of spherical micrometer sized particles in 3D was developed. rnOne of the foci during this dissertation was a model system for dry cohesive granular matter. In such systems the particle motion during a compression of the granular matter was investigated. In general the rotation of single particles was the more sensitive parameter compared to the translation. In regions with large structural changes the rotation had an earlier onset than the translation. In granular systems under shear, shear dilatation and shear zone formation were observed. Globally the granular sediments showed a shear behavior, which was known already from classical shear experiments, for example with Jenike cells. Locally the shear zone formation was enhanced, when near the applied load a pre-diluted region existed. In regions with constant volume fraction a mixing between the different particle layers occurred. In particular an exchange of particles between the current flowing region and the non-flowing region was observed. rnThe second focus was on model systems for wet granular matter, where an additional binding liquid is added to the particle suspension. To examine the 3D structure of the binding liquid on the micrometer scale independently from the particles, a second illumination and detection beam path was implemented. In shear and compression experiments of wet clusters and bulk systems completely different dynamics compared to dry cohesive models systems occured. In a Pickering emulsion-like system large structural changes predominantly occurred in the local environment of binding liquid droplets. These large local structural changes were due to an energy interplay between the energy stored in the binding droplet during its deformation and the binding energy of particles at the droplet interface. rnConfocal microscopy in combination with nanoindentation gave new insights into the single particle motions and dynamics of granular systems under a mechanical load. These novel experimental results can help to improve the understanding of the relationship between bulk properties of granular matter, such as volume fraction or yield stress and the dynamics on a single particle level.rnrn
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Little sequence information exists on the matrix-protein (MA) encoding region of small ruminant lentiviruses (SRLV). Fifty-two novel sequences were established and permitted a first phylogenetic analysis of this region of the SRLV genome. The variability of the MA encoding region is higher compared to the gag region encoding the capsid protein and surprisingly close to that reported for the env gene. In contrast to primate lentiviruses, the deduced amino acid sequences of the N- and C-terminal domains of MA are variable. This permitted to pinpoint a basic domain in the N-terminal domain that is conserved in all lentiviruses and likely to play an important functional role. Additionally, a seven amino acid insertion was detected in all MVV strains, which may be used to differentiate CAEV and MVV isolates. A molecular epidemiology analysis based on these sequences indicates that the Italian lentivirus strains are closely related to each other and to the CAEV-CO strain, a prototypic strain isolated three decades ago in the US. This suggests a common origin of the SRLV circulating in the monitored flocks, possibly related to the introduction of infected goats in a negative population. Finally, this study shows that the MA region is suitable for phylogenetic studies and may be applied to monitor SRLV eradication programs.
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Out-of-body experiences (OBEs) are illusory perceptions of one's body from an elevated disembodied perspective. Recent theories postulate a double disintegration process in the personal (visual, proprioceptive and tactile disintegration) and extrapersonal (visual and vestibular disintegration) space as the basis of OBEs. Here we describe a case which corroborates and extends this hypothesis. The patient suffered from peripheral vestibular damage and presented with OBEs and lucid dreams. Analysis of the patient's behaviour revealed a failure of visuo-vestibular integration and abnormal sensitivity to visuo-tactile conflicts that have previously been shown to experimentally induce out-of-body illusions (in healthy subjects). In light of these experimental findings and the patient's symptomatology we extend an earlier model of the role of vestibular signals in OBEs. Our results advocate the involvement of subcortical bodily mechanisms in the occurrence of OBEs.
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Cell-CAM 105 has been identified as a cell adhesion molecule (CAM) based on the ability of monospecific and monovalent anti-cell-CAM 105 antibodies to inhibit the reaggregation of rat hepatocytes. Although one would expect to find CAMs concentrated in the lateral membrane domain where adhesive interactions predominate, immunofluorescence analysis of rat liver frozen sections revealed that cell-CAM 105 was present exclusively in the bile canalicular (BC) domain of the hepatocyte. To more precisely define the in situ localization of cell-CAM 105, immunoperoxidase and electron microscopy were used to analyze intact and mechanically dissociated fixed liver tissue. Results indicate that although cell-CAM 105 is apparently restricted to the BC domain in situ, it can be detected in the pericanalicular region of the lateral membranes when accessibility to lateral membranes is provided by mechanical dissociation. In contrast, when hepatocytes were labeled following incubation in vitro under conditions used during adhesion assays, cell-CAM 105 had redistributed to all areas of the plasma membrane. Immunofluorescence analysis of primary hepatocyte cultures revealed that cell-CAM 105 and two other BC proteins were localized in discrete domains reminscent of BC while cell-CAM 105 was also present in regions of intercellular contact. These results indicate that the distribution of cell-CAM 105 under the experimental conditions used for cell adhesion assays differs from that in situ and raises the possibility that its adhesive function may be modulated by its cell surface distribution. The implications of these and other findings are discussed with regard to a model for BC formation.^ Analysis of molecular events involved in BC formation would be accelerated if an in vitro model system were available. Although BC formation in culture has previously been observed, repolarization of cell-CAM 105 and two other domain-specific membrane proteins was incomplete. Since DMSO had been used by Isom et al. to maintain liver-specific gene expression in vitro, the effect of this differentiation system on the polarity of these membrane proteins was examined. Based on findings presented here, DMSO apparently prolongs the expression and facilitates polarization of hepatocyte membrane proteins in vitro. ^
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Pollen and spores from a deep-sea core located west of the Niger Delta record an uninterrupted area of lowland rain forest in West Africa from Guinea to Cameroon during the last Interglacial and the early Holocene. During other periods of the last 150 ka, a savanna corridor between the western - Guinean - and the eastern - Congolian - part of the African lowland rain forest existed. This so-called Dahomey Gap had its largest extension during Glacial Stages 6, 4, 3, and 2. Reduced surface salinity in the eastern Gulf of Guinea as recorded by dinoflagellate cysts indicates sufficient precipitation for extensive forest growth during Stages 5 and 1. The large modern extension of dry forest and savanna in West Africa cannot be solely explained by climatic factors. Mangrove expansion in and west of the Niger Delta was largest during the phases of sea-level rise of Stages 5 and 1. During Stages 6, 4, 3, and 2, shelf areas were exposed and the area of the mangrove swamps was minimal.