996 resultados para Sequential distribution


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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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There is a continuous search for theoretical methods that are able to describe the effects of the liquid environment on molecular systems. Different methods emphasize different aspects, and the treatment of both the local and bulk properties is still a great challenge. In this work, the electronic properties of a water molecule in liquid environment is studied by performing a relaxation of the geometry and electronic distribution using the free energy gradient method. This is made using a series of steps in each of which we run a purely molecular mechanical (MM) Monte Carlo Metropolis simulation of liquid water and subsequently perform a quantum mechanical/molecular mechanical (QM/MM) calculation of the ensemble averages of the charge distribution, atomic forces, and second derivatives. The MP2/aug-cc-pV5Z level is used to describe the electronic properties of the QM water. B3LYP with specially designed basis functions are used for the magnetic properties. Very good agreement is found for the local properties of water, such as geometry, vibrational frequencies, dipole moment, dipole polarizability, chemical shift, and spin-spin coupling constants. The very good performance of the free energy method combined with a QM/MM approach along with the possible limitations are briefly discussed.

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A combination of changes in the species composition of the radiolarian populations, and in the sediment chemical composition (content and mass accumulation rates of carbonate, organic carbon, and selected major and trace elements, with special attention paid to Ba) is used to reconstruct the variations in upwelling activity over the last 250 kyr in the Socotra gyre area (Somali-Socotra upwelling system, NW Indian Ocean). In the Socotra gyre (Core MD 962073 at 10°N), the variations in upwelling intensity are reconstructed by the upwelling radiolarian index (URI) while the thermocline/surface radiolarian index (TSRI) testifies to productivity variations during non-upwelling intervals. Despite an origin related both to marine and terrigenous inputs, the geochemical records of organic carbon, silica, and trace elements (Ba, P, Cu, and Zn) normalized to Al are controlled by the variations in surface paleoproductivity. The data indicate a continuous increase in upwelling intensity during the last 250 kyr with a maximum activity within the MIS 3, while high productivity periods in between the upwelling seasons occurred both during glacial and interglacial intervals. A comparison of our data with published observations from another gyre of the Somalian upwelling area located at 5°N in the Somali gyre area shows differences regarding periods of upwelling activity and their geochemical imprint. Three hypotheses are proposed to explain these differences: (1) changes in the planktonic community, resulting in more silica-rich deposits in the Socotra gyre, and more carbonate-rich deposits in the Somali gyre, that are controlled by differences in the source water of the upwelling; (2) a more important terrigenous input in the southern gyre; and (3) a different location of the sites relative to the geographic distribution of the upwelling gyres and hydrologic fronts.

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This paper empirically examines the different comparative advantages of two emerging economic giants, China and India, in relation to the different skill distribution patterns in each country. By utilizing industry export data on China and India from 1983 to 2000, we find that a country with a greater dispersion of skills (i.e., India, especially in the earlier years) has higher exports in industries with shorter production chains, whereas a country with a more equal dispersion of skills (i.e., China, especially in the later years) is found to have higher exports in industries with longer production chains. The causal relationship is fairly robust across different specifications. This empirical evidence supports our assumption that the likely mechanism for these results is the negative impact of low-skilled workers on input quality, which accumulates and becomes larger as the length of production chains and the proportion of low-skilled workers in the economy increase.

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The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

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In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm(3) from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented.

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A mathematical model that describes the operation of a sequential leach bed process for anaerobic digestion of organic fraction of municipal solid waste (MSW) is developed and validated. This model assumes that ultimate mineralisation of the organic component of the waste occurs in three steps, namely solubilisation of particulate matter, fermentation to volatile organic acids (modelled as acetic acid) along with liberation of carbon dioxide and hydrogen, and methanogenesis from acetate and hydrogen. The model incorporates the ionic equilibrium equations arising due to dissolution of carbon dioxide, generation of alkalinity from breakdown of solids and dissociation of acetic acid. Rather than a charge balance, a mass balance on the hydronium and hydroxide ions is used to calculate pH. The flow of liquid through the bed is modelled as occurring through two zones-a permeable zone with high flushing rates and the other more stagnant. Some of the kinetic parameters for the biological processes were obtained from batch MSW digestion experiments. The parameters for flow model were obtained from residence time distribution studies conducted using tritium as a tracer. The model was validated using data from leach bed digestion experiments in which a leachate volume equal to 10% of the fresh waste bed volume was sequenced. The model was then tested, without altering any kinetic or flow parameters, by varying volume of leachate that is sequenced between the beds. Simulations for sequencing/recirculating 5 and 30% of the bed volume are presented and compared with experimental results. (C) 2002 Elsevier Science B.V. All rights reserved.

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This paper presents a new multi-depot combined vehicle and crew scheduling algorithm, and uses it, in conjunction with a heuristic vehicle routing algorithm, to solve the intra-city mail distribution problem faced by Australia Post. First we describe the Australia Post mail distribution problem and outline the heuristic vehicle routing algorithm used to find vehicle routes. We present a new multi-depot combined vehicle and crew scheduling algorithm based on set covering with column generation. The paper concludes with a computational investigation examining the affect of different types of vehicle routing solutions on the vehicle and crew scheduling solution, comparing the different levels of integration possible with the new vehicle and crew scheduling algorithm and comparing the results of sequential versus simultaneous vehicle and crew scheduling, using real life data for Australia Post distribution networks.

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The main aim of the work is to investigate sequential pyrolysis of willow SRC using two different heating rates (25 and 1500 °C/min) between 320 and 520 °C. Thermogravimetric analysis (TGA) and pyrolysis - gas chromatography - mass spectroscopy (Py-GC-MS) have been used for this analysis. In addition, laboratory scale processing has been undertaken to compare product distribution from fast and slow pyrolysis at 500 °C. Fast pyrolysis was carried out using a 1 kg/h continuous bubbling fluidized bed reactor, and slow pyrolysis using a 100 g batch reactor. Findings from this study show that heating rate and pyrolysis temperatures have a significant influence on the chemical content of decomposition products. From the analytical sequential pyrolysis, an inverse relationship was seen between the total yield of furfural (at high heating rates) and 2-furanmethanol (at low heating rates). The total yield of 1,2-dihydroxybenzene (catechol) was found to be significant higher at low heating rates. The intermediates of catechol, 2-methoxy-4-(2-propenyl)phenol (eugenol); 2-methoxyphenol (guaiacol); 4-Hydroxy-3,5-dimethoxybenzaldehyde (syringaldehyde) and 4-hydroxy-3-methoxybenzaldehyde (vanillin), were found to be highest at high heating rates. It was also found that laboratory scale processing alters the pyrolysis bio-oil chemical composition, and the proportions of pyrolysis product yields. The GC-MS/FID analysis of fast and slow pyrolysis bio-oils reveals significant differences. © 2011 Elsevier Ltd. All rights reserved.

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The principled statistical application of Gaussian random field models used in geostatistics has historically been limited to data sets of a small size. This limitation is imposed by the requirement to store and invert the covariance matrix of all the samples to obtain a predictive distribution at unsampled locations, or to use likelihood-based covariance estimation. Various ad hoc approaches to solve this problem have been adopted, such as selecting a neighborhood region and/or a small number of observations to use in the kriging process, but these have no sound theoretical basis and it is unclear what information is being lost. In this article, we present a Bayesian method for estimating the posterior mean and covariance structures of a Gaussian random field using a sequential estimation algorithm. By imposing sparsity in a well-defined framework, the algorithm retains a subset of “basis vectors” that best represent the “true” posterior Gaussian random field model in the relative entropy sense. This allows a principled treatment of Gaussian random field models on very large data sets. The method is particularly appropriate when the Gaussian random field model is regarded as a latent variable model, which may be nonlinearly related to the observations. We show the application of the sequential, sparse Bayesian estimation in Gaussian random field models and discuss its merits and drawbacks.

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We report on a study conducted to extend our knowledge about the process of gaining a mental representation of music. Several studies, inspired by research on the statistical learning of language, have investigated statistical learning of sequential rules underlying tone sequences. Given that the mental representation of music correlates with distributional properties of music, we tested whether participants are able to abstract distributional information contained in tone sequences to form a mental representation. For this purpose, we created an unfamiliar music genre defined by an underlying tone distribution, to which 40 participants were exposed. Our stimuli allowed us to differentiate between sensitivity to the distributional properties contained in test stimuli and long term representation of the distributional properties of the music genre overall. Using a probe tone paradigm and a two-alternative forced choice discrimination task, we show that listeners are able to abstract distributional properties of music through mere exposure into a long term representation of music. This lends support to the idea that statistical learning is involved in the process of gaining musical knowledge.

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Sequential panel selection methods (spsms — procedures that sequentially use conventional panel unit root tests to identify I(0)I(0) time series in panels) are increasingly used in the empirical literature. We check the reliability of spsms by using Monte Carlo simulations based on generating directly the individual asymptotic pp values to be combined into the panel unit root tests, in this way isolating the classification abilities of the procedures from the small sample properties of the underlying univariate unit root tests. The simulations consider both independent and cross-dependent individual test statistics. Results suggest that spsms may offer advantages over time series tests only under special conditions.