942 resultados para Current Density Mapping Method
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Anew thermodynamic approach has been developed in this paper to analyze adsorption in slitlike pores. The equilibrium is described by two thermodynamic conditions: the Helmholtz free energy must be minimal, and the grand potential functional at that minimum must be negative. This approach has led to local isotherms that describe adsorption in the form of a single layer or two layers near the pore walls. In narrow pores local isotherms have one step that could be either very sharp but continuous or discontinuous benchlike for a definite range of pore width. The latter reflects a so-called 0 --> 1 monolayer transition. In relatively wide pores, local isotherms have two steps, of which the first step corresponds to the appearance of two layers near the pore walls, while the second step corresponds to the filling of the space between these layers. All features of local isotherms are in agreement with the results obtained from the density functional theory and Monte Carlo simulations. The approach is used for determining pore size distributions of carbon materials. We illustrate this with the benzene adsorption data on activated carbon at 20, 50, and 80 degreesC, argon adsorption on activated carbon Norit ROX at 87.3 K, and nitrogen adsorption on activated carbon Norit R1 at 77.3 K.
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A range of lasers. is now available for use in dentistry. This paper summarizes key current and emerging applications, for lasers in clinical practice. A major diagnostic application of low power lasers is the detection of caries, using fluorescence elicited from hydroxyapatite or from bacterial by-products. Laser fluorescence is an effective method for detecting and quantifying incipient occlusal and cervical,carious lesions, and with further refinement could be used in the, same manner for proximal lesions. Photoactivated dye techniques have been developed which use low power lasers to elicit a photochemical reaction, Photoactivated dye techniques' can be used to disinfect root canals, periodontal pockets, cavity preparations and sites of peri-implantitis. Using similar principles, more powerful lasers tan be used for photodynamic therapy in the treatment of malignancies of the oral mucosa. Laser-driven photochemical reactions can also be used for tooth whitening. In combination with fluoride, laser irradiation can improve the resistance of tooth structure to demineralization, and this application is of particular benefit for susceptible sites in high caries risk patients. Laser technology for caries' removal, cavity preparation and soft tissue surgery is at a high state of refinement, having had several decades of development up to the present time. Used in conjunction with or as a replacement for traditional methods, it is expected that specific laser technologies will become an essential component of contemporary dental practice over the next decade.
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Blasting has been the most frequently used method for rock breakage since black powder was first used to fragment rocks, more than two hundred years ago. This paper is an attempt to reassess standard design techniques used in blasting by providing an alternative approach to blast design. The new approach has been termed asymmetric blasting. Based on providing real time rock recognition through the capacity of measurement while drilling (MWD) techniques, asymmetric blasting is an approach to deal with rock properties as they occur in nature, i.e., randomly and asymmetrically spatially distributed. It is well accepted that performance of basic mining operations, such as excavation and crushing rely on a broken rock mass which has been pre conditioned by the blast. By pre-conditioned we mean well fragmented, sufficiently loose and with adequate muckpile profile. These muckpile characteristics affect loading and hauling [1]. The influence of blasting does not end there. Under the Mine to Mill paradigm, blasting has a significant leverage on downstream operations such as crushing and milling. There is a body of evidence that blasting affects mineral liberation [2]. Thus, the importance of blasting has increased from simply fragmenting and loosing the rock mass, to a broader role that encompasses many aspects of mining, which affects the cost of the end product. A new approach is proposed in this paper which facilitates this trend 'to treat non-homogeneous media (rock mass) in a non-homogeneous manner (an asymmetrical pattern) in order to achieve an optimal result (in terms of muckpile size distribution).' It is postulated there are no logical reasons (besides the current lack of means to infer rock mass properties in the blind zones of the bench and onsite precedents) for drilling a regular blast pattern over a rock mass that is inherently heterogeneous. Real and theoretical examples of such a method are presented.
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A new modeling approach-multiple mapping conditioning (MMC)-is introduced to treat mixing and reaction in turbulent flows. The model combines the advantages of the probability density function and the conditional moment closure methods and is based on a certain generalization of the mapping closure concept. An equivalent stochastic formulation of the MMC model is given. The validity of the closuring hypothesis of the model is demonstrated by a comparison with direct numerical simulation results for the three-stream mixing problem. (C) 2003 American Institute of Physics.
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Free-space optical interconnects (FSOIs), made up of dense arrays of vertical-cavity surface-emitting lasers, photodetectors and microlenses can be used for implementing high-speed and high-density communication links, and hence replace the inferior electrical interconnects. A major concern in the design of FSOIs is minimization of the optical channel cross talk arising from laser beam diffraction. In this article we introduce modifications to the mode expansion method of Tanaka et al. [IEEE Trans. Microwave Theory Tech. MTT-20, 749 (1972)] to make it an efficient tool for modelling and design of FSOIs in the presence of diffraction. We demonstrate that our modified mode expansion method has accuracy similar to the exact solution of the Huygens-Kirchhoff diffraction integral in cases of both weak and strong beam clipping, and that it is much more accurate than the existing approximations. The strength of the method is twofold: first, it is applicable in the region of pronounced diffraction (strong beam clipping) where all other approximations fail and, second, unlike the exact-solution method, it can be efficiently used for modelling diffraction on multiple apertures. These features make the mode expansion method useful for design and optimization of free-space architectures containing multiple optical elements inclusive of optical interconnects and optical clock distribution systems. (C) 2003 Optical Society of America.
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OBJECTIVES: The current study set out to investigate alcohol availability in a densely populated, residential area of suburban São Paulo associated with high levels of social deprivation and violence. Gun-related deaths and a heavy concentration of alcohol outlets are notable features of the area surveyed. Given the strong evidence for a link between alcohol availability and a number of alcohol-related problems, including violent crime, measures designed to reduce accessibility have become a favored choice for alcohol prevention programs in recent years. METHODS: The interviewers were 24 residents of the area who were trained for the study. It was selected an area of nineteen streets, covering a total distance of 3.7 km. A profile of each alcohol outlet available on the area was recorded. RESULTS: One hundred and seven alcohol outlets were recorded. The number of other properties in the same area was counted at 1,202. Two measures of outlet density may thus be calculated: the number of outlets per kilometer of roadway (29 outlets/km); and the proportion of all properties that sold alcohol (1 in 12). CONCLUSIONS: The results of this study is compared with others which are mainly from developed countries and shown that the area studied have the highest density of alcohol outlet density ever recorded in the medical literature. The implication of this data related to the violence of the region is discussed. By generating a profile of alcohol sales and selling points, it was hoped to gain a better understanding of alcohol access issues within the sample area. Future alcohol prevention policy would be well served by such knowledge.
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Tese de Doutoramento, Ciências do Mar (Biologia Marinha)
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OBJECTIVE: To estimate the prevalence and analyze risk factors associated to osteoporosis and low-trauma fracture in women. METHODS: Cross-sectional study including a total of 4,332 women older than 40 attending primary care services in the Greater São Paulo, Southeastern Brazil, between 2004 and 2007. Anthropometrical and gynecological data and information about lifestyle habits, previous fracture, medical history, food intake and physical activity were obtained through individual quantitative interviews. Low-trauma fracture was defined as that resulting from a fall from standing height or less in individuals 50 years or older. Multiple logistic regression models were designed having osteoporotic fracture and bone mineral density (BMD) as the dependent variables and all other parameters as the independent ones. The significance level was set at p<0.05. RESULTS: The prevalence of osteoporosis and osteoporotic fractures was 33% and 11.5%, respectively. The main risk factors associated with low bone mass were age (OR=1.07; 95% CI: 1.06;1.08), time since menopause (OR=2.16; 95% CI: 1.49;3.14), previous fracture (OR=2.62; 95% CI: 2.08;3.29) and current smoking (OR=1.45; 95% CI: 1.13;1.85). BMI (OR=0.88; 95% CI: 0.86;0.89), regular physical activity (OR=0.78; 95% CI: 0.65;0.94) and hormone replacement therapy (OR=0.43; 95% CI: 0.33;0.56) had a protective effect on bone mass. Risk factors significantly associated with osteoporotic fractures were age (OR=1.05; 95% CI: 1.04;1.06), time since menopause (OR=4.12; 95% CI: 1.79;9.48), familial history of hip fracture (OR=3.59; 95% CI: 2.88;4.47) and low BMD (OR=2.28; 95% CI: 1.85;2.82). CONCLUSIONS: Advanced age, menopause, low-trauma fracture and current smoking are major risk factors associated with low BMD and osteoporotic fracture. The clinical use of these parameters to identify women at higher risk for fractures might be a reasonable strategy to improve the management of osteoporosis.
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Bread is consumed worldwide by man, thus contributing to the regular ingestion of certain inorganic species such as chloride. It controls the blood pressure if associated to a sodium intake and may increase the incidence of stomach ulcer. Its routine control should thus be established by means of quick and low cost procedures. This work reports a double- channel flow injection analysis (FIA) system with a new chloride sensor for the analysis of bread. All solutions are prepared in water and necessary ionic strength adjustments are made on-line. The body of the indicating electrode is made from a silver needle of 0.8 mm i.d. with an external layer of silver chloride. These devices were constructed with different lengths. Electrodes of 1.0 to 3.0 cm presented better analytical performance. The calibration curves under optimum conditions displayed Nernstian behaviour, with average slopes of 56 mV decade-1, with sampling rates of 60 samples h-1. The method was applied to analyze several kinds of bread, namely pão de trigo, pão integral, pão de centeio, pão de mistura, broa de milho, pão sem sal, pão meio sal, pão-de-leite, and pão de água. The accuracy and precision of the potentiometric method were ascertained by comparison to a spectrophotometric method of continuous segmented flow. These methods were validated against ion-chromatography procedures.
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Many-core platforms based on Network-on-Chip (NoC [Benini and De Micheli 2002]) present an emerging technology in the real-time embedded domain. Although the idea to group the applications previously executed on separated single-core devices, and accommodate them on an individual many-core chip offers various options for power savings, cost reductions and contributes to the overall system flexibility, its implementation is a non-trivial task. In this paper we address the issue of application mapping onto a NoCbased many-core platform when considering fundamentals and trends of current many-core operating systems, specifically, we elaborate on a limited migrative application model encompassing a message-passing paradigm as a communication primitive. As the main contribution, we formulate the problem of real-time application mapping, and propose a three-stage process to efficiently solve it. Through analysis it is assured that derived solutions guarantee the fulfilment of posed time constraints regarding worst-case communication latencies, and at the same time provide an environment to perform load balancing for e.g. thermal, energy, fault tolerance or performance reasons.We also propose several constraints regarding the topological structure of the application mapping, as well as the inter- and intra-application communication patterns, which efficiently solve the issues of pessimism and/or intractability when performing the analysis.
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Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometers require controlled current sources in order to get accurate flux density with respect to its magnet. The main elements of the proposed solution are a power semiconductor, a DC voltage source and the magnet. The power semiconductor is commanded in order to get a linear control of the flux density. To implement the flux density control, a Hall Effect sensor is used. Furthermore, the dynamic behavior of the current source is analyzed and compared when using a PI controller and a PD2I controller.
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Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.
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OBJECTIVE To analyze the methodology used for assessing the spatial distribution of specialized cardiac care units. METHODS A modeling and simulation method was adopted for the practical application of cardiac care service in the state of Santa Catarina, Southern Brazil, using the p-median model. As the state is divided into 21 health care regions, a methodology which suggests an arrangement of eight intermediate cardiac care units was analyzed, comparing the results obtained using data from 1996 and 2012. RESULTS Results obtained using data from 2012 indicated significant changes in the state, particularly in relation to the increased population density in the coastal regions. The current study provided a satisfactory response, indicated by the homogeneity of the results regarding the location of the intermediate cardiac care units and their respective regional administrations, thereby decreasing the average distance traveled by users to health care units, located in higher population density areas. The validity of the model was corroborated through the analysis of the allocation of the median vertices proposed in 1996 and 2012. CONCLUSIONS The current spatial distribution of specialized cardiac care units is more homogeneous and reflects the demographic changes that have occurred in the state over the last 17 years. The comparison between the two simulations and the current configuration showed the validity of the proposed model as an aid in decision making for system expansion.
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Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometers require controlled current sources in order to get accurate flux density with respect to its magnet. The main elements of the proposed solution are a power semiconductor, a DC voltage source and the magnet. The power semiconductor is commanded in order to get a linear control of the flux density. To implement the flux density control, a Hall Effect sensor is used. Furthermore, the dynamic behavior of the current source is analyzed and compared when using a PI controller and a PD2I controller.