777 resultados para Off-Tracking.
Resumo:
Empirical data indicate that the so-called ""Buddhism of yellow color"" that is predominantly associated with Japanese ""immigrant"" Buddhism, is constantly in decline in terms of ""explicit"" adherents. After some methodological observations, this article gives an overview of the relevant statistical data. The last part discusses possible reasons for these negative dynamics, referring to causes within Buddhist institutions, the ethnic community, and at the level of the individual.
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The dengue virus has a single-stranded positive-sense RNA genome of similar to 10.700 nucleotides with a single open reading frame that encodes three structural (C, prM, and E) and seven nonstructural (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) proteins. It possesses four antigenically distinct serotypes (DENV 1-4). Many phylogenetic studies address particularities of the different serotypes using convenience samples that are not conducive to a spatio-temporal analysis in a single urban setting. We describe the pattern of spread of distinct lineages of DENV-3 circulating in Sao Jose do Rio Preto, Brazil, during 2006. Blood samples from patients presenting dengue-like symptoms were collected for DENV testing. We performed M-N-PCR using primers based on NS5 for virus detection and identification. The fragments were purified from PCR mixtures and sequenced. The positive dengue cases were geo-coded. To type the sequenced samples, 52 reference sequences were aligned. The dataset generated was used for iterative phylogenetic reconstruction with the maximum likelihood criterion. The best demographic model, the rate of growth, rate of evolutionary change, and Time to Most Recent Common Ancestor (TMRCA) were estimated. The basic reproductive rate during the epidemics was estimated. We obtained sequences from 82 patients among 174 blood samples. We were able to geo-code 46 sequences. The alignment generated a 399-nucleotide-long dataset with 134 taxa. The phylogenetic analysis indicated that all samples were of DENV-3 and related to strains circulating on the isle of Martinique in 2000-2001. Sixty DENV-3 from Sao Jose do Rio Preto formed a monophyletic group (lineage 1), closely related to the remaining 22 isolates (lineage 2). We assumed that these lineages appeared before 2006 in different occasions. By transforming the inferred exponential growth rates into the basic reproductive rate, we obtained values for lineage 1 of R(0) = 1.53 and values for lineage 2 of R(0) = 1.13. Under the exponential model, TMRCA of lineage 1 dated 1 year and lineage 2 dated 3.4 years before the last sampling. The possibility of inferring the spatio-temporal dynamics from genetic data has been generally little explored, and it may shed light on DENV circulation. The use of both geographic and temporally structured phylogenetic data provided a detailed view on the spread of at least two dengue viral strains in a populated urban area.
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We studied copepod assemblage variability among years, seasons, and tidal states in the Mucuri River estuary (Bahia State, Brazil). Zooplankton samples were collected seasonally through five years (2002-2006) at three sampling stations, one of which was sampled over a complete tidal cycle (two ebb and two flood tides). Temperature, salinity, river flux, and rainfall data were collected. Winter and summer represented dry and wet seasons, respectively. Copepod abundances ranged from 40 to 63% of the total zooplankton assemblage and comprised 46 taxa, among which, common estuarine species such as Temora turbinata (first record for the studied area), Parvocalanus crassirostris, Acartia lilljeborgi, Oithona hebes were the most abundant (euryhaline species). Interannual and seasonal variations were most marked in stenohaline species, e.g.. Notodiaptomus sp. and Thermocyclops minutus; density variations of euryhaline species, which made up the majority of the abundant taxa, were most closely related to tides. Diversity and richness also followed an intertidal pattern of variation.
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Various molecular systems are available for epidemiological, genetic, evolutionary, taxonomic and systematic studies of innumerable fungal infections, especially those caused by the opportunistic pathogen C. albicans. A total of 75 independent oral isolates were selected in order to compare Multilocus Enzyme Electrophoresis (MLEE), Electrophoretic Karyotyping (EK) and Microsatellite Markers (Simple Sequence Repeats - SSRs), in their abilities to differentiate and group C. albicans isolates (discriminatory power), and also, to evaluate the concordance and similarity of the groups of strains determined by cluster analysis for each fingerprinting method. Isoenzyme typing was performed using eleven enzyme systems: Adh, Sdh, M1p, Mdh, Idh, Gdh, G6pdh, Asd, Cat, Po, and Lap (data previously published). The EK method consisted of chromosomal DNA separation by pulsed-field gel electrophoresis using a CHEF system. The microsatellite markers were investigated by PCR using three polymorphic loci: EF3, CDC3, and HIS3. Dendrograms were generated by the SAHN method and UPGMA algorithm based on similarity matrices (S(SM)). The discriminatory power of the three methods was over 95%, however a paired analysis among them showed a parity of 19.7-22.4% in the identification of strains. Weak correlation was also observed among the genetic similarity matrices (S(SM)(MLEE) x S(SM)(EK) x S(SM)(SSRs)). Clustering analyses showed a mean of 9 +/- 12.4 isolates per cluster (3.8 +/- 8 isolates/taxon) for MLEE, 6.2 +/- 4.9 isolates per cluster (4 +/- 4.5 isolates/taxon) for SSRs, and 4.1 +/- 2.3 isolates per cluster (2.6 +/- 2.3 isolates/taxon) for EK. A total of 45 (13%), 39(11.2%), 5 (1.4%) and 3 (0.9%) clusters pairs from 347 showed similarity (Si) of 0.1-10%, 10.1-20%, 20.1-30% and 30.1-40%, respectively. Clinical and molecular epidemiological correlation involving the opportunistic pathogen C. albicans may be attributed dependently of each method of genotyping (i.e., MLEE, EK, and SSRs) supplemented with similarity and grouping analysis. Therefore, the use of genotyping systems that give results which offer minimum disparity, or the combination of the results of these systems, can provide greater security and consistency in the determination of strains and their genetic relationships. (C) 2010 Elsevier B.V. All rights reserved.
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Special attention is given to cephalic structures of a species complex within the Notogynaphallia ( Platyhelminthes, Tricladida). Notogynaphallia muelleri is redescribed. The species possesses a cephalic musculo-glandular organ. Its glandular and muscular organization are similar to that previously observed in N. caissara and N. fita and to that herein described for N. abundans, N. ceciliae, N. ernesti, and N. graffi. Based on these unique cephalic specializations, a new genus is proposed for these seven species. Functionally, the musculo-glandular organ may be an adaptation for capturing and holding prey.
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Little information is available concerning early specialization and competitive success in judo across the early training years. Thus, the present objective was to verify the stability of individual competitive performance of a state-level championship for judo athletes who had been previously successful. For this, 406 athletes from six age groups (9 to 20+ years old) of each sex were followed for 10 years. Using recorded data from the Sao Paulo State Judo Federation beginning in 1999, the scores and standings for these judo players were analyzed. The proportion of medal winners during this period was not constant, differing from the grand mean in all groups of both 204 males and 202 females. At the end of this period, only 7% of the male and 5% of the female athletes had maintained their competitive levels. Successful competitive performance in early judo competition was not associated with success later in adulthood.
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Simulated annealing (SA) is an optimization technique that can process cost functions with degrees of nonlinearities, discontinuities and stochasticity. It can process arbitrary boundary conditions and constraints imposed on these cost functions. The SA technique is applied to the problem of robot path planning. Three situations are considered here: the path is represented as a polyline; as a Bezier curve; and as a spline interpolated curve. In the proposed SA algorithm, the sensitivity of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensitivity of each parameter is associated to its probability distribution in the definition of the next candidate. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
In this work, a stable MPC that maximizes the domain of attraction of the closed-loop system is proposed. The proposed approach is suitable to real applications in the sense that it accounts for the case of output tracking, it is offset free if the output target is reachable and minimizes the offset if some of the constraints are active at steady state. The new approach is based on the definition of a Minkowski functional related to the input and terminal constraints of the stable infinite horizon MPC. It is also shown that the domain of attraction is defined by the system model and the constraints, and it does not depend on the controller tuning parameters. The proposed controller is illustrated with small order examples of the control literature. (C) 2011 Elsevier Ltd. All rights reserved.
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A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.
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This paper deals with the problem of tracking target sets using a model predictive control (MPC) law. Some MPC applications require a control strategy in which some system outputs are controlled within specified ranges or zones (zone control), while some other variables - possibly including input variables - are steered to fixed target or set-point. In real applications, this problem is often overcome by including and excluding an appropriate penalization for the output errors in the control cost function. In this way, throughout the continuous operation of the process, the control system keeps switching from one controller to another, and even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. From a theoretical point of view, the control objective of this kind of problem can be seen as a target set (in the output space) instead of a target point, since inside the zones there are no preferences between one point or another. In this work, a stable MPC formulation for constrained linear systems, with several practical properties is developed for this scenario. The concept of distance from a point to a set is exploited to propose an additional cost term, which ensures both, recursive feasibility and local optimality. The performance of the proposed strategy is illustrated by simulation of an ill-conditioned distillation column. (C) 2010 Elsevier Ltd. All rights reserved.
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We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.
Resumo:
As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.
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In recent years, maize has become one of the main alternative crops for the autumn winter growing season in the central-western and southeastern regions of Brazil. However, water deficits, sub-optimal temperatures and low solar radiation levels are common problems that are experienced during this growing season by local farmers. One methodology to assess the impact of variable weather conditions on crop production is the use of crop simulation models. The goal of this study was to evaluate the effect of climate variability on maize yield for a subtropical region of Brazil. Specific objectives for this study were (1) to analyse the effect of El Nino Southern Oscillation (ENSO) on precipitation and air temperature for four locations in the state of Sao Paulo and (2) to analyse the impact of ENSO on maize grown off-season for the same four locations using a crop simulation model. For each site, historical weather data were categorised as belonging to one of three phases of ENSO: El Nino (warm sea surface temperature anomalies in the Pacific), La Nina (cool sea surface temperature anomalies) or neutral, based on an index derived from observed sea surface temperature anomalies. During El Nino, there is a tendency for an increase in the rainfall amount during May for the four selected locations, and also during April, mainly in three of the locations, resulting in an increase in simulated maize yield planted between February 15 and March 15. In general, there was a decrease in the simulated yield for maize grown off-season during neutral years. This study showed how a crop model can be used to assess the impact of climate variability on the yield of maize grown off-season in a subtropical region of Brazil. The outcomes of this study can be very useful for both policy makers and local farmers for agricultural planning and decision making. Copyright (C) 2009 Royal Meteorological Society
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Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.