988 resultados para model state durations


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The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

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This paper shows the insertion of corona effect in a transmission line model based on lumped elements. The development is performed considering a frequency-dependent line representation by cascade of pi sections and state equations. Hence, the detailed profile of currents and voltages along the line, described from a non-homogeneous system of differential equations, can be obtained directly in time domain applying numerical or analytic solution integration methods. The corona discharge model is also based on lumped elements and is implemented from the well-know Skilling-Umoto Model.

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Appendices (p. 1-14): A. Model state act for soil erosion and sediment control--B. Selected bibliography on sediment control.

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A systematic diagrammatic expansion for Gutzwiller wavefunctions (DE-GWFs) proposed very recently is used for the description of the superconducting (SC) ground state in the two-dimensional square-lattice t-J model with the hopping electron amplitudes t (and t') between nearest (and next-nearest) neighbors. For the example of the SC state analysis we provide a detailed comparison of the method's results with those of other approaches. Namely, (i) the truncated DE-GWF method reproduces the variational Monte Carlo (VMC) results and (ii) in the lowest (zeroth) order of the expansion the method can reproduce the analytical results of the standard Gutzwiller approximation (GA), as well as of the recently proposed 'grand-canonical Gutzwiller approximation' (called either GCGA or SGA). We obtain important features of the SC state. First, the SC gap at the Fermi surface resembles a d(x2-y2) wave only for optimally and overdoped systems, being diminished in the antinodal regions for the underdoped case in a qualitative agreement with experiment. Corrections to the gap structure are shown to arise from the longer range of the real-space pairing. Second, the nodal Fermi velocity is almost constant as a function of doping and agrees semi-quantitatively with experimental results. Third, we compare the

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The relationship between soil structure and the ability of soil to stabilize soil organic matter (SOM) is a key element in soil C dynamics that has either been overlooked or treated in a cursory fashion when developing SOM models. The purpose of this paper is to review current knowledge of SOM dynamics within the framework of a newly proposed soil C saturation concept. Initially, we distinguish SOM that is protected against decomposition by various mechanisms from that which is not protected from decomposition. Methods of quantification and characteristics of three SOM pools defined as protected are discussed. Soil organic matter can be: (1) physically stabilized, or protected from decomposition, through microaggregation, or (2) intimate association with silt and clay particles, and (3) can be biochemically stabilized through the formation of recalcitrant SOM compounds. In addition to behavior of each SOM pool, we discuss implications of changes in land management on processes by which SOM compounds undergo protection and release. The characteristics and responses to changes in land use or land management are described for the light fraction (LF) and particulate organic matter (POM). We defined the LF and POM not occluded within microaggregates (53-250 mum sized aggregates as unprotected. Our conclusions are illustrated in a new conceptual SOM model that differs from most SOM models in that the model state variables are measurable SOM pools. We suggest that physicochemical characteristics inherent to soils define the maximum protective capacity of these pools, which limits increases in SOM (i.e. C sequestration) with increased organic residue inputs.

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可重构模块星球机器人系统由母体和多个子机器人模块组成,单个模块可以独立运动和操作,多个模块可以重构组合成不同构形,模块采用非对称式轮手一体机构,具有姿态方位性和运动方向性,重构目的是组成在某种环境下更好地完成有向性运动的构形。基于此,提出矢量构形概念,将运动趋势方向和方位性融合到构形拓扑结构中。在模块矢量分析模型基础上,提出并构建状态构形矢量(State configuration vector,SCV)和状态构形矩阵(State configuration matrix,SCM),对非对称式单模块和整体构形的状态信息进行描述,同时支持预定义的数学变换操作,可以表达并触发模块的基础动作、构形重构。提出离散模块组合重构成目标构形的优化分析算法,通过实例仿真计算获得优化分析的选择结果。

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Quel est le pouvoir des normes internationales de droits humains ? Ces normes ont-elles un pouvoir politique? En s’appuyant sur le cas mexicain (entre 1988 et 2006), la thèse tente de répondre à trois questionnements. Le premier est lié à la trajectoire des normes: les défenseurs mexicains des droits humains cherchent-ils l’appui d’acteurs internationaux pour promouvoir les droits humains vis-à-vis leur gouvernement, tel que le suggère le modèle du boomerang ? Deuxièmement, il s’agit de comprendre l’impact du processus de diffusion des normes sur le respect des droits humains : les acteurs internationaux et nationaux qui défendent les droits humains parviennent-ils à influencer les décisions politiques gouvernementales, en matière de protection des droits humains ? Et finalement: ces groupes contribuent-ils à changer le cours du processus de démocratisation d’un État ? Les résultats de la recherche permettent de tirer quelques conclusions. La thèse confirme dans un premier temps la théorie du boomerang de Keck et Sikkink (1998), puisque les pressions domestiques en matière de droits humains deviennent efficaces au moment où les acteurs domestiques gagnent l’appui des acteurs internationaux. En ce qui concerne l’impact de la diffusion des normes internationales des droits humains sur leur protection gouvernementale, il semble que le gouvernement mexicain entre 1988 et 2006 réagisse aux pressions des acteurs qui diffusent les normes de droits humains par la mise en place d’institutions et de lois et non par une protection effective de ces droits. Un deuxième type d’impact, lié à la diffusion des normes en droits humains, est observé sur le processus de démocratisation. La thèse montre que les acteurs qui diffusent les normes en droits humains jouent un rôle dans la mise en place de réformes électorales, tout en contribuant à une redéfinition plus démocratique des rapports de pouvoir entre la société civile et l’État.

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El presente trabajo pretende mostrar algunos avances en el término “engagement”, y como puede ser implementado en las organizaciones, teniendo en cuenta los diferentes factores que intervienen, para que los trabajadores se sientan “engaged” dentro de la organización. Además busca relacionar las diferentes habilidades y tipos de liderazgo que los altos mandos utilizan con sus empleados y como éste afecta la productividad de los trabajadores en las organizaciones. Para esto, se realizó una investigación de las clases de liderazgo y los comportamientos de los altos mandos, que pueden afectar positiva y negativamente el vínculo y sentido de pertenencia que tienen los trabajadores con la empresa en la que trabajan. Considerando importante las habilidades del liderazgo transformacional, para lograr desarrollar algún grado de engagement en los trabajadores, lo cual genera a su vez, un alza en la productividad de sus resultados dentro de la organización.

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The Met Office Unified Model is run for a case observed during Intensive Observation Period 18 (IOP18) of the Convective Storms Initiation Project (CSIP). The aims are to identify the physical processes that lead to perturbation growth at the convective scale in response to model-state perturbations and to determine their sensitivity to the character of the perturbations. The case is strongly upper-level forced but with detailed mesoscale/convective-scale evolution that is dependent on smaller-scale processes. Potential temperature is perturbed within the boundary layer. The effects on perturbation growth of both the amplitude and typical scalelength of the perturbations are investigated and perturbations are applied either sequentially (every 30 min throughout the simulation) or at specific times. The direct effects (within one timestep) of the perturbations are to generate propagating Lamb and acoustic waves and produce generally small changes in cloud parameters and convective instability. In exceptional cases a perturbation at a specific gridpoint leads to switching of the diagnosed boundary-layer type or discontinuous changes in convective instability, through the generation or removal of a lid. The indirect effects (during the entire simulation) are changes in the intensity and location of precipitation and in the cloud size distribution. Qualitatively different behaviour is found for strong (1K amplitude) and weak (0.01K amplitude) perturbations, with faster growth after sunrise found only for the weaker perturbations. However, the overall perturbation growth (as measured by the root-mean-square error of accumulated precipitation) reaches similar values at saturation, regardless of the perturbation characterisation.

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Flood extents caused by fluvial floods in urban and rural areas may be predicted by hydraulic models. Assimilation may be used to correct the model state and improve the estimates of the model parameters or external forcing. One common observation assimilated is the water level at various points along the modelled reach. Distributed water levels may be estimated indirectly along the flood extents in Synthetic Aperture Radar (SAR) images by intersecting the extents with the floodplain topography. It is necessary to select a subset of levels for assimilation because adjacent levels along the flood extent will be strongly correlated. A method for selecting such a subset automatically and in near real-time is described, which would allow the SAR water levels to be used in a forecasting model. The method first selects candidate waterline points in flooded rural areas having low slope. The waterline levels and positions are corrected for the effects of double reflections between the water surface and emergent vegetation at the flood edge. Waterline points are also selected in flooded urban areas away from radar shadow and layover caused by buildings, with levels similar to those in adjacent rural areas. The resulting points are thinned to reduce spatial autocorrelation using a top-down clustering approach. The method was developed using a TerraSAR-X image from a particular case study involving urban and rural flooding. The waterline points extracted proved to be spatially uncorrelated, with levels reasonably similar to those determined manually from aerial photographs, and in good agreement with those of nearby gauges.

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Ensemble clustering (EC) can arise in data assimilation with ensemble square root filters (EnSRFs) using non-linear models: an M-member ensemble splits into a single outlier and a cluster of M−1 members. The stochastic Ensemble Kalman Filter does not present this problem. Modifications to the EnSRFs by a periodic resampling of the ensemble through random rotations have been proposed to address it. We introduce a metric to quantify the presence of EC and present evidence to dispel the notion that EC leads to filter failure. Starting from a univariate model, we show that EC is not a permanent but transient phenomenon; it occurs intermittently in non-linear models. We perform a series of data assimilation experiments using a standard EnSRF and a modified EnSRF by a resampling though random rotations. The modified EnSRF thus alleviates issues associated with EC at the cost of traceability of individual ensemble trajectories and cannot use some of algorithms that enhance performance of standard EnSRF. In the non-linear regimes of low-dimensional models, the analysis root mean square error of the standard EnSRF slowly grows with ensemble size if the size is larger than the dimension of the model state. However, we do not observe this problem in a more complex model that uses an ensemble size much smaller than the dimension of the model state, along with inflation and localisation. Overall, we find that transient EC does not handicap the performance of the standard EnSRF.

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Particle filters are fully non-linear data assimilation techniques that aim to represent the probability distribution of the model state given the observations (the posterior) by a number of particles. In high-dimensional geophysical applications the number of particles required by the sequential importance resampling (SIR) particle filter in order to capture the high probability region of the posterior, is too large to make them usable. However particle filters can be formulated using proposal densities, which gives greater freedom in how particles are sampled and allows for a much smaller number of particles. Here a particle filter is presented which uses the proposal density to ensure that all particles end up in the high probability region of the posterior probability density function. This gives rise to the possibility of non-linear data assimilation in large dimensional systems. The particle filter formulation is compared to the optimal proposal density particle filter and the implicit particle filter, both of which also utilise a proposal density. We show that when observations are available every time step, both schemes will be degenerate when the number of independent observations is large, unlike the new scheme. The sensitivity of the new scheme to its parameter values is explored theoretically and demonstrated using the Lorenz (1963) model.

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In general, particle filters need large numbers of model runs in order to avoid filter degeneracy in high-dimensional systems. The recently proposed, fully nonlinear equivalent-weights particle filter overcomes this requirement by replacing the standard model transition density with two different proposal transition densities. The first proposal density is used to relax all particles towards the high-probability regions of state space as defined by the observations. The crucial second proposal density is then used to ensure that the majority of particles have equivalent weights at observation time. Here, the performance of the scheme in a high, 65 500 dimensional, simplified ocean model is explored. The success of the equivalent-weights particle filter in matching the true model state is shown using the mean of just 32 particles in twin experiments. It is of particular significance that this remains true even as the number and spatial variability of the observations are changed. The results from rank histograms are less easy to interpret and can be influenced considerably by the parameter values used. This article also explores the sensitivity of the performance of the scheme to the chosen parameter values and the effect of using different model error parameters in the truth compared with the ensemble model runs.

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We investigate the influence of ail interaction between dark energy and dark matter upon the dynamics of galaxy clusters. We obtain file general Layser-Irvine equation in the presence of interactions, and find how, in that case. the virial theorem stands corrected. Using optical, X-ray and weak lensing data from 33 relaxed galaxy clusters, we put constraints on the strength of the coupling between the dark sectors. Available data Suggests that this coupling is small but positive, indicating that dark energy might be decaying into dark matter. Systematic effects between the several mass estimates, however, should be better known, before definitive conclusions oil the magnitude and significance of this coupling could be established. (C) 2009 Published by Elsevier B.V.

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This study examined, within the context of the Contingencies of Self-Worth model, state-based associations between self-esteem and body satisfaction using the experience sampling method. One hundred and forty-four adolescent girls (mean age = 14.28 years) completed up to 6 assessments per day for one week using Palm Digital Assistants, in addition to baseline measures of trait body satisfaction and self-esteem. Results showed considerable variation in both state-based constructs within days, and evidence of effects of body satisfaction on self-esteem, but not vice versa. Although these state-based associations were small in size and weakened as the time lag between assessments increased for the sample as a whole, individual differences in the magnitude of these effects were observed and predicted by trait self-esteem and body satisfaction. Collectively, these findings offer support for key tenets of the Contingencies of Self-Worth model.