990 resultados para HAND Model


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ABSTRACT One of the most relevant activities of Brazilian economy is agriculture. Among the main crops in Brazil, rice is one of high relevance. The state of Rio Grande do Sul, in Southern Brazil, is responsible for 68.7% of domestic production (IBGE, 2013). The goal of this study was to develop a low-cost methodology with a regional scope to identify suitable areas for irrigated rice cropping in this state, using spectro-temporal behavior of vegetation index by means of MODIS images and HAND model. The rice-cropped area of this study was the southern half of the State. Using the HAND model, flood areas were mapped to identify irrigated rice cultivation. We used multi-temporal images of vegetation index from MODIS sensor, covering the period from August 2001 to May 2012. To assess the results, we used data collected in the fields and cropped area information from IBGE. The results showed that the proposed methodology was satisfactory, with Kappa 0.92 and global accuracy of 98.18%. As result, MODIS sensor data and flood areas delineation by means of HAND model generated the estimate irrigated rice area for the area of study.

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Application of semi-distributed hydrological models to large, heterogeneous watersheds deals with several problems. On one hand, the spatial and temporal variability in catchment features should be adequately represented in the model parameterization, while maintaining the model complexity in an acceptable level to take advantage of state-of-the-art calibration techniques. On the other hand, model complexity enhances uncertainty in adjusted model parameter values, therefore increasing uncertainty in the water routing across the watershed. This is critical for water quality applications, where not only streamflow, but also a reliable estimation of the surface versus subsurface contributions to the runoff is needed. In this study, we show how a regularized inversion procedure combined with a multiobjective function calibration strategy successfully solves the parameterization of a complex application of a water quality-oriented hydrological model. The final value of several optimized parameters showed significant and consistentdifferences across geological and landscape features. Although the number of optimized parameters was significantly increased by the spatial and temporal discretization of adjustable parameters, the uncertainty in water routing results remained at reasonable values. In addition, a stepwise numerical analysis showed that the effects on calibration performance due to inclusion of different data types in the objective function could be inextricably linked. Thus caution should be taken when adding or removing data from an aggregated objective function.

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En la actualidad los conflictos internos son cada vez más permeables y sus vínculos más estrechos. Esta circunstancia significa que las acciones que tienen su origen en el exterior, afectan de manera creciente el desenvolvimiento de los antagonismos internos. Basándose en un enfoque transaccional, el autor estudia el fenómeno en la perspectiva de la seguridad interactiva y construye el modelo de ‘echar una mano’ que toma en cuenta cinco dimensiones y permite sistematizar las diferentes posibilidades de acción exterior en el desarrollo de la actual realidad conflictiva.---At the present moment internal conflicts are more permeable and have greater ties between them. This circumstance means that the actions that have foreign origin affect in a growing manner the development of internal antagonisms. Based on a transactional focus, the author studies the phenomena in the interactive security perspective and builds the “giving a hand model” that, upon taking into account five dimensions, allows to categorize the different foreign action possibilities in the development of the present conflictive reality.

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The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

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Kinesin is a processive motor protein: A single molecule can walk continuously along a microtubule for several micrometers, taking hundreds of 8-nm steps without dissociating. To elucidate the biochemical and structural basis for processivity, we have engineered a heterodimeric one-headed kinesin and compared its biochemical properties to those of the wild-type two-headed molecule. Our construct retains the functionally important neck and tail domains and supports motility in high-density microtubule gliding assays, though it fails to move at the single-molecule level. We find that the ATPase rate of one-headed kinesin is 3–6 s−1 and that detachment from the microtubule occurs at a similar rate (3 s−1). This establishes that one-headed kinesin usually detaches once per ATP hydrolysis cycle. Furthermore, we identify the rate-limiting step in the one-headed hydrolysis cycle as detachment from the microtubule in the ADP⋅Pi state. Because the ATPase and detachment rates are roughly an order of magnitude lower than the corresponding rates for two-headed kinesin, the detachment of one head in the homodimer (in the ADP⋅Pi state) must be accelerated by the other head. We hypothesize that this results from internal strain generated when the second head binds. This idea accords with a hand-over-hand model for processivity in which the release of the trailing head is contingent on the binding of the forward head. These new results, together with previously published ones, allow us to propose a pathway that defines the chemical and mechanical cycle for two-headed kinesin.

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For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.