944 resultados para least mean-square methods
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PURPOSE: Chemotherapy (CT) combined with radiation therapy (RT) is the standard treatment for limited disease small-cell lung cancer (LDSCLC). Many questions including RT dose, fractionation, and sequence of RT/CT administration remain controversial. In this paper, we retrospectively assessed the outcome of patients with LDSCLC treated with radiation of at least 50 Gy.METHODS AND MATERIALS: From December 1997 to January 2006, 69 consecutive patients with LDSCLC were treated at our institutions. Treatment consisted of at least 4 cycles of CT, and 3D conformal thoracic RT. The median age was 61 years (range, 37-78 years). Sequential or concomitant CT/RT was given in 47 (68%) and 22 (32%) of the patients, respectively. The median RT dose was 60 Gy. Prophylactic cranial irradiation (PCI) was administered in 47 (68%) patients.RESULTS: With a median follow-up of 36 months (range, 6-107), 16 patients were alive without disease. The median overall survival time was 24 months, with a 3-year survival rate of 29%. The 3-year disease-free survival (DFS) and loco-regional control (LRC) rates were 23% and 60%, respectively. A better DFS was significantly associated with performance status (PS) 0 (p = 0.004), complete response to treatment (p = 0.03), and PCI group (p = 0.03). A trend towards improved overall survival (OS) was observed for patients who underwent PCI (p = 0.07). Patients treated with sequential CT/RT had a better outcome than those treated with concomitant treatment (3-year DFS rate 27% vs. 13%; p = 0.04). However, PCI was delivered more frequently for the sequential group. No significant dose-response relationship was found in terms of LRC. The multivariate analysis showed that complete response to treatment was the only significant factor for OS.CONCLUSION: Complete response to treatment was the most important factor for OS. A better DFS was significantly associated with the PCI group. We did not find a significant difference in outcome between patients receiving doses of 60 Gy or more and patients receiving 60 Gy or less.
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Whereas numerical modeling using finite-element methods (FEM) can provide transient temperature distribution in the component with enough accuracy, it is of the most importance the development of compact dynamic thermal models that can be used for electrothermal simulation. While in most cases single power sources are considered, here we focus on the simultaneous presence of multiple sources. The thermal model will be in the form of a thermal impedance matrix containing the thermal impedance transfer functions between two arbitrary ports. Eachindividual transfer function element ( ) is obtained from the analysis of the thermal temperature transient at node ¿ ¿ after a power step at node ¿ .¿ Different options for multiexponential transient analysis are detailed and compared. Among the options explored, small thermal models can be obtained by constrained nonlinear least squares (NLSQ) methods if the order is selected properly using validation signals. The methods are applied to the extraction of dynamic compact thermal models for a new ultrathin chip stack technology (UTCS).
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The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransfer functions (PTF) mainly saving time and reducing cost. Great differences among soils, however, can yield non desirable results when applying this method. This study discusses the application of developed PTFs by several authors using a variety of soils of different characteristics, to evaluate soil water contents of two Brazilian lowland soils. Comparisons are made between PTF evaluated data and field measured data, using statistical and geostatistical tools, like mean error, root mean square error, semivariogram, cross-validation, and regression coefficient. The eight tested PTFs to evaluate gravimetric soil water contents (Ug) at the tensions of 33 kPa and 1,500 kPa presented a tendency to overestimate Ug 33 kPa and underestimate Ug1,500 kPa. The PTFs were ranked according to their performance and also with respect to their potential in describing the structure of the spatial variability of the set of measured values. Although none of the PTFs have changed the distribution pattern of the data, all resulted in mean and variance statistically different from those observed for all measured values. The PTFs that presented the best predictive values of Ug33 kPa and Ug1,500 kPa were not the same that had the best performance to reproduce the structure of spatial variability of these variables.
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This study aimed to determine changes in spring-mass model (SMM) characteristics, plantar pressures, and muscle activity induced by the repetition of sprints in soccer-specific conditions; i.e., on natural grass with soccer shoes. Thirteen soccer players performed 6 × 20 m sprints interspersed with 20 s of passive recovery. Plantar pressure distribution was recorded via an insole pressure recorder device divided into nine areas for analysis. Stride temporal parameters allowed to estimate SMM characteristics. Surface electromyographic activity was monitored for vastus lateralis, rectus femoris, and biceps femoris muscles. Sprint time, contact time, and total stride duration lengthened from the first to the last repetition (+6.7, +12.9, and +9.3%; all P < 0.05), while flight time, swing time, and stride length remained constant. Stride frequency decrease across repetitions approached significance (-6.8%; P = 0.07). No main effect of the sprint number or any significant interaction between sprint number and foot region was found for maximal force, mean force, peak pressure and mean pressure (all P > 0.05). Center of mass vertical displacement increased (P < 0.01) with time, together with unchanged (both P > 0.05) peak vertical force and leg compression. Vertical stiffness decreased (-15.9%; P < 0.05) across trials, whereas leg stiffness changes were not significant (-5.9%; P > 0.05). Changes in root mean square activity of the three tested muscles over sprint repetitions were not significant. Although repeated sprinting on natural grass with players wearing soccer boots impairs their leg-spring behavior (vertical stiffness), there is no substantial concomitant alterations in muscle activation levels or plantar pressure patterns.
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Pedotransfer functions (PTF) were developed to estimate the parameters (α, n, θr and θs) of the van Genuchten model (1980) to describe soil water retention curves. The data came from various sources, mainly from studies conducted by universities in Northeast Brazil, by the Brazilian Agricultural Research Corporation (Embrapa) and by a corporation for the development of the São Francisco and Parnaíba river basins (Codevasf), totaling 786 retention curves, which were divided into two data sets: 85 % for the development of PTFs, and 15 % for testing and validation, considered independent data. Aside from the development of general PTFs for all soils together, specific PTFs were developed for the soil classes Ultisols, Oxisols, Entisols, and Alfisols by multiple regression techniques, using a stepwise procedure (forward and backward) to select the best predictors. Two types of PTFs were developed: the first included all predictors (soil density, proportions of sand, silt, clay, and organic matter), and the second only the proportions of sand, silt and clay. The evaluation of adequacy of the PTFs was based on the correlation coefficient (R) and Willmott index (d). To evaluate the PTF for the moisture content at specific pressure heads, we used the root mean square error (RMSE). The PTF-predicted retention curve is relatively poor, except for the residual water content. The inclusion of organic matter as a PTF predictor improved the prediction of parameter a of van Genuchten. The performance of soil-class-specific PTFs was not better than of the general PTF. Except for the water content of saturated soil estimated by particle size distribution, the tested models for water content prediction at specific pressure heads proved satisfactory. Predictions of water content at pressure heads more negative than -0.6 m, using a PTF considering particle size distribution, are only slightly lower than those obtained by PTFs including bulk density and organic matter content.
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This study aimed to examine the effects of a 5-h hilly run on ankle plantar (PF) and dorsal flexor (DF) force and fatigability. It was hypothesised that DF fatigue/fatigability would be greater than PF fatigue/fatigability. Eight male trail long distance runners (42.5 ± 5.9 years) were tested for ankle PF and DF maximal voluntary isokinetic contraction strength and fatigue resistance tests (percent decrement score), maximal voluntary and electrically evoked isometric contraction strength before and after the run. Maximal EMG root mean square (RMS(max)) and mean power frequency (MPF) values of the tibialis anterior (TA), gastrocnemius lateralis (GL) and soleus (SOL) EMG activity were calculated. The peak torque of the potentiated high- and low-frequency doublets and the ratio of paired stimulation peak torques at 10 Hz over 100 Hz (Db10:100) were analysed for PF. Maximal voluntary isometric contraction strength of PF decreased from pre- to post-run (-17.0 ± 6.2%; P < 0.05), but no significant decrease was evident for DF (-7.9 ± 6.2%). Maximal voluntary isokinetic contraction strength and fatigue resistance remained unchanged for both PF and DF. RMS(max) SOL during maximal voluntary isometric contraction and RMS(max) TA during maximal voluntary isokinetic contraction were decreased (P < 0.05) after the run. For MPF, a significant decrease for TA (P < 0.05) was found and the ratio Db10:100 decreased for PF (-6.5 ± 6.0%; P < 0.05). In conclusion, significant isometric strength loss was only detected for PF after a 5-h hilly run and was partly due to low-frequency fatigue. This study contradicted the hypothesis that neuromuscular alterations due to prolonged hilly running are predominant for DF.
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We have shown that finite-size effects in the correlation functions away from equilibrium may be introduced through dimensionless numbers: the Nusselt numbers, accounting for both the nature of the boundaries and the size of the system. From an analysis based on fluctuating hydrodynamics, we conclude that the mean-square fluctuations satisfy scaling laws, since they depend only on the dimensionless numbers in addition to reduced variables. We focus on the case of diffusion modes and describe some physical situations in which finite-size effects may be relevant.
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Using the experimental data of Paret and Tabeling [Phys. Rev. Lett. 79, 4162 (1997)] we consider in detail the dispersion of particle pairs by a two-dimensional turbulent flow and its relation to the kinematic properties of the velocity field. We show that the mean square separation of a pair of particles is governed by rather rare, extreme events and that the majority of initially close pairs are not dispersed by the flow. Another manifestation of the same effect is the fact that the dispersion of an initially dense cluster is not the result of homogeneously spreading the particles within the whole system. Instead it proceeds through a splitting into smaller but also dense clusters. The statistical nature of this effect is discussed.
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In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.
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BACKGROUND CONTEXT: Kyphotic deformities with sagittal imbalance of the spine can be treated with spinal osteotomies. Those procedures are known to have a high incidence of neurological complications, in particular at the thoracic level. Motor evoked potentials (MEPs) have been widely used in helping to avoid major neurological deficits postoperatively. Previous reports have shown that a significant proportion of such cases present with important transcranial MEP (Tc-MEP) changes during surgery with some of them being predictive of postoperative deficits. PURPOSE: Our aim was to study Tc-MEP changes in a consecutive series of patients and correlate them with clinical parameters and radiological changes. STUDY DESIGN/SETTING: Retrospective case notes study from a prospective patient register. PATIENT SAMPLE: Eighteen patients undergoing posterior shortening osteotomies (nine at thoracic and nine at lumbar levels) for kyphosis of congenital, degenerative, inflammatory, or post-traumatic origin were included. OUTCOME MEASURES: Loss of at least 80% of Tc-MEP signal expressed as the area under the curve percentual change, of at least one muscle. METHODS: We studied the relation between outcome measure (80% Tc-MEP loss in at least one muscle group) and amount of posterior vertebral body shortening as well as angular correction measured on computed tomography scans, occurrence of postoperative deficits, intraoperative blood pressure at the time of the osteotomy, and hemoglobin (Hb) change. RESULTS: All patients showed significant Tc-MEP changes. In particular, greater than 80% MEP loss in at least one muscle group was observed in five of nine patients in the thoracic group and four of nine patients in the lumbar group. No surgical maneuver was undertaken as a result of this loss in an effort to improve motor responses other than verifying the stability of the construct and the extent of the decompression. Four patients developed postoperative deficits of radicular origin, three of them recovering fully at 3 months. No relation was found between intraoperative blood pressure, Hb changes, and Tc-MEP changes. Severity of Tc-MEP loss did not correlate with postoperative deficits. Shortening of more than 10 mm was linked to more severe Tc-MEP changes in the thoracic group. CONCLUSIONS: Transcranial MEP changes during spinal shortening procedures are common and do not appear to predict severe postoperative deficits. Total loss of Tc-MEP (not witnessed in our series) might require a more drastic approach with possible reversal of the correction and wake-up test.
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The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the adequate performance and pertinence of this methodology to estimate complex phenomena, such as solar radiation.
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The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.
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The objective of this work was to parameterize, calibrate, and validate a new version of the soybean growth and yield model developed by Sinclair, under natural field conditions in northeastern Amazon. The meteorological data and the values of soybean growth and leaf area were obtained from an agrometeorological experiment carried out in Paragominas, PA, Brazil, from 2006 to 2009. The climatic conditions during the experiment were very distinct, with a slight reduction in rainfall in 2007, due to the El Niño phenomenon. There was a reduction in the leaf area index (LAI) and in biomass production during this year, which was reproduced by the model. The simulation of the LAI had root mean square error (RMSE) of 0.55 to 0.82 m² m-2, from 2006 to 2009. The simulation of soybean yield for independent data showed a RMSE of 198 kg ha-1, i.e., an overestimation of 3%. The model was calibrated and validated for Amazonian climatic conditions, and can contribute positively to the improvement of the simulations of the impacts of land use change in the Amazon region. The modified version of the Sinclair model is able to adequately simulate leaf area formation, total biomass, and soybean yield, under northeastern Amazon climatic conditions.
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This study compares the effects of two short multiple-sprint exercise (MSE) (6 × 6 s) sessions with two different recovery durations (30 s or 180 s) on the slow component of oxygen uptake ([Formula: see text]O(2)) during subsequent high-intensity exercise. Ten male subjects performed a 6-min cycling test at 50% of the difference between the gas exchange threshold and [Formula: see text]O(2peak) (Δ50). Then, the subjects performed two MSEs of 6 × 6 s separated by two intersprint recoveries of 30 s (MSE(30)) and 180 s (MSE(180)), followed 10 min later by the Δ50 (Δ50(30) and Δ50(180), respectively). Electromyography (EMG) activities of the vastus medialis and lateralis were measured throughout each exercise bout. During MSE(30), muscle activity (root mean square) increased significantly (p ≤ 0.04), with a significant leftward-shifted median frequency of the power density spectrum (MDF; p ≤ 0.01), whereas MDF was significantly rightward-shifted during MSE(180) (p = 0.02). The mean [Formula: see text]O(2) value was significantly higher in MSE(30) than in MSE(180) (p < 0.001). During Δ50(30), [Formula: see text]O(2) and the deoxygenated hemoglobin ([HHb]) slow components were significantly reduced (-27%, p = 0.02, and -34%, p = 0.003, respectively) compared with Δ50. There were no significant modifications of the [Formula: see text]O(2) slow component in Δ50(180) compared with Δ50 (p = 0.32). The neuromuscular and metabolic adaptations during MSE(30) (preferential activation of type I muscle fibers evidenced by decreased MDF and a greater aerobic metabolism contribution to the required energy demands), but not during MSE(180), may lead to reduced [Formula: see text]O(2) and [HHb] slow components, suggesting an alteration in motor units recruitment profile (i.e., change in the type of muscle fibers recruited) and (or) an improved muscle O(2) delivery during subsequent exercise.
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The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R²), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century.