978 resultados para IRRADIANCE PREDICTIONS


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We explored the interaction between radiation of different wavelength and jasmonic acid (JA) or brassinosteroids (BR) on leaf senescence-induced oxidative stress. Three approaches were used: 1) jasmonic acid insensitive1-1 (jai1-1) and brassinosteroid-deficient [dumpy (dpy)] mutants were treated with red (R) or far-red (FR) radiation; 2) phytochromedeficient aurea (au) and high pigment-1 (hp-1) (radiation exaggerated response) mutants were treated with methyl jasmonate (MeJA) or epibrassinolide (epiBL); and 3) double mutants au jai1-1 and au dpy were produced. Leaf chlorophyll content, lipid peroxidation, and antioxidant enzyme activities were determined. After senescence induction in detached leaves, we verified that the patterns of chlorophyll degradation of hormonal and photomorphogenic mutants were not significantly different in comparison with original cv. Micro-Tom (MT). Moreover, there was no significant change in lipid peroxidation measured as malondialdehyde (MDA) production, as well as catalase (CAT), ascorbate peroxidase (APX), and glutathione reductase (GR) activities in the hormonal mutants. Exogenous BR increased CAT and APX activities in MT, au, and hp-1. As concerns the double mutants, severe reduction in H2O2 production which was not accompanied by changes in MDA content, and CAT and APX activities was observed during senescence in au dpy. The results suggest that JA and BR do not participate in light signaling pathway during leaf senescence-induced oxidative stress. © 2013 Springer Science+Business Media Dordrecht.

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We examine the problem of combining Mexican inflation predictions or projections provided by a biweekly survey of professional forecasters. Consumer price inflation in Mexico is measured twice a month. We consider several combining methods and advocate the use of dimension reduction techniques whose performance is compared with different benchmark methods, including the simplest average prediction. Missing values in the database are imputed by two different databased methods. The results obtained are basically robust to the choice of the imputation method. A preliminary analysis of the data was based on its panel data structure and showed the potential usefulness of using dimension reduction techniques to combine the experts' predictions. The main findings are: the first monthly predictions are best combined by way of the first principal component of the predictions available; the best second monthly prediction is obtained by calculating the median prediction and is more accurate than the first one.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The present study aimed to assess the influence of curing distance on the loss of irradiance and power density of four curing light devices. The behavior in terms of power density of four different dental curing devices was analyzed (Valo, Elipar 2, Radii-Cal, and Optilux-401) using three different distances of photopolymerization (0 mm, 4 mm, and 8 mm). All devices had their power density measured using a MARC simulator. Ten measurements were made per device at each distance. The total amount of energy delivered and the required curing time to achieve 16 J/cm2 of energy was also calculated. Data were statistically analyzed with one-way analysis of variance and Tukey’s tests (p < 0.05). The curing distance significantly interfered with the loss of power density for all curing light devices, with the farthest distance generating the lowest power density and consequently the longer time to achieve an energy density of 16 J/cm2 (p < 0.01). Comparison of devices showed that Valo, in extra power mode, showed the best results at all distances, followed by Valo in high power mode, Valo in standard mode, Elipar 2, Radii-Cal, and Optilux-401 halogen lamp (p < 0.01). These findings indicate that all curing lights induced a significant loss of irradiance and total energy when the light was emitted farther from the probe. The Valo device in extra power mode showed the highest power density and the shortest time to achieve an energy density of 16 J/cm2 at all curing distances.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The aim of the present thesis was to investigate the influence of lower-limb joint models on musculoskeletal model predictions during gait. We started our analysis by using a baseline model, i.e., the state-of-the-art lower-limb model (spherical joint at the hip and hinge joints at the knee and ankle) created from MRI of a healthy subject in the Medical Technology Laboratory of the Rizzoli Orthopaedic Institute. We varied the models of knee and ankle joints, including: knee- and ankle joints with mean instantaneous axis of rotation, universal joint at the ankle, scaled-generic-derived planar knee, subject-specific planar knee model, subject-specific planar ankle model, spherical knee, spherical ankle. The joint model combinations corresponding to 10 musculoskeletal models were implemented into a typical inverse dynamics problem, including inverse kinematics, inverse dynamics, static optimization and joint reaction analysis algorithms solved using the OpenSim software to calculate joint angles, joint moments, muscle forces and activations, joint reaction forces during 5 walking trials. The predicted muscle activations were qualitatively compared to experimental EMG, to evaluate the accuracy of model predictions. Planar joint at the knee, universal joint at the ankle and spherical joints at the knee and at the ankle produced appreciable variations in model predictions during gait trials. The planar knee joint model reduced the discrepancy between the predicted activation of the Rectus Femoris and the EMG (with respect to the baseline model), and the reduced peak knee reaction force was considered more accurate. The use of the universal joint, with the introduction of the subtalar joint, worsened the muscle activation agreement with the EMG, and increased ankle and knee reaction forces were predicted. The spherical joints, in particular at the knee, worsened the muscle activation agreement with the EMG. A substantial increase of joint reaction forces at all joints was predicted despite of the good agreement in joint kinematics with those of the baseline model. The introduction of the universal joint had a negative effect on the model predictions. The cause of this discrepancy is likely to be found in the definition of the subtalar joint and thus, in the particular subject’s anthropometry, used to create the model and define the joint pose. We concluded that the implementation of complex joint models do not have marked effects on the joint reaction forces during gait. Computed results were similar in magnitude and in pattern to those reported in literature. Nonetheless, the introduction of planar joint model at the knee had positive effect upon the predictions, while the use of spherical joint at the knee and/or at the ankle is absolutely unadvisable, because it predicted unrealistic joint reaction forces.

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We have extended the Boltzmann code CLASS and studied a specific scalar tensor dark energy model: Induced Gravity

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Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

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We present a geospatial model to predict the radiofrequency electromagnetic field from fixed site transmitters for use in epidemiological exposure assessment. The proposed model extends an existing model toward the prediction of indoor exposure, that is, at the homes of potential study participants. The model is based on accurate operation parameters of all stationary transmitters of mobile communication base stations, and radio broadcast and television transmitters for an extended urban and suburban region in the Basel area (Switzerland). The model was evaluated by calculating Spearman rank correlations and weighted Cohen's kappa (kappa) statistics between the model predictions and measurements obtained at street level, in the homes of volunteers, and in front of the windows of these homes. The correlation coefficients of the numerical predictions with street level measurements were 0.64, with indoor measurements 0.66, and with window measurements 0.67. The kappa coefficients were 0.48 (95%-confidence interval: 0.35-0.61) for street level measurements, 0.44 (95%-CI: 0.32-0.57) for indoor measurements, and 0.53 (95%-CI: 0.42-0.65) for window measurements. Although the modeling of shielding effects by walls and roofs requires considerable simplifications of a complex environment, we found a comparable accuracy of the model for indoor and outdoor points.

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An efficient mixed molecular dynamics/quantum mechanics model has been applied to the water cluster system. The use of the MP2 method and correlation consistent basis sets, with appropriate correction for BSSE, allows for the accurate calculation of electronic and free energies for the formation of clusters of 2−10 water molecules. This approach reveals new low energy conformers for (H2O)n=7,9,10. The water heptamer conformers comprise five different structural motifs ranging from a three-dimensional prism to a quasi-planar book structure. A prism-like structure is favored energetically at low temperatures, but a chair-like structure is the global Gibbs free energy minimum past 200 K. The water nonamers exhibit less complexity with all the low energy structures shaped like a prism. The decamer has 30 conformers that are within 2 kcal/mol of the Gibbs free energy minimum structure at 298 K. These structures are categorized into four conformer classes, and a pentagonal prism is the most stable structure from 0 to 320 K. Results can be used as benchmark values for empirical water models and density functionals, and the method can be applied to larger water clusters.

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The G3, CBS-QB3, and CBS-APNO methods have been used to calculate ΔH and ΔG values for deprotonation of seventeen gas-phase reactions where the experimental values are reported to be accurate within one kcal/mol. For these reactions, the mean absolute deviation of these three methods from experiment is 0.84 to 1.26 kcal/mol, and the root-mean-square deviation for ΔG and ΔH is 1.43 and 1.49 kcal/mol for the CBS-QB3 method, 1.06 and 1.14 kcal/mol for the CBS-APNO method, and 1.16 and 1.28 for the G3 method. The high accuracy of these methods makes them reliable for calculating gas-phase deprotonation reactions, and allows them to serve as a valuable check on the accuracy of experimental data reported in the National Institutes of Standards and Technology database.

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The SVWN, BVWN, BP86, BLYP, BPW91, B3P86, B3LYP, B3PW91, B1LYP, mPW1PW, and PBE1PBE density functionals, as implemented in Gaussian 98 and Gaussian 03, were used to calculate ΔG0 and ΔH0 values for 17 deprotonation reactions where the experimental values are accurately known. The PBE1PBE and B3P86 functionals are shown to compute results with accuracy comparable to more computationally intensive compound model chemistries. A rationale for the relative performance of various functionals is explored.

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A series of CCSD(T) single-point calculations on MP4(SDQ) geometries and the W1 model chemistry method have been used to calculate ΔH° and ΔG° values for the deprotonation of 17 gas-phase reactions where the experimental values have reported accuracies within 1 kcal/mol. These values have been compared with previous calculations using the G3 and CBS model chemistries and two DFT methods. The most accurate CCSD(T) method uses the aug-cc-pVQZ basis set. Extrapolation of the aug-cc-pVTZ and aug-cc-pVQZ results yields the most accurate agreement with experiment, with a standard deviation of 0.58 kcal/mol for ΔG° and 0.70 kcal/mol for ΔH°. Standard deviations from experiment for ΔG° and ΔH° for the W1 method are 0.95 and 0.83 kcal/mol, respectively. The G3 and CBS-APNO results are competitive with W1 and are much less expensive. Any of the model chemistry methods or the CCSD(T)/aug-cc-pVQZ method can serve as a valuable check on the accuracy of experimental data reported in the National Institutes of Standards and Technology (NIST) database.