950 resultados para root-mean-square roughness
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Purpose: The aim of this study was to evaluate the surface roughness of four packable composite resins, SureFil™ (Dentsply, Petrópolis, Rio de Janeiro, Brazil), Prodigy Condensable™ (Kerr Co., Orange, CA, USA), Filtek P60™ (3M do Brasil, São Paulo, Brazil), and ALERT® (Jeneric/Pentron, Inc., Wallingford, CT, USA) and one microhybrid composite resin (Filtek Z250™, 3M do Brasil) after polishing with four finishing systems. Materials and Methods: Twenty specimens were made of each material (5 mm in diameter and 4 mm high) and were analyzed with a profilometer (Perthometer® S8P, Perthen, Mahr, Germany) to measure the mean surface roughness (Ra). The specimens were then divided into four groups according to the polishing system: group 1 - Sof-Lex™ (3M do Brasil), group 2 - Enhance™ (Dentsply), group 3 - Composite Finishing Kit (KG Sorensen, Barueri, São Paulo, Brazil), and group 4 - Jiffy Polisher Cups® (Ultradent Products, Inc., South Jordan, UT, USA). The specimens were polished and then evaluated for Ra, and the data were subjected to analysis of variance, analysis of covariance, and Tukey's test (p = .05). Results: The mean Ra of SureFil polished with Sof-Lex was significantly lower than that of KG points. Prodigy Condensable polished with Enhance showed a significantly less rough surface than when polished with Sof-Lex. Filtek P60 did not exhibit a significant difference with the various polishing systems. For ALERT the lowest mean Ra was obtained with Sof-Lex and the highest mean Ra with KG points. Regarding Filtek Z250, polishing with KG and Jiffy points resulted in a significantly lower mean Ra than when polished with Enhance. Conclusions: Packable composite resins display variable roughness depending on the polishing system used; the Sof-Lex disks and Jiffy points resulted in the best Ra values for the majority of the materials tested.
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The aim of this study was to evaluate the influence of 2 different surface polishing procedures - glazing (GZ) and manual polishing (MP) - on the roughness of ceramics processed by computer-aided design/computer-aided manufacturing (CAD/CAM) and conventional systems (stratification technique). Eighty ceramic discs (diameter: 8 mm, thickness: 1 mm) were prepared and divided among 8 groups (n = 10) according to the type of ceramic disc and polishing method: 4 GZ and 4 MP. Specimens were glazed according to each manufacturer's recommendations. Two silicone polishing points were used on the ceramic surface for manual polishing. Roughness was measured using a surface roughness tester. The roughness measurements were made along a distance of 2 mm on the sample surface and the speed of reading was 0.1 mm/s. Three measurements were taken for each sample. The data (μm) were statistically analyzed using analysis of variance (ANOVA) and Tukey's test (α = 0.05). Qualitative analysis was performed using scanning electron microscopy (SEM). The mean (± SD) roughness values obtained for GZ were: 1.1 ± 0.40 μm; 1.0 ± 0.31 μm; 1.6 ± 0.31 μm; and 2.2 ± 0.73 μm. For MP, the mean values were: 0.66 ± 0.13 μm; 0.43 ± 0.14 μm; 1.6 ± 0.55 μm; and 2.0 ± 0.63 μm. The mean roughness values were significantly affected by the ceramic type (P = 0.0001) and polishing technique (P = 0.0047). The SEM images confirmed the roughness data. The manually polished glass CAD/CAM ceramics promoted lower surface roughness than did the glazed feldspathic dental ceramics.
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Estimating equations of global radiation based on the sunshine duration were proposed for horizontal surface and with inclination of 12.85, 22.85 and 32.85° facing the North in Botucatu, SP, Brazil, in monthly, seasonal and annual groupings of data. Simple linear correlations were applied (for definition of the linear and angular coefficients of Angstrom-Prescott model), in a database measured in all three inclinations in different periods (22.85°: 04/1998 to 07/2001; 12.85°: 08/2011 to 02/2003; and 32.85°: 03/2003 to 12/2007) concomitant with horizontal measures and sunshine duration. The statistical performance of the model was analysed by the means absolute error (MBE), the square root of the mean square error (RMSE) and the index adjustment (d). The minimum global radiation transmissivity varied from 14.35% in August (12.85°) to 27.86% in December (32.85°) and the maximum transmissivity ranged between 62.10% and 78.90%, for June (32.85°) and December (12.85°). Increasing the angle of inclination surface increased the scattering and decreased the index of adjustment and performance. The worst results were found for application of the seasonal and annual models in the months of autumn and winter for 32.85° (RMSE below 42.93% and adjustment superior to 0.4693).
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Pós-graduação em Engenharia Mecânica - FEIS
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Pós-graduação em Zootecnia - FCAV
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Engenharia Mecânica - FEB
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Fine roots are the most dynamic portion of a plant's root system and a major source of soil organic matter. By altering plant species diversity and composition, soil conditions and nutrient availability, and consequently belowground allocation and dynamics of root carbon (C) inputs, land-use and management changes may influence organic C storage in terrestrial ecosystems. In three German regions, we measured fine root radiocarbon (14C) content to estimate the mean time since C in root tissues was fixed from the atmosphere in 54 grassland and forest plots with different management and soil conditions. Although root biomass was on average greater in grasslands 5.1 ± 0.8 g (mean ± SE, n = 27) than in forests 3.1 ± 0.5 g (n = 27) (p < 0.05), the mean age of C in fine roots in forests averaged 11.3 ± 1.8 yr and was older and more variable compared to grasslands 1.7 ± 0.4 yr (p < 0.001). We further found that management affects the mean age of fine root C in temperate grasslands mediated by changes in plant species diversity and composition. Fine root mean C age is positively correlated with plant diversity (r = 0.65) and with the number of perennial species (r = 0.77). Fine root mean C age in grasslands was also affected by study region with averages of 0.7 ± 0.1 yr (n = 9) on mostly organic soils in northern Germany and of 1.8 ± 0.3 yr (n = 9) and 2.6 ± 0.3 (n = 9) in central and southern Germany (p < 0.05). This was probably due to differences in soil nutrient contents and soil moisture conditions between study regions, which affected plant species diversity and the presence of perennial species. Our results indicate more long-lived roots or internal redistribution of C in perennial species and suggest linkages between fine root C age and management in grasslands. These findings improve our ability to predict and model belowground C fluxes across broader spatial scales.
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Chrysophyte cysts are recognized as powerful proxies of cold-season temperatures. In this paper we use the relationship between chrysophyte assemblages and the number of days below 4 °C (DB4 °C) in the epilimnion of a lake in northern Poland to develop a transfer function and to reconstruct winter severity in Poland for the last millennium. DB4 °C is a climate variable related to the length of the winter. Multivariate ordination techniques were used to study the distribution of chrysophytes from sediment traps of 37 low-land lakes distributed along a variety of environmental and climatic gradients in northern Poland. Of all the environmental variables measured, stepwise variable selection and individual Redundancy analyses (RDA) identified DB4 °C as the most important variable for chrysophytes, explaining a portion of variance independent of variables related to water chemistry (conductivity, chlorides, K, sulfates), which were also important. A quantitative transfer function was created to estimate DB4 °C from sedimentary assemblages using partial least square regression (PLS). The two-component model (PLS-2) had a coefficient of determination of View the MathML sourceRcross2 = 0.58, with root mean squared error of prediction (RMSEP, based on leave-one-out) of 3.41 days. The resulting transfer function was applied to an annually-varved sediment core from Lake Żabińskie, providing a new sub-decadal quantitative reconstruction of DB4 °C with high chronological accuracy for the period AD 1000–2010. During Medieval Times (AD 1180–1440) winters were generally shorter (warmer) except for a decade with very long and severe winters around AD 1260–1270 (following the AD 1258 volcanic eruption). The 16th and 17th centuries and the beginning of the 19th century experienced very long severe winters. Comparison with other European cold-season reconstructions and atmospheric indices for this region indicates that large parts of the winter variability (reconstructed DB4 °C) is due to the interplay between the oscillations of the zonal flow controlled by the North Atlantic Oscillation (NAO) and the influence of continental anticyclonic systems (Siberian High, East Atlantic/Western Russia pattern). Differences with other European records are attributed to geographic climatological differences between Poland and Western Europe (Low Countries, Alps). Striking correspondence between the combined volcanic and solar forcing and the DB4 °C reconstruction prior to the 20th century suggests that winter climate in Poland responds mostly to natural forced variability (volcanic and solar) and the influence of unforced variability is low.
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Doutoramento em Economia
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This study aimed to describe and compare the ventilation behavior during an incremental test utilizing three mathematical models and to compare the feature of ventilation curve fitted by the best mathematical model between aerobically trained (TR) and untrained ( UT) men. Thirty five subjects underwent a treadmill test with 1 km.h(-1) increases every minute until exhaustion. Ventilation averages of 20 seconds were plotted against time and fitted by: bi-segmental regression model (2SRM); three-segmental regression model (3SRM); and growth exponential model (GEM). Residual sum of squares (RSS) and mean square error (MSE) were calculated for each model. The correlations between peak VO2 (VO2PEAK), peak speed (Speed(PEAK)), ventilatory threshold identified by the best model (VT2SRM) and the first derivative calculated for workloads below (moderate intensity) and above (heavy intensity) VT2SRM were calculated. The RSS and MSE for GEM were significantly higher (p < 0.01) than for 2SRM and 3SRM in pooled data and in UT, but no significant difference was observed among the mathematical models in TR. In the pooled data, the first derivative of moderate intensities showed significant negative correlations with VT2SRM (r = -0.58; p < 0.01) and Speed(PEAK) (r = -0.46; p < 0.05) while the first derivative of heavy intensities showed significant negative correlation with VT2SRM (r = -0.43; p < 0.05). In UT group the first derivative of moderate intensities showed significant negative correlations with VT2SRM (r = -0.65; p < 0.05) and Speed(PEAK) (r = -0.61; p < 0.05), while the first derivative of heavy intensities showed significant negative correlation with VT2SRM (r= -0.73; p < 0.01), Speed(PEAK) (r = -0.73; p < 0.01) and VO2PEAK (r = -0.61; p < 0.05) in TR group. The ventilation behavior during incremental treadmill test tends to show only one threshold. UT subjects showed a slower ventilation increase during moderate intensities while TR subjects showed a slower ventilation increase during heavy intensities.
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Inductively coupled plasma optical emission spectrometers (ICP DES) allow fast simultaneous measurements of several spectral lines for multiple elements. The combination of signal intensities of two or more emission lines for each element may bring such advantages as improvement of the precision, the minimization of systematic errors caused by spectral interferences and matrix effects. In this work, signal intensities for several spectral lines were combined for the determination of Al, Cd, Co, Cr, Mn, Pb, and Zn in water. Afterwards, parameters for evaluation of the calibration model were calculated to select the combination of emission lines leading to the best accuracy (lowest values of PRESS-Predicted error sum of squares and RMSEP-Root means square error of prediction). Limits of detection (LOD) obtained using multiple lines were 7.1, 0.5, 4.4, 0.042, 3.3, 28 and 6.7 mu g L(-1) (n = 10) for Al, Cd. Co, Cr, Mn, Pb and Zn, respectively, in the presence of concomitants. On the other hand, the LOD established for the most intense emission line were 16. 0.7, 8.4, 0.074. 23, 26 and 9.6 mu g L(-1) (n = 10) for these same elements in the presence of concomitants. The accuracy of the developed procedure was demonstrated using water certified reference material. The use of multiple lines improved the sensitivity making feasible the determination of these analytes according to the target values required for the current environmental legislation for water samples and it was also demonstrated that measurements in multiple lines can also be employed as a tool to verify the accuracy of an analytical procedure in ICP DES. (C) 2009 Elsevier B.V. All rights reserved.
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Pires, FO, Hammond, J, Lima-Silva, AE, Bertuzzi, RCM, and Kiss, MAPDM. Ventilation behavior during upper-body incremental exercise. J Strength Cond Res 25(1): 225-230, 2011-This study tested the ventilation (V(E)) behavior during upper-body incremental exercise by mathematical models that calculate 1 or 2 thresholds and compared the thresholds identified by mathematical models with V-slope, ventilatory equivalent for oxygen uptake (V(E)/(V) over dotO(2)), and ventilatory equivalent for carbon dioxide uptake (V(E)/(V) over dotCO(2)). Fourteen rock climbers underwent an upper-body incremental test on a cycle ergometer with increases of approximately 20 W.min(-1) until exhaustion at a cranking frequency of approximately 90 rpm. The V(E) data were smoothed to 10-second averages for V(E) time plotting. The bisegmental and the 3-segmental linear regression models were calculated from 1 or 2 intercepts that best shared the V(E) curve in 2 or 3 linear segments. The ventilatory threshold(s) was determined mathematically by the intercept(s) obtained by bisegmental and 3-segmental models, by V-slope model, or visually by V(E)/(V) over dotO(2) and V(E)/(V) over dotCO(2). There was no difference between bisegmental (mean square error [MSE] = 35.3 +/- 32.7 l.min(-1)) and 3-segmental (MSE = 44.9 +/- 47.8 l.min(-1)) models in fitted data. There was no difference between ventilatory threshold identified by the bisegmental (28.2 +/- 6.8 ml.kg(-1).min(-1)) and second ventilatory threshold identified by the 3-segmental (30.0 +/- 5.1 ml.kg(-1).min(-1)), V(E)/(V) over dotO(2) (28.8 +/- 5.5 ml.kg(-1).min(-1)), or V-slope (28.5 +/- 5.6 ml.kg(-1).min(-1)). However, the first ventilatory threshold identified by 3-segmental (23.1 +/- 4.9 ml.kg(-1).min(-1)) or by VE/(V) over dotO(2) (24.9 +/- 4.4 ml.kg(-1).min(-1)) was different from these 4. The V(E) behavior during upper-body exercise tends to show only 1 ventilatory threshold. These findings have practical implications because this point is frequently used for aerobic training prescription in healthy subjects, athletes, and in elderly or diseased populations. The ventilatory threshold identified by V(E) curve should be used for aerobic training prescription in healthy subjects and athletes.
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This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.
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In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.