Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

Relating MODIS vegetation index time-series with structure, light absorption and stem production of fast-growing Eucalyptus plantations

By allowing the estimation of forest structural and biophysical characteristics at different temporal and spatial scales, remote sensing may contribute to our understanding and monitoring of planted forests. Here, we studied 9-year time-series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on a network of 16 stands in fast-growing Eucalyptus plantations in Sao Paulo State, Brazil. We aimed to examine the relationships between NDVI time-series spanning entire rotations and stand structural characteristics (volume, dominant height, mean annual increment) in these simple forest ecosystems. Our second objective was to examine spatial and temporal variations of light use efficiency for wood production, by comparing time-series of Absorbed Photosynthetically Active Radiation (APAR) with inventory data. Relationships were calibrated between the NDVI and the fractions of intercepted diffuse and direct radiation, using hemispherical photographs taken on the studied stands at two seasons. APAR was calculated from the NDVI time-series using these relationships. Stem volume and dominant height were strongly correlated with summed NDVI values between planting date and inventory date. Stand productivity was correlated with mean NDVI values. APAR during the first 2 years of growth was variable between stands and was well correlated with stem wood production (r(2) = 0.78). In contrast, APAR during the following years was less variable and not significantly correlated with stem biomass increments. Production of wood per unit of absorbed light varied with stand age and with site index. In our study, a better site index was accompanied both by increased APAR during the first 2 years of growth and by higher light use efficiency for stem wood production during the whole rotation. Implications for simple process-based modelling are discussed. (C) 2009 Elsevier B.V. All rights reserved.

TIME COURSE OF SKELETAL MUSCLE LOSS AND OXIDATIVE STRESS IN RATS WITH WALKER 256 SOLID TUMOR

Reactive oxygen species oxidize proteins and modulate the proteasomal system in muscle-wasting cancer cachexia. On day 5 (D5), day 10 (D10), and day 14 (D14) after tumor implantation, skeletal muscle was evaluated. Carbonylated proteins and thiobarbituric acid reactive substances were measured. Chemiluminescence was employed for lipid hydroperoxide estimation. Glutathione, superoxide dismutase, and total radical antioxidant capacity were evaluated. The proteasomal system was assessed by mRNA atrogin-1 expression. Increased muscle wasting, lipid hydroperoxide, and superoxide dismutase, and decreased glutathione levels and total radical antioxidant capacity, were found on D5 in accordance with increased mRNA atrogin-1 expression. All parameters were significantly modified in animals treated with alpha-tocopherol. The elevation in aldehylde levels and carbonylated proteins observed on D10 were reversed by cc-tocopherol treatment. Oxidative stress may trigger signal transduction of the proteasomal system and cause protein oxidation. These pathways may be associated with the mechanism of muscle wasting that occurs in cancer cachexia. Muscle Nerve 42: 950-958, 2010

Extended time weather forecasts contributes to agricultural productivity estimates

Weather conditions in critical periods of the vegetative crop development influence crop productivity, thus being a basic parameter for crop forecast. Reliable extended period weather forecasts may contribute to improve the estimation of agricultural productivity. The production of soybean plays an important role in the Brazilian economy, because this country is ranked among the largest producers of soybeans in the world. This culture can be significantly affected by water conditions, depending on the intensity of water deficit. This work explores the role of extended period weather forecasts for estimating soybean productivity in the southern part of Brazil, Passo Fundo, and Londrina (State of Rio Grande do Sul and Parana, respectively) in the 2005/2006 harvest. The goal was to investigate the possible contribution of precipitation forecasts as a substitute for the use of climatological data on crop forecasts. The results suggest that the use of meteorological forecasts generate more reliable productivity estimates during the growth period than those generated only through climatological information.

Measuring time series predictability using support vector regression

Most studies involving statistical time series analysis rely on assumptions of linearity, which by its simplicity facilitates parameter interpretation and estimation. However, the linearity assumption may be too restrictive for many practical applications. The implementation of nonlinear models in time series analysis involves the estimation of a large set of parameters, frequently leading to overfitting problems. In this article, a predictability coefficient is estimated using a combination of nonlinear autoregressive models and the use of support vector regression in this model is explored. We illustrate the usefulness and interpretability of results by using electroencephalographic records of an epileptic patient.

A semi-Markov multistate model for estimation of the mean quality-adjusted survival for non-progressive processes

We discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models. We generalize an earlier work, considering the sojourn times in health states are not identically distributed, for a given vector of covariates. Approaches based on semiparametric and parametric (exponential and Weibull distributions) methodologies are considered. A simulation study is conducted to evaluate the performance of the proposed estimator and the jackknife resampling method is used to estimate the variance of such estimator. An application to a real data set is also included.

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator. (C) 2007 Elsevier B.V. All rights reserved.

Effect of cement type and water storage time on the push-out bond strength of a glass fiber post

This study investigated the effects of the cement type and the water storage time on the push-out bond strength of a glass fiber post. Glass fiber posts (Fibrekor, Jeneric Pentron) were luted to post spaces using a self-cured resin cement (C&B Cement [CB]), a glass ionomer cement (Ketac Cem [KC]) or a resin-modified glass ionomer cement (GC FujiCEM [FC]) according to the manufacturers’ instructions. For each luting agent, the specimens were exposed to one of the following water storage times (n=5): 1 day (T1), 7 days (T7), 90 days (T90) and 180 days (T180). Push-out tests were performed after the storage times. Control specimens were not exposed to water storage, but subjected to the push-out test 10 min after post cementation. Data (in MPa) were analyzed by Kruskal-Wallis and Dunn`s test (α=0.05). Cement type and water storage time had a significant effect (p<0.05) on the push-out bond strength. CB showed significantly higher values of retention (p<0.05) than KC and FC, irrespective of the water storage time. Water storage increased significantly the push-out bond strength in T7 and T90, regardless of the cement type (p<0.05). The results showed that fiber posts luted to post spaces with the self-cured resin cement exhibited the best bonding performance throughout the 180-day water storage period. All cements exhibited a tendency to increase the bond strength after 7 and 90 days of water storage, decreasing thereafter.

Effects of light-curing time on the cytotoxicity of a restorative composite resin on odontoblast-like cells

This in vitro study evaluated the cytotoxicity of an experimental restorative composite resin subjected to different light-curing regimens. METHODS: Forty round-shaped specimens were prepared and randomly assigned to four experimental groups (n=10), as follows: in Group 1, no light-curing; in Groups 2, 3 and 4, the composite resin specimens were light-cured for 20, 40 or 60 s, respectively. In Group 5, filter paper discs soaked in 5 µL PBS were used as negative controls. The resin specimens and paper discs were placed in wells of 24-well plates in which the odontoblast-like cells MDPC-23 (30,000 cells/cm²) were plated and incubated in a humidified incubator with 5% CO2 and 95% air at 37ºC for 72 h. The cytotoxicity was evaluated by the cell metabolism (MTT assay) and cell morphology (SEM). The data were analyzed statistically by Kruskal-Wallis and Mann-Whitney tests (p<0.05). RESULTS: In G1, cell metabolism decreased by 86.2%, indicating a severe cytotoxicity of the non-light-cured composite resin. On the other hand, cell metabolism decreased by only 13.3% and 13.5% in G2 and G3, respectively. No cytotoxic effects were observed in G4 and G5. In G1, only a few round-shaped cells with short processes on their cytoplasmic membrane were observed. In the other experimental groups as well as in control group, a number of spindle-shaped cells with long cytoplasmic processes were found. CONCLUSION: Regardless of the photoactivation time used in the present investigation, the experimental composite resin presented mild to no toxic effects to the odontoblast-like MDPC-23 cells. However, intense cytotoxic effects occurred when no light-curing was performed.

Surface and subsurface erosion of primary enamel by acid beverages over time

This study evaluated the influence of a cola-type soft drink and a soy-based orange juice on the surface and subsurface erosion of primary enamel, as a function of the exposure time. Seventy-five primary incisors were divided for microhardness test (n=45) or scanning electron microscopy (SEM) analysis (n=30). The specimens were randomly assigned to 3 groups: 1 - artificial saliva (control); 2 - cola-type soft drink; and 3 - soy-based orange juice. Immersion cycles in the beverages were undertaken under agitation for 5 min, 3 times a day, during 60 days. Surface microhardness was measured at 7, 15, 30, 45 and 60 days. After 60 days, specimens were bisected and subsurface microhardness was measured at 30, 60, 90, 120, 150 and 200 µm from the surface exposed. Data were analyzed by ANOVA and Tukey’s test (a=0.05). Groups 2 and 3 presented similar decrease of surface microhardness. Regarding subsurface microhardness, group 2 presented the lowest values. SEM images revealed that after 60 days the surfaces clearly exhibited structural loss, unlike those immersed in artificial saliva. It may be concluded that erosion of the surfaces exposed to the cola-type soft drink was more accentuated and directly proportional to the exposure time.

Influence of surface sealant on the translucency of composite resin: effect of immersion time and immersion media

This study evaluated the effect of surface sealant on the translucency of composite resin immersed in different solutions. The study involved the following materials: Charisma, Fortify and coffee, Coca-Cola®, tea and artificial saliva as solutions. Sixty-four specimens (n = 8) were manufactured and immersed in artificial saliva at 37 ± 1 °C. Samples were immersed in the solutions for three times a day and re-immersed in artificial saliva until the translucency readings. The measurements were carried out at nine times: T1 - 24 hours after specimen preparation, T2 - 24 hours after immersion in the solutions, T3 - 48 hours and T4 to T9 - 7, 14, 21, 30, 60 and 90 days, respectively, after immersion. The translucency values were measured using a JOUAN device. The results were subjected to ANOVA and Tukey's test at 5%. The surface sealant was not able to protect the composite resin against staining, the coffee showed the strongest staining action, followed by tea and regarding immersion time, a significant alteration was noted in the translucency of composite resin after 21 days.

In vitro analysis of thermocompaction time and gutta-percha type on quality of main canal and lateral canals filling

The aim of this study was to evaluate the quality of filling in main and lateral root canals performed with the McSpadden technique, regarding the time spent on the procedure and the type of gutta-percha employed. Fifty simulated root canals, made with six lateral canals placed two apiece in the cervical, middle and apical thirds of the root, were divided into 5 groups. Group A: McSpadden technique with conventional gutta-percha, performed with sufficient time for canal filling; Group B: McSpadden technique with conventional gutta-percha, performed in twice the mean time used in Group A; Group C: McSpadden technique with TP gutta-percha, performed with sufficient time for canal filling; Group D: McSpadden technique with TP gutta-percha, performed in twice the mean time used in Group C; Group E: lateral condensation technique. Images of the filled root canals were taken using a stereomicroscope and analyzed using the Leica QWIN Pro software for filling material flow, gutta-percha filling extension and sealer flow. Data were analyzed by analysis of variance (ANOVA) and Tukey test (p < 0.05). The best values of penetration in lateral canals in the middle third occurred in the groups where TP gutta-percha was used. However, in the apical third, group B showed the best values. Although a longer time of compactor use allows greater penetration of the filling material into the lateral canals, the presence of voids resulted in bad quality radiographic images, suggesting porosity. The best quality of filling material was observed in Group A (McSpadden technique with conventional Gutta-Percha, performed with sufficient time for root canal filling).

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

The quantification of the available energy in the environment is important because it determines photosynthesis, evapotranspiration and, therefore, the final yield of crops. Instruments for measuring the energy balance are costly and indirect estimation alternatives are desirable. This study assessed the Deardorff's model performance during a cycle of a sugarcane crop in Piracicaba, State of São Paulo, Brazil, in comparison to the aerodynamic method. This mechanistic model simulates the energy fluxes (sensible, latent heat and net radiation) at three levels (atmosphere, canopy and soil) using only air temperature, relative humidity and wind speed measured at a reference level above the canopy, crop leaf area index, and some pre-calibrated parameters (canopy albedo, soil emissivity, atmospheric transmissivity and hydrological characteristics of the soil). The analysis was made for different time scales, insolation conditions and seasons (spring, summer and autumn). Analyzing all data of 15 minute intervals, the model presented good performance for net radiation simulation in different insolations and seasons. The latent heat flux in the atmosphere and the sensible heat flux in the atmosphere did not present differences in comparison to data from the aerodynamic method during the autumn. The sensible heat flux in the soil was poorly simulated by the model due to the poor performance of the soil water balance method. The Deardorff's model improved in general the flux simulations in comparison to the aerodynamic method when more insolation was available in the environment.

Time evolution of the South Atlantic Magnetic Anomaly

The South Atlantic Magnetic Anomaly (SAMA) is one of the most outstanding anomalies of the geomagnetic field. The SAMA secular variation was obtained and compared to the evolution of other anomalies using spherical harmonic field models for the 1590-2005 period. An analysis of data from four South American observatories shows how this large scale anomaly affected their measurements. Since SAMA is a low total field anomaly, the field was separated into its nondipolar, quadrupolar and octupolar parts. The time evolution of the non-dipole/total, quadrupolar/total and octupolar/total field ratios yielded increasingly high values for the South Atlantic since 1750. The SAMA evolution is compared to the evolution of other large scale surface geomagnetic features like the North and the South Pole and the Siberia High, and this comparison shows the intensity equilibrium between these anomalies in both hemispheres. The analysis of non-dipole fields in historical period suggests that SAMA is governed by (i) quadrupolar field for drift, and (ii) quadrupolar and octupolar fields for intensity and area of influence. Furthermore, our study reinforces the possibility that SAMA may be related to reverse fluxes in the outer core under the South Atlantic region.