970 resultados para Covariance estimate
Resumo:
The application of airborne laser scanning (ALS) technologies in forest inventories has shown great potential to improve the efficiency of forest planning activities. Precise estimates, fast assessment and relatively low complexity can explain the good results in terms of efficiency. The evolution of GPS and inertial measurement technologies, as well as the observed lower assessment costs when these technologies are applied to large scale studies, can explain the increasing dissemination of ALS technologies. The observed good quality of results can be expressed by estimates of volumes and basal area with estimated error below the level of 8.4%, depending on the size of sampled area, the quantity of laser pulses per square meter and the number of control plots. This paper analyzes the potential of an ALS assessment to produce certain forest inventory statistics in plantations of cloned Eucalyptus spp with precision equal of superior to conventional methods. The statistics of interest in this case were: volume, basal area, mean height and dominant trees mean height. The ALS flight for data assessment covered two strips of approximately 2 by 20 Km, in which clouds of points were sampled in circular plots with a radius of 13 m. Plots were sampled in different parts of the strips to cover different stand ages. The clouds of points generated by the ALS assessment: overall height mean, standard error, five percentiles (height under which we can find 10%, 30%, 50%,70% and 90% of the ALS points above ground level in the cloud), and density of points above ground level in each percentile were calculated. The ALS statistics were used in regression models to estimate mean diameter, mean height, mean height of dominant trees, basal area and volume. Conventional forest inventory sample plots provided real data. For volume, an exploratory assessment involving different combinations of ALS statistics allowed for the definition of the most promising relationships and fitting tests based on well known forest biometric models. The models based on ALS statistics that produced the best results involved: the 30% percentile to estimate mean diameter (R(2)=0,88 and MQE%=0,0004); the 10% and 90% percentiles to estimate mean height (R(2)=0,94 and MQE%=0,0003); the 90% percentile to estimate dominant height (R(2)=0,96 and MQE%=0,0003); the 10% percentile and mean height of ALS points to estimate basal area (R(2)=0,92 and MQE%=0,0016); and, to estimate volume, age and the 30% and 90% percentiles (R(2)=0,95 MQE%=0,002). Among the tested forest biometric models, the best fits were provided by the modified Schumacher using age and the 90% percentile, modified Clutter using age, mean height of ALS points and the 70% percentile, and modified Buckman using age, mean height of ALS points and the 10% percentile.
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Experimental results obtained from a greenhouse trial with common bean (Phaseolus vulgaris L) plants performed to test model hypotheses regarding the onset of limiting hydraulic conditions and the shape of the transpiration reduction curve in the falling rate phase are presented. According to these hypotheses based on simulations with an upscaled single-root model, the matric flux potential at the onset of limiting hydraulic conditions is as a function of root length density and potential transpiration rate, while the relative transpiration in the falling rate phase equals the relative matric flux potential. Transpiration of bean plants in water stressed pots with four different soils was determined daily by weighing and compared to values obtained from non-stressed pots. This procedure allowed determining the onset of the falling rate phase and corresponding soil hydraulic conditions. At the onset of the falling rate phase, the value of matric flux potential M(I) showed to differ in order of magnitude from the model predicted value for three out of four soils. This difference between model and experiment can be explained by the heterogeneity of the root distribution which is not considered by the model. An empirical factor to deal with this heterogeneity should be included in the model to improve predictions. Comparing the predictions of relative transpiration in the falling rate phase using a linear shape with water content, pressure head or matric flux potential, the matric flux potential based reduction function, in agreement with the hypothesis, showed the best performance, while the pressure head based equation resulted in the highest deviations between observed and predicted values of relative transpiration rates. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.
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The objective of this study was to compare the results of an on-farm test, named Somaticell, with results of electronic cell counting and for milk somatic cell count (SCC) among readers. The Somaticell test correctly determined the SCC in fresh quarter milk samples. Correlation between Somaticell and electronic enumeration of somatic cells was 0.92 and. coefficient 0.82. Using a threshold of 205,000 cells/mL, the sensitivity and specificity for determination of intramammary infections were 91.3 and 96.0%, respectively. The SCC was greater for milk samples from which major mastitis pathogens were recovered. Minor variation among readers was observed and most likely associated with the mixing procedure. However, the final analysis indicated that this variation was not significant and did not affect the amount of samples classified as having subclinical mastitis. The on-farm test evaluated in this study showed adequate capacity of determining SCC on quarter milk samples and may be considered as an alternative for on-farm detection of subclinical mastitis.
Resumo:
Application of the thermal sum concept was developed to determine the optimal harvesting stage of new banana hybrids to be grown for export. It was tested on two triploid hybrid bananas, FlhorBan 916 (F916) and FlhorBan 918 (F918), created by CIRAD`s banana breeding programme, using two different approaches. The first approach was used with F916 and involved calculating the base temperature of bunches sampled at two sites at the ripening stage, and then determining the thermal sum at which the stage of maturity would be identical to that of the control Cavendish export banana. The second approach was used to assess the harvest stage of F918 and involved calculating the two thermal parameters directly, but using more plants and a longer period. Using the linear regression model, the estimated thermal parameters were a thermal sum of 680 degree-days (dd) at a base temperature of 17.0 degrees C for cv. F916, and 970 dd at 13.9 degrees C for cv. F918. This easy-to-use method provides quick and reliable calculations of the two thermal parameters required at a specific harvesting stage for a given banana variety in tropical climate conditions. Determining these two values is an essential step for gaining insight into the agronomic features of a new variety and its potential for export. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
The evolution of a positive genetic correlation between male and female components of mate recognition systems will result as a consequence of assortative mating and, in particular, is central to a number of theories of sexual selection. Although the existence of such genetic correlations has been investigated in a number of taxa, it has yet to be shown that such correlations evolve and whether they may evolve as rapidly as suggested by sexual selection models. In this study, I used a hybridization experiment to disrupt natural mate recognition systems and then observed the subsequent evolutionary dynamics of the genetic correlation between male and female components for 56 generations in hybrids between Drosophila serrata and Drosophila birchii. The genetic correlation between male and female components evolved from 0.388 at generation 5 to 1.017 at generation 37 and then declined to -0.040 after a further 19 generations. These results indicated that the genetic basis of the mate recognition system in the hybrid populations evolved rapidly. The initial rapid increase in the genetic correlation was consistent with the classic assumption that male and female components will coevolve under sexual selection. The subsequent decline in genetic correlation may be attributable to the fixation of major genes or, alternatively, may be a result of a cyclic evolutionary change in mate recognition.
Resumo:
Aims: To estimate dementia prevalence and describe the etiology of dementia in a community sample from the city of Sao Paulo, Brazil. Methods: A sample of subjects older than 60 years was screened for dementia in the first phase. During the second phase, the diagnostic workup included a structured interview, physical and neurological examination, laboratory exams, a brain scan, and DSM-IV criteria diagnosis. Results: Mean age was 71.5 years (n = 1,563) and 58.3% had up to 4 years of schooling (68.7% female). Dementia was diagnosed in 107 subjects with an observed prevalence of 6.8%. The estimate of dementia prevalence was 12.9%, considering design effect, nonresponse during the community phase, and positive and negative predictive values. Alzheimer`s disease was the most frequent cause of dementia (59.8%), followed by vascular dementia (15.9%). Older age and illiteracy were significantly associated with dementia. Conclusions: The estimate of dementia prevalence was higher than previously reported in Brazil, with Alzheimer`s disease and vascular dementia being the most frequent causes of dementia. Dementia prevalence in Brazil and in other Latin American countries should be addressed by additional studies to confirm these higher dementia rates which might have a sizable impact on countries` health services. Copyright (C) 2008 S. Karger AG, Basel
Resumo:
The risk of breast cancer arises from a combination of genetic susceptibility and environmental factors. Recent studies show that type and duration of use of hormone replacement therapy affect a women's risk of developing breast cancer.1-7 The women's health initiative trial was stopped early because of excess adverse cardiovascular events and invasive breast cancer with oestrogen and progestogen.6 The publicity increased public awareness of the risks of hormone replacement therapy, and this was heightened by the publication of the million women study.2 However, the recently published oestrogen only arm of the women's health initiative trial suggests that this formulation may reduce the risk of breast cancer.8 To help make sense of the often confusing information,9 women and clinicians need individual rather than population risk data. We have produced estimates that can be used to calculate individual risk for women living up to the age of 79 and suggest the risk
Resumo:
Background: Condition-dependence is a ubiquitous feature of animal life histories and has important implications for both natural and sexual selection. Mate choice, for instance, is typically based on condition-dependent signals. Theory predicts that one reason why condition-dependent signals may be special is that they allow females to scan for genes that confer high parasite resistance. Such explanations require a genetic link between immunocompetence and body condition, but existing evidence is limited to phenotypic associations. It remains unknown, therefore, whether females selecting males with good body condition simply obtain a healthy mate, or if they acquire genes for their offspring that confer high immunocompetence. Results: Here we use a cross-foster experimental design to partition the phenotypic covariance in indices of body condition and immunocompetence into genetic, maternal and environmental effects in a passerine bird, the zebra finch Taeniopygia guttata. We show that there is significant positive additive genetic covariance between an index of body condition and an index of cell-mediated immune response. In this case, genetic variance in the index of immune response explained 56% of the additive genetic variance in the index of body condition. Conclusion: Our results suggest that, in the context of sexual selection, females that assess males on the basis of condition-dependent signals may gain genes that confer high immunocompetence for their offspring. More generally, a genetic correlation between indices of body condition and imuunocompetence supports the hypothesis that parasite resistance may be an important target of natural selection. Additional work is now required to test whether genetic covariance exists among other aspects of both condition and immunocompetence.
Resumo:
The incidence of 21-hydroxylase deficiency (CYP21 D) congenital adrenal hyperplasia (CAH) in Brazil is purportedly one of the highest in the world (1:7,533). However, this information is not based on official data. The aim of this study was to determine the incidence of CYP21 D CAH in the state of Goias, Brazil, based on the 2005 results of government-funded mandatory screening. Of the live births during this period, 92.95% were screened by heel-prick capillary 17 alpha-hydroxyprogesterone (17-OHP). Of these, 82,343 were normal, 28 were at high risk for CAH and 232 at low risk for CAH. Eight cases, all from the high risk group, were confirmed. Eight asymptomatic children at 6-18 months of age still have high 17-OHP levels and await diagnostic definition. Based on the number of confirmed CYP21 D CAH cases among the 82,603 screened, the estimated annual incidence of the disease was 1:10,325, lower than the previously reported rate in Brazil.
Resumo:
Calculating the estimated resting energy expenditure (REE) in severely obese patients is useful, but there is controversy concerning the effectiveness of available prediction equations (PE) using body weight (BW). We evaluated the efficacy of REE equations against indirect calorimetry (IC) in severely obese subjects and aimed to develop a new equation based on body composition compartments. One hundred and twenty severely obese patients had their REE measured (MREE) by IC and compared to the most commonly used PE (Harris-Benedict (HB), Ireton-Jones, Owen, and Mifflin St. Jeor). In a random sample (n = 60), a new REE equation based on fat-free mass (FFM) was developed and validated. All PE studied failed to estimate REE in severe obesity (low concordance correlation coefficient (CCC) and limits of agreement of nearly 50% of the sample +/- 10% of MREE). The HB equation using actual BW exhibited good results for all samples when compared to IC (2,117 +/- 518 kcal/day by HB vs. 2,139 +/- 423 kcal/day by MREE, P > 0.01); these results were blunted when patients were separated by gender (2,771 vs. 2,586 kcal/day, P < 0.001 in males and 1,825 vs. 1,939 kcal/day, P < 0.001 in females). A new resting energy expenditure equation prediction was developed using FFM, Horie-Waitzberg, & Gonzalez, expressed as 560.43 + (5.39 x BW) + (14.14 x FFM). The new resting energy expenditure equation prediction, which uses FFM and BW, demonstrates higher accuracy, precision, CCC, and limits of agreement than the standard PE in patients when compared to MREE (2,129 +/- 45 kcal/day vs. 2,139 +/- 423 kcal/day, respectively, P = 0.1). The new equation developed to estimate REE, which takes into account both FFM and BW, provides better results than currently available equations.
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Axial vertebral rotation, an important parameter in the assessment of scoliosis may be identified on X-ray images. In line with the advances in the field of digital radiography, hospitals have been increasingly using this technique. The objective of the present study was to evaluate the reliability of computer-processed rotation measurements obtained from digital radiographs. A software program was therefore developed, which is able to digitally reproduce the methods of Perdriolle and Raimondi and to calculate semi-automatically the rotation degree of vertebra on digital radiographs. Three independent observers estimated vertebral rotation employing both the digital and the traditional manual methods. Compared to the traditional method, the digital assessment showed a 43% smaller error and a stronger correlation. In conclusion, the digital method seems to be reliable and enhance the accuracy and precision of vertebral rotation measurements.