930 resultados para kernel estimates


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Weight records of Brazilian Nelore cattle, from birth to 630 d of age, recorded every 3 mo, were analyzed using random regression models. Independent variables were Legendre polynomials of age at recording. The model of analysis included contemporary groups as fixed effects and age of dam as a linear and quadratic covariable. Mean trends were modeled through a cubic regression on orthogonal polynomials of age. Up to four sets of random regression coefficients were fitted for animals' direct and maternal, additive genetic, and permanent environmental effects. Changes in measurement error variances with age were modeled through a variance function. Orders of polynomial fit from three to six were considered, resulting in up to 77 parameters to be estimated. Models fitting random regressions modeled the pattern of variances in the data adequately, with estimates similar to those from corresponding univariate analysis. Direct heritability estimates decreased after birth and tended to be lowest at ages at which maternal effect estimates tended to be highest. Maternal heritability estimates increased after birth to a peak around 110 to 120 d of age and decreased thereafter. Additive genetic direct correlation estimates between weights at standard ages (birth, weaning, yearling, and final weight) were moderate to high and maternal genetic and environmental correlations were consistently high.

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Polymerase chain reaction techniques were developed and applied to identify DNA from .40 species of prey contained in fecal (scat) soft-part matrix collected at terrestrial sites used by Steller sea lions (Eumetopias jubatus) in British Columbia and the eastern Aleutian Islands, Alaska. Sixty percent more fish and cephalopod prey were identified by morphological analyses of hard parts compared with DNA analysis of soft parts (hard parts identified higher relative proportions of Ammodytes sp., Cottidae, and certain Gadidae). DNA identified 213 prey occurrences, of which 75 (35%) were undetected by hard parts (mainly Salmonidae, Pleuronectidae, Elasmobranchii, and Cephalopoda), and thereby increased species occurrences by 22% overall and species richness in 44% of cases (when comparing 110 scats that amplified prey DNA). Prey composition was identical within only 20% of scats. Overall, diet composition derived from both identification techniques combined did not differ significantly from hard-part identification alone, suggesting that past scat-based diet studies have not missed major dietary components. However, significant differences in relative diet contributions across scats (as identified using the two techniques separately) reflect passage rate differences between hard and soft digesta material and highlight certain hypothesized limitations in conventional morphological-based methods (e.g., differences in resistance to digestion, hard part regurgitation, partial and secondary prey consumption), as well as potential technical issues (e.g., resolution of primer efficiency and sensitivity and scat subsampling protocols). DNA analysis of salmon occurrence (from scat soft-part matrix and 238 archived salmon hard parts) provided species-level taxonomic resolution that could not be obtained by morphological identification and showed that Steller sea lions were primarily consuming pink (Oncorhynchus gorbuscha) and chum (Oncorhynchus keta) salmon. Notably, DNA from Atlantic salmon (Salmo salar) that likely originated from a distant fish farm was also detected in two scats from one site in the eastern Aleutian Islands. Overall, molecular techniques are valuable for identifying prey in the fecal remains of marine predators. Combining DNA and hard-part identification will effectively alleviate certain predicted biases and will ultimately enhance measures of diet richness, fisheries interactions (especially salmon-related ones), and the ecological role of pinnipeds and other marine predators, to the benefit of marine wildlife conservationists and fisheries managers.

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The multiple-instance learning (MIL) model has been successful in areas such as drug discovery and content-based image-retrieval. Recently, this model was generalized and a corresponding kernel was introduced to learn generalized MIL concepts with a support vector machine. While this kernel enjoyed empirical success, it has limitations in its representation. We extend this kernel by enriching its representation and empirically evaluate our new kernel on data from content-based image retrieval, biological sequence analysis, and drug discovery. We found that our new kernel generalized noticeably better than the old one in content-based image retrieval and biological sequence analysis and was slightly better or even with the old kernel in the other applications, showing that an SVM using this kernel does not overfit despite its richer representation.

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The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.

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In dealing with population estimates, we need to determine first the reason for estimating the population. If we are dealing with a local situation, are we concerned with a local estimate? If we are dealing with a regional problem, are we concerned with a regional estimate? The blackbird problem is chiefly a regional problem, but we need to look at broader horizons than just local or regional situations. Are we dealing with a national problem? Is this problem a year-round one or is it a seasonal problem? We may want to know just purely the number of birds we are dealing with. Another reason for doing population estimates might be to determine the effectiveness of some lethal control method that has been employed. Fortunately, those species with which we are most concerned are those not on the endangered species list at the present time. Many Ohio farmers would like to see the Red-winged Blackbird on the endangered species list, I think, but it is not there. My particular interest in population estimates is to determine if we can develop an early warning system for the agriculturists, so that they can better anticipate the time they can expect damage from birds. A lot of methods have been tried in the past.

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An estimated 538 million blackbirds and Starlings are found in the United States, based on the national cooperative blackbird/Starling winter roost survey conducted by the U.S. Fish and Wildlife Service during the 1974-75 winter period of December 20-February 15. Ap- proximately 74% or 398 million of these blackbirds and Starlings occurred in the Eastern States, including the tier from Minnesota to Louisiana; 26% or 139 million birds were in the West. The national roosting population in 1974-75 was composed of 11 species (Table 1) in the following approximate proportions: 38% Red-winged Blackbirds; 22% Common Grackles; 20% Starlings; 18% Brown-headed Cowbirds; 2% Brewer’s Blackbirds; and less than 1% six species combined (Rusty Blackbirds, Boat-tailed Grackles, Great-tailed Grackles, Tri-colored Black- birds, Yellow-headed Blackbirds, and Bronzed Cowbirds). (Some 2 million robins also were reported in the 1974-75 survey, though not solicited and therefore not tabulated, from 20 of the blackbird roosts in the Southeast.) The 1974-75 species proportions are similar to those found in the last nationwide winter survey (1969-70). In the 1963-64 national winter survey, Redwings made up 33% and Common Grackles 31% of the total population.

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Several theories have been advanced to estimate effective thermal conductivities of particulate mixtures, but most theories have focused on the dilute case. A method is proposed to estimate the effective thermal conductivity coefficient of mixtures of arbitrary concentration. Earlier the authors developed a theory to determine the expected contact area between different species. This theory is employed to determine the Kapitza resistance of the heterogeneous mixture and forms part of an overall theory to estimate the effective thermal conductivity. Results are compared with other theoretical estimates and with experiments.

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"How large a sample is needed to survey the bird damage to corn in a county in Ohio or New Jersey or South Dakota?" Like those in the Bureau of Sport Fisheries and Wildlife and the U.S.D.A. who have been faced with a question of this sort we found only meager information on which to base an answer, whether the problem related to a county in Ohio or to one in New Jersey, or elsewhere. Many sampling methods and rates of sampling did yield reliable estimates but the judgment was often intuitive or based on the reasonableness of the resulting data. Later, when planning the next study or survey, little additional information was available on whether 40 samples of 5 ears each or 5 samples of 200 ears should be examined, i.e., examination of a large number of small samples or a small number of large samples. What information is needed to make a reliable decision? Those of us involved with the Agricultural Experiment Station regional project concerned with the problems of bird damage to crops, known as NE-49, thought we might supply an ans¬wer if we had a corn field in which all the damage was measured. If all the damage were known, we could then sample this field in various ways and see how the estimates from these samplings compared to the actual damage and pin-point the best and most accurate sampling procedure. Eventually the investigators in four states became involved in this work1 and instead of one field we were able to broaden the geographical base by examining all the corn ears in 2 half-acre sections of fields in each state, 8 sections in all. When the corn had matured well past the dough stage, damage on each corn ear was assessed, without removing the ear from the stalk, by visually estimating the percent of the kernel surface which had been destroyed and rating it in one of 5 damage categories. Measurements (by row-centimeters) of the rows of kernels pecked by birds also were made on selected ears representing all categories and all parts of each field section. These measurements provided conversion factors that, when fed into a computer, were applied to the more than 72,000 visually assessed ears. The machine now had in its memory and could supply on demand a map showing each ear, its location and the intensity of the damage.

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This work quantifies, using ADP and rating curve techniques, the instantaneous outflows at estuarine interfaces: higher to middle estuary and middle to lower estuary, in two medium-sized watersheds (72 000 and 66 000 km(2) of area, respectively), the Jaguaribe and Contas Rivers located in the northeastern (semi-arid) and eastern (tropical humid) Brazilian coasts, respectively. Results from ADP showed that the net water balances show the Contas River as a net water exporter, whereas the Jaguaribe River Estuary is a net water importer. At the Jaguaribe Estuary, water retention during flood tide contributes to 58% of the total volume transferred during the ebb tide from the middle to lower estuary. However, 42% of the total water volume (452 m(3) s(-1)) that entered during flood tide is retained in the middle estuary. In the Contas River, 90% of the total water is retained during the flood tide contributing to the volume transported in the ebb tide from the middle to the lower estuary. Outflows obtained with the rating curve method for the Contas and Jaguaribe Rivers were uniform through time due to river flow normalization by dams in both basins. Estimated outflows with this method are about 65% (Contas) and 95% (Jaguaribe) lower compared to outflows obtained with ADP. This suggests that the outflows obtained with the rating curve method underestimate the net water balance in both systems, particularly in the Jaguaribe River under a semi-arid climate. This underestimation is somewhat decreased due to wetter conditions in the Contas River basin. Copyright. (C) 2011 John Wiley & Sons, Ltd.

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Despite their generality, conventional Volterra filters are inadequate for some applications, due to the huge number of parameters that may be needed for accurate modelling. When a state-space model of the target system is known, this can be assessed by computing its kernels, which also provides valuable information for choosing an adequate alternate Volterra filter structure, if necessary, and is useful for validating parameter estimation procedures. In this letter, we derive expressions for the kernels by using the Carleman bilinearization method, for which an efficient algorithm is given. Simulation results are presented, which confirm the usefulness of the proposed approach.

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Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (< 40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha(-1) (range 6.6 to 112.4) to 8.0 Mg ha(-1) (-2.5 to 23.0).

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In this study, we analyzed the ABCD1 gene in X-linked adrenoleukodystrophy (X-ALD) patients and relatives from 38 unrelated families from South America, as well as phenotypic proportions, survival estimates, and the potential effect of geographical origin in clinical characteristics. Methods: X-ALD patients from Brazil, Argentina and Uruguay were invited to participate in molecular studies to determine their genetic status, characterize the mutations and improve the genetic counseling of their families. All samples were screened by SSCP analysis of PCR fragments, followed by automated DNA sequencing to establish the specific mutation in each family. Age at onset and at death, male phenotypes, genetic status of women, and the effect of family and of latitude of origin were also studied. Results: We identified thirty-six different mutations (twelve novel). This population had an important allelic heterogeneity, as only p. Arg518Gln was repeatedly found (three families). Four cases carried de novo mutations. Intra-familiar phenotype variability was observed in all families. Out of 87 affected males identified, 65% had the cerebral phenotype (CALD). The mean (95% CI) ages at onset and at death of the CALD were 10.9 (9.1-12.7) and 24.7 (19.8-29.6) years. No association was found between phenotypic manifestations and latitude of origin. One index-case was a girl with CALD who carried an ABCD1 mutation, and had completely skewed X inactivation. Conclusions: This study extends the spectrum of mutations in X-ALD, confirms the high rates of de novo mutations and the absence of common mutations, and suggests a possible high frequency of cerebral forms in our population.

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Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)Penman-Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO-Penman-Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature-based estimates by Camargo and Jensen-Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.