928 resultados para Weights initialization


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The educational system in Spain is undergoing a reorganization. At present, high-school graduates who want to enroll at a public university must take a set of examinations Pruebas de Aptitud para el Acceso a la Universidad (PAAU). A "new formula" (components, weights, type of exam,...) for university admission is been discussed. The present paper summarizes part of the research done by the author in her PhD. The context for this thesis is the evaluation of large-scale and complex systems of assessment. The main objectives were: to achieve a deep knowledge of the entire university admissions process in Spain, to discover the main sources of uncertainty and topromote empirical research in a continual improvement of the entire process. Focusing in the suitable statistical models and strategies which allow to high-light the imperfections of the system and reduce them, the paper develops, among other approaches, some applications of multilevel modeling.

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We compare two methods for visualising contingency tables and developa method called the ratio map which combines the good properties of both.The first is a biplot based on the logratio approach to compositional dataanalysis. This approach is founded on the principle of subcompositionalcoherence, which assures that results are invariant to considering subsetsof the composition. The second approach, correspondence analysis, isbased on the chi-square approach to contingency table analysis. Acornerstone of correspondence analysis is the principle of distributionalequivalence, which assures invariance in the results when rows or columnswith identical conditional proportions are merged. Both methods may bedescribed as singular value decompositions of appropriately transformedmatrices. Correspondence analysis includes a weighting of the rows andcolumns proportional to the margins of the table. If this idea of row andcolumn weights is introduced into the logratio biplot, we obtain a methodwhich obeys both principles of subcompositional coherence and distributionalequivalence.

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Blowflies utilize discrete and ephemeral sites for breeding and larval nutrition. After the exhaustion of food, the larvae begin dispersing to search for sites to pupate or to additional food source, process referred as postfeeding larval dispersal. Some of the most important aspects of this process were investigated in Chrysomya megacephala, utilizing a circular arena to permit the radial dispersion of larvae from the center. To determinate the localization of each pupa, the arena was split in 72 equal sectors from the center. For each pupa, distance from the center of arena, weight and depth were determined. Statistical tests were performed to verify the relation among weight, depth and distance of burying for pupation. It was verified that the larvae that disperse farther are those with higher weights. The majority of individuals reached the depth of burying for pupation between 7 and 18 cm. The study of this process of dispersion can be utilized in the estimation of postmortem interval (PMI) for human corpses in medico-criminal investigations.

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Microtubule-associated protein 1b, previously also referred to as microtubule-associated protein 5 or microtubule-associated protein 1x, is a major component of the juvenile cytoskeleton, and is essential during the early differentiation of neurons. It is required for axonal growth and its function is influenced by phosphorylation. The distribution of microtubule-associated protein 1b in kitten cerebellum and cortex during postnatal development was studied with two monoclonal antibodies. Hybridoma clone AA6 detected a non-phosphorylated site, while clone 125 detected a site phosphorylated by casein-kinase II. On blots, both monoclonal antibodies stained the same two proteins of similar molecular weights, also referred to as microtubule-associated protein 5a and 5b. Antibody 125 detected a phosphorylated epitope on both microtubule-associated protein 1b forms; dephosphorylation by alkaline phosphatase abolished the immunological detection. During development of cat cortex and cerebellum, AA6 stained the perikarya and dendrites of neurons during their early differentiation, and especially labelled newly generated axons. The staining decreased during development, and axonal staining was reduced in adult tissue. In contrast to previous reports which demonstrated that antibodies against phosphorylated microtubule-associated protein 1b label exclusively axons, antibody 125 also localized microtubule-associated protein 1b in cell bodies and dendrites, even in adulthood. Some nuclear staining was observed, indicating that a phosphorylated form of microtubule-associated protein 1b may participate in nuclear function. These results demonstrate that microtubule-associated protein 1b is subject to CK2-type phosphorylation throughout neuronal maturation and suggest that phosphorylation of microtubule-associated protein 1b may participate in juvenile and mature-type microtubule functions throughout development.

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The sequence profile method (Gribskov M, McLachlan AD, Eisenberg D, 1987, Proc Natl Acad Sci USA 84:4355-4358) is a powerful tool to detect distant relationships between amino acid sequences. A profile is a table of position-specific scores and gap penalties, providing a generalized description of a protein motif, which can be used for sequence alignments and database searches instead of an individual sequence. A sequence profile is derived from a multiple sequence alignment. We have found 2 ways to improve the sensitivity of sequence profiles: (1) Sequence weights: Usage of individual weights for each sequence avoids bias toward closely related sequences. These weights are automatically assigned based on the distance of the sequences using a published procedure (Sibbald PR, Argos P, 1990, J Mol Biol 216:813-818). (2) Amino acid substitution table: In addition to the alignment, the construction of a profile also needs an amino acid substitution table. We have found that in some cases a new table, the BLOSUM45 table (Henikoff S, Henikoff JG, 1992, Proc Natl Acad Sci USA 89:10915-10919), is more sensitive than the original Dayhoff table or the modified Dayhoff table used in the current implementation. Profiles derived by the improved method are more sensitive and selective in a number of cases where previous methods have failed to completely separate true members from false positives.

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PURPOSE To develop a score predicting the risk of adverse events (AEs) in pediatric patients with cancer who experience fever and neutropenia (FN) and to evaluate its performance. PATIENTS AND METHODS Pediatric patients with cancer presenting with FN induced by nonmyeloablative chemotherapy were observed in a prospective multicenter study. A score predicting the risk of future AEs (ie, serious medical complication, microbiologically defined infection, radiologically confirmed pneumonia) was developed from a multivariate mixed logistic regression model. Its cross-validated predictive performance was compared with that of published risk prediction rules. Results An AE was reported in 122 (29%) of 423 FN episodes. In 57 episodes (13%), the first AE was known only after reassessment after 8 to 24 hours of inpatient management. Predicting AE at reassessment was better than prediction at presentation with FN. A differential leukocyte count did not increase the predictive performance. The score predicting future AE in 358 episodes without known AE at reassessment used the following four variables: preceding chemotherapy more intensive than acute lymphoblastic leukemia maintenance (weight = 4), hemoglobin > or = 90 g/L (weight = 5), leukocyte count less than 0.3 G/L (weight = 3), and platelet count less than 50 G/L (weight = 3). A score (sum of weights) > or = 9 predicted future AEs. The cross-validated performance of this score exceeded the performance of published risk prediction rules. At an overall sensitivity of 92%, 35% of the episodes were classified as low risk, with a specificity of 45% and a negative predictive value of 93%. CONCLUSION This score, based on four routinely accessible characteristics, accurately identifies pediatric patients with cancer with FN at risk for AEs after reassessment.

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The biology of nymphs and adults of the neotropical pentatomid, Dichelops melacanthus (Dallas), feeding on the natural foods, soybean, Glycine max (L.) Merrill immature pods, and corn, Zea mays L. immature seeds, and on an artificial dry diet, was studied in the laboratory. Nymph developmental time was shorter on the natural foods (ca. 21-22 days) than on the artificial diet (28 days), and most nymphs reached adulthood on the food plants (55% on soybean and 73% on corn) than on the artificial diet (40%). Fresh body weight at adult emergence was similar and higher for females raised as nymphs on the natural foods, compared to females from nymphs raised on the artificial diet; for males, weights were similar on all foods. Mean (female and male) survivorship up to day 20, decreased from 55% on soybean to 40% on corn, down to 0% on the artificial diet. Total longevity for females was higher on soybean, while for males was similar on all foods. About three times more females oviposited on soybean than on corn, but fecundity/female was similar on both foods. On the artificial diet, only one out of 30 females oviposited. Fresh body weight of adults increased significantly during the first week of adult life, and at the end of the 3rd week, weight gain was similar on all foods.

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The effectiveness of decision rules depends on characteristics of bothrules and environments. A theoretical analysis of environments specifiesthe relative predictive accuracies of the lexicographic rule 'take-the-best'(TTB) and other simple strategies for binary choice. We identify threefactors: how the environment weights variables; characteristics of choicesets; and error. For cases involving from three to five binary cues, TTBis effective across many environments. However, hybrids of equal weights(EW) and TTB models are more effective as environments become morecompensatory. In the presence of error, TTB and similar models do not predictmuch better than a naïve model that exploits dominance. We emphasizepsychological implications and the need for more complete theories of theenvironment that include the role of error.

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Several studies have reported high performance of simple decision heuristics multi-attribute decision making. In this paper, we focus on situations where attributes are binary and analyze the performance of Deterministic-Elimination-By-Aspects (DEBA) and similar decision heuristics. We consider non-increasing weights and two probabilistic models for the attribute values: one where attribute values are independent Bernoulli randomvariables; the other one where they are binary random variables with inter-attribute positive correlations. Using these models, we show that good performance of DEBA is explained by the presence of cumulative as opposed to simple dominance. We therefore introduce the concepts of cumulative dominance compliance and fully cumulative dominance compliance and show that DEBA satisfies those properties. We derive a lower bound with which cumulative dominance compliant heuristics will choose a best alternative and show that, even with many attributes, this is not small. We also derive an upper bound for the expected loss of fully cumulative compliance heuristics and show that this is moderateeven when the number of attributes is large. Both bounds are independent of the values ofthe weights.

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In the fixed design regression model, additional weights areconsidered for the Nadaraya--Watson and Gasser--M\"uller kernel estimators.We study their asymptotic behavior and the relationships between new andclassical estimators. For a simple family of weights, and considering theIMSE as global loss criterion, we show some possible theoretical advantages.An empirical study illustrates the performance of the weighted estimatorsin finite samples.

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A phylogenetic analysis is presented of subgenera and species-groups of Mischocyttarus de Saussure, the largest genus of social wasps. The analysis is based on 62 morphological and nest architecture characters, coded for 71 terminals representing much of the taxonomic diversity within the genus, plus three outgroup terminals representing other polistine tribes. The main conclusions about phylogenetic relationships within the genus are based on parsimony analysis under implied weights. Monophyly of Mischocyttarus is confirmed as well as that of most of the previously recognized subgenera: Mischocyttarus s. str., Clypeopolybia, Monogynoecus, Scytokeraia, Phi, Kappa, Megacanthopus and Omega sensu Richards (1978). Haplometrobius as conceived by Richards (1978) is not a monophyletic taxon, but some of its species-groups are monophyletic. The groups of M.artifex and M.cerberus are raised to subgenus level, and a new concept of Haplometrobius restricts it to the group of M.iheringi (the type species of this subgenus) in the sense of this work. The concept of subgenus Omega is widened to include the species-groups of M.surinamensis and M.prominulus. Besides the new subgeneric classification presented, limits and diagnoses of all species-groups of the subgenera Phi and Haplometrobius sensu Richards (1978) are discussed, and a new key for all subgenera and species-groups of Mischocyttarus is also presented.

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Most methods for small-area estimation are based on composite estimators derived from design- or model-based methods. A composite estimator is a linear combination of a direct and an indirect estimator with weights that usually depend on unknown parameters which need to be estimated. Although model-based small-area estimators are usually based on random-effects models, the assumption of fixed effects is at face value more appropriate.Model-based estimators are justified by the assumption of random (interchangeable) area effects; in practice, however, areas are not interchangeable. In the present paper we empirically assess the quality of several small-area estimators in the setting in which the area effects are treated as fixed. We consider two settings: one that draws samples from a theoretical population, and another that draws samples from an empirical population of a labor force register maintained by the National Institute of Social Security (NISS) of Catalonia. We distinguish two types of composite estimators: a) those that use weights that involve area specific estimates of bias and variance; and, b) those that use weights that involve a common variance and a common squared bias estimate for all the areas. We assess their precision and discuss alternatives to optimizing composite estimation in applications.

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We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

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This paper establishes a general framework for metric scaling of any distance measure between individuals based on a rectangular individuals-by-variables data matrix. The method allows visualization of both individuals and variables as well as preserving all the good properties of principal axis methods such as principal components and correspondence analysis, based on the singular-value decomposition, including the decomposition of variance into components along principal axes which provide the numerical diagnostics known as contributions. The idea is inspired from the chi-square distance in correspondence analysis which weights each coordinate by an amount calculated from the margins of the data table. In weighted metric multidimensional scaling (WMDS) we allow these weights to be unknown parameters which are estimated from the data to maximize the fit to the original distances. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing a matrix and displaying its rows and columns in biplots.

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Sarcosaprophagous macroinvertebrates (earthworms, termites and a number of Diptera larvae) enhance changes in the physical and chemical properties of organic matter during degradation and stabilization processes in composting, causing a decrease in the molecular weights of compounds. This activity makes these organisms excellent recyclers of organic matter. This article evaluates the succession of insects associated with the decomposition of solid urban waste separated at the source. The study was carried out in the city of Medellin, Colombia. A total of 11,732 individuals were determined, belonging to the classes Insecta and Arachnida. Species of three orders of Insecta were identified, Diptera, Coleoptera and Hymenoptera. Diptera corresponding to 98.5% of the total, was the most abundant and diverse group, with 16 families (Calliphoridae, Drosophilidae, Psychodidae, Fanniidae, Muscidae, Milichiidae, Ulidiidae, Scatopsidae, Sepsidae, Sphaeroceridae, Heleomyzidae, Stratiomyidae, Syrphidae, Phoridae, Tephritidae and Curtonotidae) followed by Coleoptera with five families (Carabidae, Staphylinidae, Ptiliidae, Hydrophilidae and Phalacaridae). Three stages were observed during the composting process, allowing species associated with each stage to be identified. Other species were also present throughout the whole process. In terms of number of species, Diptera was the most important group observed, particularly Ornidia obesa, considered a highly invasive species, and Hermetia illuscens, both reported as beneficial for decomposition of organic matter.