994 resultados para quadrat-variance methods
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Although correspondence analysis is now widely available in statistical software packages and applied in a variety of contexts, notably the social and environmental sciences, there are still some misconceptions about this method as well as unresolved issues which remain controversial to this day. In this paper we hope to settle these matters, namely (i) the way CA measures variance in a two-way table and how to compare variances between tables of different sizes, (ii) the influence, or rather lack of influence, of outliers in the usual CA maps, (iii) the scaling issue and the biplot interpretation of maps,(iv) whether or not to rotate a solution, and (v) statistical significance of results.
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When rare is just a matter of sampling: Unexpected dominance of clubtail dragonflies (Odonata, Gomphidae) through different collecting methods at Parque Nacional da Serra do Cipó, Minas Gerais State, Brazil. Capture of dragonfly adults during two short expeditions to Parque Nacional da Serra do Cipó, Minas Gerais State, using three distinct collecting methodsaerial nets, Malaise and light sheet trapsis reported. The results are outstanding due the high number of species of Gomphidae (7 out of 26 Odonata species), including a new species of Cyanogomphus Selys, 1873, obtained by two non-traditional collecting methods. Because active collecting with aerial nets is the standard approach for dragonfly inventories, we discuss some aspects of the use of traps, comparing our results with those in the literature, suggesting they should be used as complementary methods in faunistic studies. Furthermore, Zonophora campanulata annulata Belle, 1983 is recorded for the first time from Minas Gerais State and taxonomic notes about Phyllogomphoides regularis (Selys, 1873) and Progomphus complicatus Selys, 1854 are also given.
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OBJECTIVE:: To determine whether there are differences in health perception and health care use among adolescents with psychosomatic symptoms (PS), with chronic conditions (CCs), and with both conditions compared with healthy controls. METHODS:: By using the SMASH02 database, 4 groups were created: youths with PS but no CCs (N = 1010); youths with CCs but no PS (N = 497); youths with both psychosomatic symptoms and chronic conditions (PSCC, N = 213); and youths with neither PS nor CC (control, N = 5709). We used χ tests and analysis of variance to compare each variable between the 4 groups. In a second step, all health and health care use variables were included in a multinomial regression analysis controlling for significant (p < .05) background variables and using the control group as the reference. RESULTS:: Overall, PS and PSCC youths were significantly more likely to rate their health as poor, to be depressed, and to have consulted several times their primary health care provider or a mental health professional than their healthy peers. With the exception of being depressed, PSCC adolescents reported worse health perception and higher health care use than CC and PS. CONCLUSIONS:: Although PS youths do not define PS as a CC, it should be considered as one. Moreover, having PS represents an additional burden to chronically ill adolescents. Health professionals dealing with adolescents must be aware of the deleterious health effects that PS can have on adolescents and have this diagnosis in mind to better target the treatment and improve their management.
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We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.
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AIM: The specific natural history of superficial soft tissue sarcomas (S-STS) has been rarely considered. We describe the clinical characteristics of a large series of S-STS (N=367) from the French Sarcoma Group (GSF-GETO) database and analyse the prognostic factors affecting outcome. METHODS: We performed univariate and multivariate analyses for overall survival (OS), metastasis-free survival (MFS) and local recurrence-free survival (LRFS). RESULTS: The median age was 59 years. Fifty-eight percent patients were female. Tumour locations were as follows: extremities, 55%; trunk wall, 35.4%; head and neck, 8% and unknown, 1.6%. Median tumour size was 3.0 cm. The most frequent tumour types were unclassified sarcoma (24.3%) and leiomyosarcoma (22.3%). Thirty-three percent of cases were grade 3. Median follow-up was 6.18 years. The 5-year OS, MFS and LRFS rates were 80.9%, 80.7% and 74.7%, respectively. Multivariate analysis retained histological type and wide resection for predicting LRFS and histological type and grade as prognostic factors of MFS. The factors influencing OS were age, histological type, grade and wide resection. STS with early invasion into but not through the underlying fascia had a significantly poorer MFS than with strict S-STS. CONCLUSION: S-STS represent a separate category characterised by a better outcome. Adequate surgery, i.e. wide resection, is essential in the management of S-STS.
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Comparative abundance and diversity of Dryininae (Hymenoptera, Dryinidae) in three savannah phytophysiognomies in southeastern Brazil, under three sampling methods. This study aimed to assess the abundance and diversity of Dryininae in riparian vegetation, Brazilian savannah, and savannah woodland vegetation at the Estação Ecológica de Jataí, in Luiz Antônio, State of São Paulo, Brazil, by using Moericke, Malaise, and light traps. The sampling was carried out from December 2006 to November 2009, and 371 specimens of Dryininae were caught, with the highest frequencies in spring and summer. Fourteen species of Dryinus Latreille, 1804 and one of Thaumatodryinus Perkins, 1905 were identified. The highest frequencies of Dryinus in the riparian vegetation differed significantly from those obtained in the Brazilian savannah and savannah woodland vegetation. In the riparian vegetation, the highest number of Dryinus was collected using light traps and the interactions between abundance and the collection method used were significant. The number of specimens of Dryinus collected in the Brazilian savannah and savannah woodland vegetation using Malaise traps did not differ significantly from those obtained using Moericke traps. Males significantly outnumbered females in the sex ratio of Dryinus. The species diversity of Dryinus based on females collected using Malaise traps was high in the Brazilian savannah. Furthermore, high species richness of female Dryinus was observed in riparian vegetation (six species) and Brazilian savannah (five). The light trap was the most successful method for sampling diversity of Dryininae.
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Pharmacogenetics, the study of how individual genetic profiles influence the response to drugs, is an important topic. Results from pharmacogenetics studies in various clinical settings may lead to personalized medicine. Herein, we present the most important concepts of this discipline, as well as currently-used study methods.
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PURPOSE: This study aimed at examining the influence of different playing surfaces on in-shoe loading patterns in each foot (back and front) separately during the first serve in tennis. METHODS: Ten competitive tennis players completed randomly five first (ie, flat) serves on two different playing surfaces: clay vs GreenSet. Maximum and mean force, peak and mean pressure, mean area, contact area and relative load were recorded by Pedar insoles divided into 9 areas for analysis. RESULTS: Mean pressure was significantly lower (123 ± 30 vs 98 ± 26 kPa; -18.5%; P < .05) on clay than on GreenSet when examining the entire back foot. GreenSet induced higher mean pressures under the medial forefoot, lateral forefoot and hallux of the back foot (+9.9%, +3.5% and +15.9%, respectively; both P < .01) in conjunction with a trend toward higher maximal forces in the back hallux (+15.1%, P = .08). Peak pressures recorded under the central and lateral forefoot (+21.8% and +25.1%; P < .05) of the front foot but also the mean area values measured on the back medial and lateral midfoot were higher (P < .05) on clay. No significant interaction between foot region and playing surface on relative load was found. CONCLUSIONS: It is suggested that in-shoe loading parameters characterizing the first serve in tennis are adjusted according to the ground type surface. A lesser asymmetry in peak (P < .01) and mean (P < .001) pressures between the two feet was found on clay, suggesting a greater need for stability on this surface.
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Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.
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Several ink dating methods based on solvents analysis using gas chromatography/mass spectrometry (GC/MS) were proposed in the last decades. These methods follow the drying of solvents from ballpoint pen inks on paper and seem very promising. However, several questions arose over the last few years among questioned documents examiners regarding the transparency and reproducibility of the proposed techniques. These questions should be carefully studied for accurate and ethical application of this methodology in casework. Inspired by a real investigation involving ink dating, the present paper discusses this particular issue throughout four main topics: aging processes, dating methods, validation procedures and data interpretation. This work presents a wide picture of the ink dating field, warns about potential shortcomings and also proposes some solutions to avoid reporting errors in court.
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In earlier work, the present authors have shown that hardness profiles are less dependent on the level of calculation than energy profiles for potential energy surfaces (PESs) having pathological behaviors. At variance with energy profiles, hardness profiles always show the correct number of stationary points. This characteristic has been used to indicate the existence of spurious stationary points on the PESs. In the present work, we apply this methodology to the hydrogen fluoride dimer, a classical difficult case for the density functional theory methods
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Two concentration methods for fast and routine determination of caffeine (using HPLC-UV detection) in surface, and wastewater are evaluated. Both methods are based on solid-phase extraction (SPE) concentration with octadecyl silica sorbents. A common “offline” SPE procedure shows that quantitative recovery of caffeine is obtained with 2 mL of an elution mixture solvent methanol-water containing at least 60% methanol. The method detection limit is 0.1 μg L−1 when percolating 1 L samples through the cartridge. The development of an “online” SPE method based on a mini-SPE column, containing 100 mg of the same sorbent, directly connected to the HPLC system allows the method detection limit to be decreased to 10 ng L−1 with a sample volume of 100 mL. The “offline” SPE method is applied to the analysis of caffeine in wastewater samples, whereas the “on-line” method is used for analysis in natural waters from streams receiving significant water intakes from local wastewater treatment plants
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In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.