930 resultados para Canonical correlation
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We show the equivalence between the use of correspondence analysis (CA)of concadenated tables and the application of a particular version ofconjoint analysis called categorical conjoint measurement (CCM). Theconnection is established using canonical correlation (CC). The second part introduces the interaction e¤ects in all three variants of theanalysis and shows how to pass between the results of each analysis.
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Araucaria angustifolia (Bert.) O. Kuntze is the main component of the Mixed Ombrophilous forest and, in the State of São Paulo, it is associated with a high diversity of soil organisms, essential for the maintenance of soil quality, making the conservation of this ecosystem a major and pressing challenge. The objective of this study was to identify the physical and chemical properties that are most closely correlated with dehydrogenase enzyme activity, basal respiration and microbial biomass under native (NF) and replanted (RF) Araucaria angustifolia forests in three regions of the state of São Paulo, in winter and summer. The main differentiating factors between the areas were also determined. Each forest was represented by three true replications; at each site, from around the araucaria trees, 15 soil samples (0-20 cm) were collected to evaluate the soil physical, chemical and microbiological properties. At the same points, forest litter was sampled to assess mass and chemical properties. The following microbiological properties were evaluated: microbial biomass carbon (MBC), basal respiration (CO2-C), metabolic quotient (Q: CO2), dehydrogenase enzyme activity (DHA) as well as the physical properties (moisture, bulk density, macroporosity and total porosity), soil chemical properties [pH, organic carbon (org-C), P, Ca, K, Mg, Al, H+Al], litter dry mass, and C, N and S contents. The data were subjected to analysis of variance (TWO-WAY: ANOVA). A Canonical Discriminant Analysis (CDA) and a Canonical Correlation Analysis (CCA) were also performed. In the soil under NF, the values of K, P, soil macroporosity, and litter dry mass were higher and Q: CO2 and DHA lower, regardless of the sampling period, and DHA was lower in winter. In the RF areas, the levels of moisture, porosity and Q: CO2 were higher in both sampling periods, and DHA was higher in winter. The MBC was only higher under NF in the summer, while the litter contents of C, N and S were greater in winter. In winter, CCA showed a high correlation of DHA with CO2-C, pH and H+Al, while in the summer org-C, moisture, Mg, pH and litter C were more associated with DHA and CO2-C. The CDA indicated H+Al, available P, total porosity, litter S content, and soil moisture as the most discriminating variables between NF and RF, but moisture was the most relevant, in both seasons and CO2-C only in winter. The combined analysis of CCA and CDA showed that the contribution of the microbiological variables to a differentiation of the areas was small at both samplings, which may indicate that the period after reforestation was long enough to allow an almost complete recovery of the microbial activity.
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In the State of Rio Grande do Sul, the municipality of Pelotas is responsible for 90 % of peach production due to its suitable climate and soil conditions. However, there is the need for new studies that aim at improved fruit quality and increased yield. The aim of this study was to evaluate the relationship that exists between soil physical properties and properties in the peach plant in the years 2010 and 2011 by the technique of multivariate canonical correlation. The experiment was conducted in a peach orchard located in the municipality of Morro Redondo, RS, Brazil, where an experimental grid of 101 plants was established. In a trench dug beside each one of the 101 plants, soil samples were collected to determine silt, clay, and sand contents, soil density, total porosity, macroporosity, microporosity, and volumetric water content in the 0.00-0.10 and 0.10-0.20 m layers, as well as the depth of the A horizon. In each plant and in each year, the following properties were assessed: trunk diameter, fruit size and number of fruits per plant, average weight of the fruit per plant, fruit pulp firmness, Brix content, and yield from the orchard. Exploratory analysis of the data was undertaken by descriptive statistics, and the relationships between the physical properties of the soil and of the plant were assessed by canonical correlation analysis. The results showed that the clay and microporosity variables were those that exhibited the highest coefficients of canonical cross-loading with the plant properties in the soil layers assessed, and that the variable of mean weight of the fruit per plant was that which had the highest coefficients of canonical loading within the plant group for the two years assessed.
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I t is generally accepted among scholars that individual learning and team learning contribute to the concept we refer to as organizational learning. However, a small number of quantitative and qualitative studies that have investigated their relationship reported contradicting results. This thesis investigated the relationship between individual learning, team learning, and organizational learning. A survey instrument was used to collect information on individual learning, team learning, and organizational learning. The study sample comprised of supervisors from the clinical laboratories in teaching hospitals and community hospitals in Ontario. The analyses utilized a linear regression to investigate the relationship between individual and team learning. The relationship between individual and organizational learning, and team and organizational learning were simultaneously investigated with canonical correlation and set correlation. T-test and multivariate analysis of variance were used to compare the differences in learning scores of respondents employed by laboratories in teaching and those employed by community hospitals. The study validated its tests results with 1,000 bootstrap replications. Results from this study suggest that there are moderate correlations between individual learning and team learning. The correlation individual learning and organizational learning and team learning and organizational learning appeared to be weak. The scores of the three learning levels show statistically significant differences between respondents from laboratories in teaching hospitals and respondents from community hospitals.
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Temperature and precipitation are major forcing factors influencing grapevine phenology and yield, as well as wine quality. Bioclimatic indices describing the suitability of a particular region for wine production are a commonly used tool for viticultural zoning. For this research these indices were computed for Europe by using the E-OBS gridded daily temperature and precipitation data set for the period from 1950 to 2009. Results showed strong regional contrasts based on the different index patterns and reproduced the wide diversity of local conditions that largely explain the quality and diversity of grapevines being grown across Europe. Owing to the strong inter-annual variability in the indices, a trend analysis and a principal component analysis were applied together with an assessment of their mean patterns. Significant trends were identified in the Winkler and Huglin indices, particularly for southwestern Europe. Four statistically significant orthogonal modes of variability were isolated for the Huglin index (HI), jointly representing 82% of the total variance in Europe. The leading mode was largely dominant (48% of variance) and mainly reflected the observed historical long-term changes. The other 3 modes corresponded to regional dipoles within Europe. Despite the relevance of local and regional climatic characteristics to grapevines, it was demonstrated via canonical correlation analysis that the observed inter-annual variability of the HI was strongly controlled by the large-scale atmospheric circulation during the growing season (April to September).
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Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.
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This paper uses canonical correlation analisys to identify leading and coincident indicators of economic activity in Brazil. ln contrast with the traditional literature on the subject, no restrictions are made regarding the number of common cycles that are necessary to explain the complete cyclical behavior of the coincident variables. For the brazillian data, it is found that three common cycles exhaust all the cyclical pattern of economic activity. Based on the methodology developed here, it is also sugested an alternative chronology of the recent brazillian recessions.
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We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.
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We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.
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We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We compare the performance of our index with other currently popular coincident indices of economic activity.
Phytoplankton structure in two contrasting cascade reservoirs (Paranapanema River, Southeast Brazil)
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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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The impact of shrimp fisheries in tropical regions has become comparable to the world's most intensively exploited temperate shed ecosystems. The increase in the fishing fleet in south-eastern Brazil and the decrease in landings of profitable shrimp species have contributed to the incorporation of additional species into those fisheries. The goal of the present study is to investigate the influence of environmental factors on the abundance patterns of shrimp communities on the south-eastern coast of Brazil, over a period of two years. Monthly collections were conducted in the Ubatuba and Caraguatatuba regions using a commercial shrimp fishing boat equipped with 'double-rig' nets. Each region was divided into 7 sampling stations up to 35 m deep. The relationship between the environmental factors and the abundance patterns in the shrimp communities was assessed using a canonical correlation analysis (CCorrA). The first set of variables used during the CCorrA included environmental characteristics and the second set of variables the abundance of the studied species. A total of 374,915 individuals were collected during the present study. Xiphopenaeus kroyeri showed the highest abundance (273,127), followed by Artemesia longinaris (73,422), and Pleoticus muelleri (15,262). In the first root, depth and temperature showed the highest factor loadings (0.9 and -0.7) and canonical weights (0.6 and -0.4). These environmental factors were strongly associated with the abundance of X. kroyeri (factor loading = - 0.9 and canonical weight = - 0.9). The second root demonstrated a positive relationship between abundance of P. muelleri and depth, and an inverse association with bottom temperature. The abundance patterns of X. kroyeri and P. muelleri were strongly affected by the water mass South Atlantic Central Water (cold waters =15 degrees C), which can lead to a temperature decrease in deeper areas (> 15 m). Thus, the opposite abundance trend for depth of these species might reflect bathymetric variation in temperature, a clear example of distinct behavioural differences of species of different origins, either tropical (X. kroyeri) or subantarctic (P. muelleri). The low overall association between environmental parameters and shrimp abundance patterns indicates that each studied species might have responded idiosyncratically to environmental variation, such that a general community-level response was not apparent. However, other confounding factors such as intraspecific migration patterns might have also played a role in generating the observed patterns.
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Metabolic differences derived from social stress usually show data with high variance that may hinder the finding of important differences. Since such high variance may be caused by agonistic variability occurring during social interactions, this work tested whether metabolism is associated with agonistic profile in the cichlid fish Nile tilapia, Oreochromis niloticus (L.). Metabolism was inferred from oxygen consumption, resistance to progressive hypoxia and ventilatory rate. Fifteen pairs of alevins were used for each metabolic and behavioral series. An ethogram based on 8 types of agonistic interactions was employed. Agonistic profiles were determined and associated with the physiological parameters later on. The test of canonical correlation showed significant association between some agonistic profiles and metabolism. Ventral nipping and lateral fight appeared as the two most important in promoting association with metabolism.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)