30 resultados para Principal component analysis (PCA)
Resumo:
CHEMICAL PROFILE COMPARISON OF SUGARCANE SPIRITS FROM THE SAME WINE DISTILLED IN ALEMBICS AND COLUMNS. Six wines were distilled in two different distillation apparatus (alembic and column) producing 24 distillates (6 for each alembic fraction - head, heart and tail; 6 column distillates). The chemical composition of distillates from the same wine was determined using chromatographic techniques. Analytical data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allowing discrimination of four clusters according to chemical profiles. Both distillation processes influenced the sugarcane spirits chemical quality since two types of distillates with different quantitative chemical profiles were produced after the elimination of fermentation step influence.
Resumo:
Locomotor capacity is often considered an excellent measure of whole animal performance because it requires the integrated functioning of many morphological, physiological (and biochemical) traits. However, because studies tend to focus on either structural or functional suits of traits, we know little on whether and how morphological and physiological traits coevolve to produce adequate locomotor capacities. Hence, we investigate the evolutionary relationships between morphological and physiological parameters related to exercise physiology, using tropidurine lizards as a model. We employ a phylogenetic principal component analysis (PCA) to identify variable clusters (factors) related to morphology, energetic metabolism and muscle metabolism, and then analyze the relationships between these clusters and measures of locomotor performance, using two models (star and hierarchical phylogenies). Our data indicate that sprint performance is enhanced by simultaneous evolutionary tendencies affecting relative limb and tail size and physiological traits. Specifically, the high absolute sprint speeds exhibited by tropidurines from the sand dunes are explained by longer limbs, feet and tails and an increased proportion of glycolytic fibers in the leg muscle, contrasting with their lower capacity for overall oxidative metabolism [principal component (PC1)]. However, when sprint speeds are corrected for body size, performance correlates with a cluster (PC3) composed by moderate loads for activity metabolic rate and body size. The simultaneous measurement of morphological and physiological parameters is a powerful tool for exploring patterns of coadaptation and proposing morphophysiological associations that are not directly predictable from theory. This approach may trigger novel directions for investigating the evolution of form and function, particularly in the context of organismal performance.
Resumo:
In humans and other mammals, sperm morphology has been considered one of the most important predictive parameters of fertility. The objective was to determine the presence and distribution of sperm head morphometric subpopulations in a nonhuman primate model (Callithrix jacchus), using an objective computer analysis system and principal component analysis (PCA) methods to establish the relationship between the subpopulation distribution observed and among-donor variation. The PCA method revealed a stable number of principal components in all donors studied, that represented more than 85% of the cumulative variance in all cases. After cluster analysis, a variable number (from three to seven) sperm morphometric subpopulations were identified with defined sperm dimensions and shapes. There were differences in the distribution of the sperm morphometric subpopulations (P < 0.001) in all ejaculates among the four donors analyzed. In conclusion, in this study, computerized sperm analysis methods combined with PCA cluster analyses were useful to identify, classify, and characterize various head sperm morphometric subpopulations in nonhuman primates, yielding considerable biological information. In addition, because all individuals were kept in the same conditions, differences in the distribution of these subpopulations were not attributed to external or management factors. Finally, the substantial information derived from subpopulation analyses provided new and relevant biological knowledge which may have a practical use for future studies in human and nonhuman primate ejaculates, including identifying individuals more suitable for assisted reproductive technologies. (c) 2012 Elsevier Inc. All rights reserved.
Resumo:
Gunshot residues (GSR) can be used in forensic evaluations to obtain information about the type of gun and ammunition used in a crime. In this work, we present our efforts to develop a promising new method to discriminate the type of gun [four different guns were used: two handguns (0.38 revolver and 0.380 pistol) and two long-barrelled guns (12-calibre pump-action shotgun and 0.38 repeating rifle)] and ammunition (five different types: normal, semi-jacketed, full-jacketed, green, and 3T) used by a suspect. The proposed approach is based on information obtained from cyclic voltammograms recorded in solutions containing GSR collected from the hands of the shooters, using a gold microelectrode; the information was further analysed by non-supervised pattern-recognition methods [(Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA)]. In all cases (gun and ammunition discrimination), good separation among different samples in the score plots and dendrograms was achieved. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Fractal theory presents a large number of applications to image and signal analysis. Although the fractal dimension can be used as an image object descriptor, a multiscale approach, such as multiscale fractal dimension (MFD), increases the amount of information extracted from an object. MFD provides a curve which describes object complexity along the scale. However, this curve presents much redundant information, which could be discarded without loss in performance. Thus, it is necessary the use of a descriptor technique to analyze this curve and also to reduce the dimensionality of these data by selecting its meaningful descriptors. This paper shows a comparative study among different techniques for MFD descriptors generation. It compares the use of well-known and state-of-the-art descriptors, such as Fourier, Wavelet, Polynomial Approximation (PA), Functional Data Analysis (FDA), Principal Component Analysis (PCA), Symbolic Aggregate Approximation (SAX), kernel PCA, Independent Component Analysis (ICA), geometrical and statistical features. The descriptors are evaluated in a classification experiment using Linear Discriminant Analysis over the descriptors computed from MFD curves from two data sets: generic shapes and rotated fish contours. Results indicate that PCA, FDA, PA and Wavelet Approximation provide the best MFD descriptors for recognition and classification tasks. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Six wines were distilled in two different distillation apparatus (alembic and column) producing 24 distillates (6 for each alembic fraction - head, heart and tail; 6 column distillates). The chemical composition of distillates from the same wine was determined using chromatographic techniques. Analytical data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allowing discrimination of four clusters according to chemical profiles. Both distillation processes influenced the sugarcane spirits chemical quality since two types of distillates with different quantitative chemical profiles were produced after the elimination of fermentation step influence.
Resumo:
The purpose of this study was to assess the composition of the rainwater in Araraquara City, Brazil, a region strongly influenced by pre-harvest burning of sugar cane crops. Chemical and mineralogical variables were measured in rainwater collected during the harvest, dry period of 2009 and the non-harvest, wet period of 2010. Ca2+ and NH4+ were responsible for 55% of cations and NO3- for 45% of anions in rainwater. Al and Fe along with K were the most abundant among trace elements in both soluble and insoluble fractions. High volume weighted mean concentration (VWM) for most of the analyzed species were observed in the harvest, dry period, mainly due to agricultural activities and meteorological conditions. The chemistry of the Araraquara rainwater and principal component analysis (PCA) quantification clearly indicate the concurrence of a diversity of sources from natural to anthropogenic especially related to agricultural activities.
Resumo:
Uca populations have an important functional and structural role in many estuarine ecosystems. These crabs exhibit distinct physiological tolerance to salinity gradients, which may partially explain their heterogeneous distribution. In order to investigate the population structure and distribution of Uca spp. in a tropical estuary, we sampled Uca crabs in replicated 0.75 m2 quadrats at six muddy plain areas during monthly intervals between July and November 2012 in spring tidal conditions. Environmental factors including water temperature, salinity, sediment total organic matter, chlorophyll-a, and granulometry were analyzed. We sampled a total of 2919 individuals distributed in three Uca species (U. uruguayensis, U. thayeri and U. maracoani), from which U. uruguayensis was dominant. The density and biomass of individuals were spatially and temporally heterogeneous. During October and November we found higher Uca spp. densities (71.3 ± 47.3 to 77.6 ± 44,5 ind. 0.75 m-²) and biomass (1.8 ± 1.1 to 2.1 ± 1.0 g 0.75 m-2 AFDW) if compared to the previous months, density (July 55,5± 44,1 August 52,5± 34,9 and September 47,7 ± 25,6 ind. 0,75m-²) and biomass in others months (July 1,0± 0,94 August 1,1 ± 0,72 and September 1,3±0,93 g 0.75 m-2 AFDW ). The same pattern was found for other variables, such as salinity (32 and 34), organic matter (30 and 67%) and chlorophyll-a (89 and 46 μg g-1). In two study areas we found this pattern which suggests that higher Uca productivity and food availability are related. A principal component analysis (PCA) suggests that salinity and granulometry (silt) can influence (60% correspondence) the distribution of U. maracoani. For U. uruguayensis and U. thayeri the PCA suggests chlorophyll-a was important, which is a good indicator for labile organic matter. Our study suggests that the population structure and distribution of Uca species may be regulated by food availability, supporting their utility as biological models for ecosystem monitoring.
Resumo:
This paper establishes the spawning habitat of the Brazilian sardine Sardinella brasiliensis and investigates the spatial variability of egg density and its relation with oceanographic conditions in the shelf of the south-east Brazil Bight (SBB). The spawning habitats of S. brasiliensis have been defined in terms of spatial models of egg density, temperature-salinity plots, quotient (Q) analysis and remote sensing data. Quotient curves (Q(C)) were constructed using the geographic distribution of egg density, temperature and salinity from samples collected during nine survey cruises between 1976 and 1993. The interannual sea surface temperature (SST) variability was determined using principal component analysis on the SST anomalies (SSTA) estimated from remote sensing data over the period between 1985 and 2007. The spatial pattern of egg occurrences in the SBB indicated that the largest concentration occurred between Paranagua and Sao Sebastiao. Spawning habitat expanded and contracted during the years, fluctuating around Paranagua. In January 1978 and January 1993, eggs were found nearly everywhere along the inner shelf of the SBB, while in January 1988 and 1991 spawning had contracted to their southernmost position. The SSTA maps for the spawning periods showed that in the case of habitat expansion (1993 only) anomalies over the SBB were zero or slightly negative, whereas for the contraction period anomalies were all positive. Sardinella brasiliensis is capable of exploring suitable spawning sites provided by the entrainment of the colder and less-saline South Atlantic Central Water onto the shelf by means of both coastal wind-driven (to the north-east of the SBB) and meander-induced (to the south-west of the SBB) upwelling.
Resumo:
EVAPORATIVE LIGHT-SCATTERING DETECTOR FOR ANALYSIS OF NATURAL PRODUCTS. The interest in the use of evaporative light scattering detector (ELSD) for the analysis of different classes of natural products has grown over the years. This is because this detector has become an excellent alternative compared to other types of detectors, such as the refractive index detector and the ultraviolet (UV) detector. This review describes the basic principles of ELSD functioning and discusses the advantages and disadvantages in using an ELSD for the analysis of organic compounds. Additionally, an overview, covering the last 23 years, of ELSD applications in natural products analysis (saponins, terpenes, carbohydrates, glycosides, alkaloids, steroids, flavonoids, peptides, polyketides, coumarins and iridoids) is presented and discussed.
Resumo:
In this paper, a novel method for power quality signal decomposition is proposed based on Independent Component Analysis (ICA). This method aims to decompose the power system signal (voltage or current) into components that can provide more specific information about the different disturbances which are occurring simultaneously during a multiple disturbance situation. The ICA is originally a multichannel technique. However, the method proposes its use to blindly separate out disturbances existing in a single measured signal (single channel). Therefore, a preprocessing step for the ICA is proposed using a filter bank. The proposed method was applied to synthetic data, simulated data, as well as actual power system signals, showing a very good performance. A comparison with the decomposition provided by the Discrete Wavelet Transform shows that the proposed method presented better decoupling for the analyzed data. (C) 2012 Elsevier Ltd. All rights reserved.
Resumo:
We investigated dietary intake patterns (DIP) in adolescents (14-18 year-olds) and the association with demographic and socioeconomic characteristics and lifestyle variables. This school-based survey was carried out among high school students from the city of Maringa in the state of Parana (PR), Brazil (2007). The sample included 991 students (54.5% girls) from high schools. DIPs were investigated by the frequency of weekly consumption of each food group: vegetables, fruit, rice, beans, fried food, sweet food, milk, soda, meat, eggs, alcoholic drinks. Independent variables were: demographic and socioeconomic characteristics and lifestyle variables. DIPS were identified using principal component analysis with orthogonal rotation (varimax). Three components were extracted. Component 1 (fried foods, sweets and soft drinks) was positively associated with not having breakfast for girls and dinner for boys. Moreover, component 2 (consumption of fruit and vegetables) was positively associated with having breakfast at home for boys and number of meals for girls. Component 3 (beans, eggs and meat) was positively associated with having lunch, employment and sedentary behavior level for girls. However, it was negatively associated with having lunch and dinner for boys. Adolescents who have healthier eating patterns also had other healthier behaviors regardless of gender. However, factors associated with dietary patterns differ between boys and girls. (C) 2012 Elsevier Ltd. All rights reserved.
Resumo:
The purpose of this study was to evaluate the antioxidant activity of honey from different entomological sources which were harvested in the dry season of 2008-2009 from distinct mesoregions of the State of Alagoas in the North East of Brazil. Honey produced by five different species of bees, even from the same region and season, showed a statistically significant difference (p <0.05) in the content of phenols, flavonoids and antioxidants, with higher levels of these compounds found in honey produced by Plebeia spp. and A. mellifera. Honey from stingless bees was quite different from that of A. mellifera, especially from the Plebeia spp. A dendrogram of the five species of bees showed the formation of 3 groups, one being formed by Apis mellifera, one by the genus Melipona (M. subnitida, M. quadrifasciata and M. scutellaris) and another formed by Plebeia spp.
Resumo:
OBJECTIVE: To identify clusters of the major occurrences of leprosy and their associated socioeconomic and demographic factors. METHODS: Cases of leprosy that occurred between 1998 and 2007 in Sao Jose do Rio Preto (southeastern Brazil) were geocodified and the incidence rates were calculated by census tract. A socioeconomic classification score was obtained using principal component analysis of socioeconomic variables. Thematic maps to visualize the spatial distribution of the incidence of leprosy with respect to socioeconomic levels and demographic density were constructed using geostatistics. RESULTS: While the incidence rate for the entire city was 10.4 cases per 100,000 inhabitants annually between 1998 and 2007, the incidence rates of individual census tracts were heterogeneous, with values that ranged from 0 to 26.9 cases per 100,000 inhabitants per year. Areas with a high leprosy incidence were associated with lower socioeconomic levels. There were identified clusters of leprosy cases, however there was no association between disease incidence and demographic density. There was a disparity between the places where the majority of ill people lived and the location of healthcare services. CONCLUSIONS: The spatial analysis techniques utilized identified the poorer neighborhoods of the city as the areas with the highest risk for the disease. These data show that health departments must prioritize politico-administrative policies to minimize the effects of social inequality and improve the standards of living, hygiene, and education of the population in order to reduce the incidence of leprosy.
Resumo:
Abstract Background Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis Results The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making. Conclusions PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.