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 4,687 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Single trial event-related cerebral potentials (ERPs) in response to skin stimuli of various intensities and qualities in man were investigated in respect to their nociceptive information content. Electrical constant current stimuli (20 msec, 2 - 8 mA) and mechanical force controlled stimuli (20 msec, 0.8 - 3.2 N) were applied to the tip of the left middle finger. Four intensities of each stimulus quality were given, each intensity appearing 40 times in standardized randomized order. EEG segments (between 5 sec before and 500 msec after stimulus onset) were subjected to computer analysis. ERP wave form was shown to depend upon the amount of alpha waves in the prestimulus EEG. For analysis, only subjects with low power in the alpha band were selected. Principal component analysis was applied to all single trial ERPs measured using the variance-covariance matrix of association. Six principal components (PCs) were extracted accounting for about 90% of total variance. Five of the extracted PCs had well located loading maxima: PC1 (50 - 80 msec), PC4 (140 - 160 msec), PC3 (200 - 250 msec), PC4 (280 - 360 msec), PC5 (400 - 500 msec); PC6 appeared polyphasic. Analysis of variance of the mean PC scores revealed that one PC (PC1) discriminated between quality, and 4 PCs (PC1 - PC4) between quantity of stimulation. Eliminating effects of stimulus intensity resulted in two PCs (PC2, PC4) which distinguished exclusively between non-pain and pain. PCA applied to disjunctive subsets of ERPs, corresponding to the different experimental conditions, yielded practically identical sets of PCs, such that no specific ERP component emerged when pain was reported.
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PMID:Principal component analysis of pain-related cerebral potentials to mechanical and electrical stimulation in man. 617 4

Alternative methods like predictions based on Quantitative Structure-Activity Relationships (QSARs) are now accepted to fill data gaps and define priority lists for more expensive and time consuming assessments. A heterogeneous data set of 74 esters was studied for their aquatic toxicity, and available experimental toxicity data on algae, Daphnia and fish were used to develop statistically validated QSAR models, obtained using multiple linear regression (MLR) by the OLS (Ordinary Least Squares) method and GA-VSS (Variable Subset Selection by Genetic Algorithms) to predict missing values. An ESter Aquatic Toxicity INdex (ESATIN) was then obtained by combining, by PCA, experimental and predicted toxicity data, from which model outliers and esters highly influential due to their structure had been eliminated. Finally this integrated aquatic toxicity index, defined by the PC1 score, was modelled using only a few theoretical molecular descriptors. This last QSAR model, statistically validated for its predictive power, could be proposed as a preliminary evaluative method for screening/prioritising esters according to their integrated aquatic toxicity, just starting from their molecular structure.
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PMID:Ranking of aquatic toxicity of esters modelled by QSAR. 1562 Jul 49

Principal component analysis was applied to XRD data from a series of Mg(OH)2 samples prepared under different hydrothermal conditions from bischofite (MgCl2.6H2O) and carnallite (KCl.MgCl2.6H2O), owing to differences in full width at half-maximum (fwhm) as well as in the intensity ratio I001/I101 of the respective diffraction peaks. According to the PCA results, the four principal components are able to explain 93% of the total variance and the samples can be classified into four main groups. For instance, the principal component PC1 can be interpreted as the crystallite size along the 101 direction since it is related to the fwhm of this peak. On the other hand, PC3 is related to orientation effects along 001 and 101 directions as it is dominated by the relative intensities of the two peaks. Finally, a comparison of the scanning electron microscopy images of the samples classified in each group revealed that in most of the cases a distinct morphology predominates within each group, which can be explained on the basis of the brucite growth mechanism.
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PMID:Principal component analysis of X-ray diffraction patterns to yield morphological classification of brucite particles. 1732 3

The anthropometric somatotype is a quantitative description of body shape and composition. Familial studies indicate the existence of a familial resemblance for this phenotype and they suggest a substantial action by genetic factors on this aggregation. The aim of this study is to examine the degree of familial resemblance of the somatotype components and of a factor of shape, in a sample of Biscay nuclear families (Basque Country, Spain). One thousand three hundred and thirty nuclear families were analysed. The anthropometric somatotype components [Carter, J.E.L., Heath, B.H., 1990. Somatotyping. Development and applications. Cambridge University Press, Cambridge, p. 503] were computed. Each component was fitted for the other two through a stepwise multiple regression, and also fitted through the LMS method [Cole, T., 1988. Fitting smoothed centile curves to reference data. J. Roy. Stat. Soc. 151, 385-418] in order to eliminate the age, sex and generation effects. The three raw components were introduced in a PCA from which a shape factor (PC1) was extracted for each generation. The correlations analysis was performed with the SEGPATH package [Province, M.A., Rao, D.C., 1995. General purpose model and computer programme for combined segregation and path analysis (SEGPATH): automatically creating computer from symbolic language model specifications. Genet. Epidemiol. 12, 203-219]. A general model of transmission and nine reduced models were tested. Maximal heritability was estimated with the formula of [Rice, T., Warwick, D.E., Gagnon, J., Bouchard, C., Leon, A.S., Skinner, J.S., Wilmore, J.H., Rao, D.C., 1997. Familial resemblance for body composition measures: the HERITAGE family study. Obes. Res. 5, 557-562]. The correlations were higher between offspring than in parents and offspring and a significant resemblance between mating partners existed. Maximum heritabilities were 55%, 52% and 46% for endomorphy, mesomorphy and ectomorphy, respectively, and 52% for PC1. In conclusion, the somatotype presents a moderate degree of familial aggregation. For the somatotype components, as well as for PC1, the degree of familial resemblance depends on age. The sex only has a significant effect on ectomorphy.
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PMID:Heritability of the somatotype components in Biscay families. 1757 Mar 68

Sludge resulting from the treatment of effluent from a vegetable oil mill, was composted mixed with domestic waste in a pile for five months. Different proportions of sludge and dry waste were mixed: M1 (1v/2v) and M2 (1v/1v). Monitoring different physical-chemical parameters showed the effect of the substrate on the microbiological activity and on the formation of fulvic acids, affecting the maturity of the final compost. Elemental analysis revealed that the fulvic acids of mixes M1 and M2 presented very low concentrations of carbon, hydrogen, and oxygen and a high level of nitrogen. The FTIR spectroscopy results showed a decrease during composting of the intensity of absorbance of the easily assimilable compounds that are predominant in the initial mixtures i.e. the carbohydrates (1170-1080 cm(-1)) in M1 and long aliphatic chains (2920 cm(-1)) in M2. For mix M1 there was enrichment in compounds bearing oxygen-containing moieties. In M2 it was the nitrogen-containing compounds (in the form of stable amides) which predominated at the end of composting. The first component of PCA analysis, PC1, accounted for 83% of the difference between two distinct groups of parameters governing degradation and restructuration of the fulvic acids during composting. PC2 (17%) explained the variance due to the level of free or less polycondensed compounds in the two mixtures. Oxidised polyphenolic and polysaccharide structures were the least free, or most polycondensed, in the fulvic structures of M1. In M2 fulvic acids however, it was the polyphenols and peptide structures that were involved in the bonding, most likely of the polyphenol-peptide type.
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PMID:The fulvic acid fraction as it changes in the mature phase of vegetable oil-mill sludge and domestic waste composting. 1823 Apr 15

Fingerprinting analysis of fresh ginseng according to root age was performed using 1H-NMR spectroscopy and multivariate analysis techniques. Various peaks were detected in the aliphatic (0-3 ppm), sugar (3-6 ppm), and aromatic (6-9 ppm) regions of the 1H-NMR spectra of the water extracts of fresh ginseng root. The use of principal components (PCs) analysis (PCA) for metabolomic profiling allowed the large 1H-NMR data set obtained for various metabolites to be reduced to PC1, PC2, and PC3. Two dimensional score plots showed clear separations with these three components at different roots ages, and explained 89.6% of the total variance. Canonical discriminant analysis identified the ginseng roots at various ages from the NMR results with over 89.9% discrimination accuracy. These results indicate that the combination of 1H-NMR and PCA provides a very promising tool for the authentication and quality control of fresh ginseng roots at different ages.
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PMID:Fingerprinting analysis of fresh ginseng roots of different ages using 1H-NMR spectroscopy and principal components analysis. 1825 51

The aim of the present study was to examine the heritability of 11 traits in a mixed-longitudinal sample of Indian siblings, and to determine whether heritability estimates vary during the growth period and whether they are influenced by sex. The sample consisted of 245 brothers and 213 sisters from 138 nuclear families living in a semi-urban area in Kolkata, India. The age ranged between 5 and 19 years. The traits were standardised for age and sex using standard deviation scores (SDS) produced by the LMS method (Cole, T.J., 1988. Fitting smoothed centile curves to reference data. J. R. Stat. Soc. A 151, 385-418). The standard deviation scores were analysed by PCA. The two factors with eigenvalues above 1 explained 77.3% of the variance; they showed a high level of pleiotropism present among the studied traits and represented body lengths (PC1) and body weight and breadths (PC2). The heritability between all types of siblings (irrespective of sex) for the PC1 and PC2 was estimated. The heritability between various pairs of siblings showed variations along the whole ontogenetic period studied. During the childhood and pre-pubertal period, heritability between brothers, brother-sister pairs and any sibling pairs was mostly constant, with small and non-significant variations. All the pairs showed the lowest degree of heritability during puberty for PC1 but not for PC2, with significant changes of heritability estimates between adolescence and adulthood, in most of the analysed sibling pairs and in both PC factors. The highest heritability was generally observed at the end of the examined growth period in all pairs. A significant effect of sex on heritability was only detected for PC2 at 11 years of age.
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PMID:Multifactorial analysis of a mixed-longitudinal sample of Indian siblings: Age and sex effects on heritability. 1955 1

Concomitant with the rapid global urbanization process, land use change detection has been the focus and "hot spot" of global change research all the time. In the present study, the rigorous orthorectification was first applied to the SPOT-5 data to guarantee precise geometric correction and image registration. Afterwards, a methodology integrating PCA-enhancement and multi-source classifier was adopted to detect the land use changes in urban area. The results show that the first three PCs derived from multi-temporal-PCA contain most of the spectral information among which unchanged land use is highlighted in PC1 and PC2, and changed land use is mainly enhanced in PC3. The following multi-source classifier integrating unsupervised classifier (ISODATA) and supervised classifier (Maximum Likelihood) accurately extracts all the information. The findings from accuracy assessment demonstrate that the overall accuracy for the proposed method reaches 92.58, KAPPA coefficient is 0.92, and proving figures are also produced for the user's and producer's accuracies. It was further found that the proposed method yielded better accuracy than that of traditional post-classification comparison approach.
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PMID:[Detecting land use change using PCA-enhancement and multi-source classifier from SPOT images]. 1981 May 46

Successive projections algorithm (SPA) was employed to select the optimal combination of principal components (PCs) which were obtained by principal component analysis. Short-wave near infrared spectra of milk powder was firstly analyzed by PCA, and the optimal combination of obtained first eight PCs was determined by SPA. The optimal PC combination of fat content prediction was PC1 , PC2, PC 4, PC5, PC6 and PC7, and the combination for protein content prediction was PC1, PC2, PC3, PC4, PC5 and PC8. Least-squares support vector machine models inputted by different PC combination were established to predict fat and protein content, respectively. Both the fat and protein content prediction results of the PC combination selected by SPA were better than those of first four PCs to first eight PCs. Rp2, and root mean square errors for prediction and residual predictive deviation of prediction results of the PC combination selected by SPA were 0.989, 0.1703 and 9.5343, respectively for fat, and 0.9876, 0.1348 and 8.9274 for protein. The overall results demonstrate that SPA can fast and effectively select the optimal PC combination. The selecting process is simple and does not need abundant parameter debugging.
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PMID:[Study on combinatorial optimization of spectral principal components using successive projections algorithm]. 2003 49

Body size is an important determinant of the diving and foraging ability in air-breathing marine vertebrate predators. Satellite-linked dive recorders were used during 2003-2004 to investigate the foraging behavior of 22 male California sea lions (Zalophus californianus, a large, sexually dimorphic otariid) and to evaluate the extent to which body size explained variation among individuals and foraging strategies. Multivariate analyses were used to reduce the number of behavioral variables used to characterize foraging strategies (principal component analysis, PCA), to identify individually based foraging strategies in multidimensional space (hierarchical cluster analysis), and to classify each individual into a cluster or foraging strategy (discriminant analysis). Approximately 81.1% of the variation in diving behavior among individuals was explained by three factors: diving patterns (PC1), foraging effort (PC2), and behavior at the surface (PC3). Individuals were classified into three distinct groups based on their diving behavior (shallow, mixed depth, and deeper divers), and jackknife resampling of the data resulted in correct group assignment 86% of the time. Body size as an independent variable was positively related to dive duration and time spent ashore and negatively related to time at sea, and it was a key parameter in PC2 used to classify the three distinct clusters. Differences among individual-based foraging strategies probably were driven by differences in body size, which enabled larger animals to dive deeper and forage more efficiently by targeting different and perhaps larger prey items. The occurrence of foraging specializations within a species and age class has implications for quantitative modeling of population-level predator-prey interactions and ecosystem structure.
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PMID:The role of body size in individual-based foraging strategies of a top marine predator. 2046 15


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