905 resultados para PCA and HCA
Resumo:
A new genus of Cobitinae, Bibarba gen. n., and a new species, B. bibarba sp. n., were discovered and are described for the Chengjiang River, a tributary of the Hongshuihe River in Guangxi Province of southern China. This river region is characterized by a Karst landscape, and the river that is inhabited by the new genus is a slowly moving stream with arenaceous and cobblestone beds. The new genus resembles Cobitis Linnaeus, 1758 (subfamily Cobitinae) in the shape and pigmentation pattern of their body, the absence of scales on their head, and the presence of a suborbital spine, but differs from it by a single Lamina circularis on the third pectoral fin ray instead of on the base of the second pectoral fin ray; two pairs of barbels (one rostral pair and one maxillo-mandibular pair) instead of three pairs of barbels (one rostral pair, one maxillary pair, and one maxillo-mandibular pair); a relatively thick and short suborbital spine with a strong medio-lateral process instead of a suborbital spine without or with a weakly formed medio-lateral process as in Cobitis; and the lack of a black stripe extending from the occiput through the eye to the insertion of the rostral barbel. The first two characters have not been reported in any other genus of the subfamily Cobitinae. A morphometric character analysis based on PCA reveals differences between B. bibarba and C. sinensis in body size, barbel length, interorbital width, pectoral fin length in males, and the position of the dorsal and ventral fins. Type specimens of the new species are kept in the Freshwater Fishes Museum of the Institute of Hydrobiology at the Chinese Academy of Sciences in Wuhan, Hubei Province. (c) 2007 Elsevier GmbH. All rights reserved.
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The purpose of the research is to study the seasonal succession of protozoa community and the effect of water quality on the protozoa community to characterize biochemical processes occurring at a eutrophic Lake Donghu, a large shallow lake in Wuhan City, China. Samples of protozoa communities were obtained monthly at three stations by PFU (polyurethane foam unit) method over a year. Synchronously, water samples also were taken from the stations for the water chemical quality analysis. Six major variables were examined in a principal component analysis (PCA), which indicate the fast changes of water quality in this station I and less within-year variation and a comparatively stable water quality in stations II and III. The community data were analyzed using multivariate techniques, and we show that clusters are rather mixed and poorly separated, suggesting that the community structure is changing gradually, giving a slight merging of clusters form the summer to the autumn and the autumn to the winter. Canonical correspondence analysis (CCA) was used to infer the relationship between water quality variables and phytoplankton community structure, which changed substantially over the survey period. From the analysis of cluster and CCA, coupled by community pollution value (CPV), it is concluded that the key factors driving the change in protozoa community composition in Lake Donghu was water qualities rather than seasons. (c) 2006 Elsevier Ltd. All rights reserved.
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The sediment of Ya-Er Lake had been heavily polluted by polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) from the former chloralkali industry. The total amounts of PCDD/Fs and I-TEQ decreased along the water flow direction and also decreased from top to bottom layers of sediment cores. Sediment of Pond 1 was dominated by PCDF, especially TCDF. In contrast, in the other four ponds, PCDD dominated in all layers and octachlorinated dibenzo-p-dioxin (OCDD) predominated in all of the homologues. When homologue profiles from sediments and water samples were compared using principal component analysis (PCA), the first two principal components represented 95.2% of the variance in the data. The first component explained 75.9% of the variance and the second one 19.3%. Two clusters were most distinct, presenting a shift in PCDD/Fs composition from PCDF to heptachlorinated dibenzo-p-dioxin (HpCDD) and OCDD in sediments and water from Pond I to Ponds 2-5. The pattern variation between Pond 1 and Ponds 2-5 in Ya-Er Lake was most likely due to the change of process in the chemical plant after the dams between the ponds were built. The results of the present study also showed that log K-oc of PCDD/Fs calculated from data of sediment and water in the field were comparable with theoretical log K-oc. The results also implied that the concentrations of PCDD/Fs in water and sediments could be predicted from each other by log K-oc. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
Pattern recognition methods were applied to the analysis of 600 MHz H-1 NMR spectra of urine from rats dosed with compounds that induced organ-specific damage in the liver and kidney. Male Wistar rats were separated into groups (n=4) and each was treated with one of following compounds: HgCl2, CCl4, Lu(NO3)(3) and Changle (a kind of rare earth complex mixed with La, Ce, Pr and Nd). Urine samples from the rats dosed with HgCl2, CCl4 and Lu(NO3)(3) were collected over a 24 h time course and the samples from the rats administrated with Changle were gained after 3 months. These samples were measured by 600 MHz NMR spectroscopy. Each spectrum was data-processed to provide 223 intensity-related descriptors of spectra. Urine spectral data corresponding to the time intervals, 0-8 h (HgCl2 and CCl4), 4-8 (Lu(NO3)(3)) h and 90 d (Changle) were analyzed using principal component analysis (PCA). Successful classification of the toxicity and biochemical effects of Lu(NO3)(3) was achieved.
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Sixteen polycyclic aromatic hydrocarbons (PAHs) and 28 polychlorinated biphenyls (PCBs) were measured at a 2-cm interval in a core sample from the middle of the southern Yellow Sea for elucidating their historical variations in inflow and sources. The chronology was obtained using the Pb-210 method. PAHs concentrations decreased generally with depth and two climax values occurred in 14-16 cm and 20-22 cm layers, demonstrating that the production and usage of PAHs might reach peaks in the periods of 1956-1962 and 1938-1944. The booming economy and the navy battles of the Second World War might explain why the higher levels were detected in the two layers. The result of principal component analysis (PCA) revealed that PAHs were primarily owing to the combustion product. Down-cored variation of PCB concentrations was complex. Higher concentrations besides the two peaks being the same as PAHs were detected from 4 to 8 cm, depositing from 1980 to 1992, which probably resulted from the disposal of the out-dated PCB-containing equipment. The average Cl percentage of PCBs detected was similar to that of the mixture of Aroclor 1254 and 1242, suggesting they might origin from the dielectrical and heat-transfer fluid. The total organic carbon (TOC) content played a prevalent role in the adsorption of high molecular weight PAHs (>= 4-ring), while no obvious relationship among total PCBs, the concentration of congeners, and TOC was found.
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Apostichopus japonicus is a common sea cucumber that undergoes seasonal inactivity phases and ceases feeding during the summer months. We used this sea cucumber species as a model in which to examine phenotypic plasticity of the digestive tract in response to food deprivation. We measured the body mass, gross gut morphology and digestive enzyme activities of A. japonicus before, during, and after the period of inactivity to examine the effects of food deprivation on the gut structure and function of this animal. Individuals were sampled semi-monthly from June to November (10 sampling intervals over 178 days) across temperature changes of more than 18 degrees C. On 5 September, which represented the peak of inactivity and lack of feeding, A. japonicus decreased its body mass, gut mass and gut length by 50%, 85%, and 70%, respectively, in comparison to values for these parameters preceding the inactive period. The activities of amylase, cellulase and lipase decreased by 77%, 98%, and 35% respectively, in comparison to mean values for these enzymes in June, whereas pepsin activity increased two-fold (luring the inactive phase. Alginase and trypsin activities were variable and did not change significantly across the 178-day experiment. With the exception of amylase and cellulase, all body size indices and digestive enzyme activities recovered and even surpassed the mean values preceding the inactive phase during the latter part of the experiment (October-November). Principal Component Analysis (PCA) utilizing the digestive enzyme activity and body size index data divided the physiological state of this cucumber into four phases: an active stage, prophase of inactivity peak inactivity, and a reversion phase. These phases are all consistent with previously suggested life stages for this species, but our data provide more defined characteristics of each phase. A. japonicus clearly exhibits phenotypic plasticity (or life-cycle staging) of the digestive tract during its annual inactive period. (C) 2008 Elsevier Inc. All rights reserved.
Resumo:
Janet Taylor, Ross D King, Thomas Altmann and Oliver Fiehn (2002). Application of metabolomics to plant genotype discrimination using statistics and machine learning. 1st European Conference on Computational Biology (ECCB). (published as a journal supplement in Bioinformatics 18: S241-S248).
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Q. Shen and R. Jensen, 'Selecting Informative Features with Fuzzy-Rough Sets and its Application for Complex Systems Monitoring,' Pattern Recognition, vol. 37, no. 7, pp. 1351-1363, 2004.
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Kohl, U. (2004). Who has the right to govern online activity? A criminal and civil point of view. International Review of Law, Computers & Technology 18 (3), 387-410 RAE2008
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Elliott, G. N., Worgan, H., Broadhurst, D. I., Draper, J. H., Scullion, J. (2007). Soil differentiation using fingerprint Fourier transform infrared spectroscopy, chemometrics and genetic algorithm-based feature selection. Soil Biology & Biochemistry, 39 (11), 2888-2896. Sponsorship: BBSRC / NERC RAE2008
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Software metrics are the key tool in software quality management. In this paper, we propose to use support vector machines for regression applied to software metrics to predict software quality. In experiments we compare this method with other regression techniques such as Multivariate Linear Regression, Conjunctive Rule and Locally Weighted Regression. Results on benchmark dataset MIS, using mean absolute error, and correlation coefficient as regression performance measures, indicate that support vector machines regression is a promising technique for software quality prediction. In addition, our investigation of PCA based metrics extraction shows that using the first few Principal Components (PC) we can still get relatively good performance.
Resumo:
11 Å tobermorite, Ca5Si6O16(OH)2 · 4H2O, is a layer lattice ion exchange mineral whose potential as a carrier for Ag+ and Zn2+ ions in antimicrobial, bioactive formulations has not yet been explored. In view of this, the in vitro bioactivity of Ag+- and Zn2+-exchanged 11 Å tobermorites and their bactericidal action against S. aureus and P.aeruginosa are reported. The in vitro bioactivity of the synthetic unsubstituted tobermorite phase was confirmed by the formation of bone-like hydroxycarbonate apatite (HCA) on its surface within 48 h of contact with simulated body fluid. The substitution of labile Ag+ ions into the tobermorite lattice delayed the onset of HCA-formation to 72 h; whereas, the Zn2+-substituted phase failed to elicit an HCA-layer within 14 days. Both Ag+- and Zn2+-exchanged tobermorite phases were found to exhibit marked antimicrobial action against S. aureus and P.aeruginosa, two common pathogens in biomaterial-centred infections.
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Plankton collected by the Continuous Plankton Recorder (CPR) survey were investigated for the English Channel, Celtic Sea and Bay of Biscay from 1979 to 1995. The main goal was to study the relationship between climate and plankton and to understand the factors influencing it. In order to take into account the spatial and temporal structure of biological data, a three-mode principal component analysis (PCA) was developed. It not only identified 5 zones characterised by their similar biological composition and by the seasonal and inter-annual evolution of the plankton, it also made species associations based on their location and year-to-year change. The studied species have stronger year-to-year fluctuations in abundance over the English Channel and Celtic Sea than the species offshore in the Bay of Biscay. The changes in abundance of plankton in the English Channel are negatively related to inter-annual changes of climatic conditions from December to March (North Atlantic Oscillation [NAO] index and air temperature). Thus, the negative relationship shown by Fromentin and Planque (1996; Mar Ecol Prog Ser 134:111-118) between year-to-year changes of Calanus finmarchicus abundance in the northern North Atlantic and North Sea and NAO was also found for the most abundant copepods in the Channel. However, the hypothesis proposed to explain the plankton/NAO relationship is different for this region and a new hypothesis is proposed. In the Celtic Sea, a relationship between the planktonic assemblage and the air temperature was detected, but it is weaker than for the English Channel. No relationship was found for the Bay of Biscay. Thus, the local physical environment and the biological composition of these zones appear to modify the relationship between winter climatic conditions and the year-to-year fluctuations of the studied planktonic species. This shows, therefore, that the relationship between climate and plankton is difficult to generalise.
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In this study, Evernia prunastri, a lichen growing in its natural habitat in Morocco was analysed for the concentration of five heavy metals (Fe, Pb, Zn, Cu and Cr) from eleven sites between Kenitra and Mohammedia cities. The control site was Dar Essalam, an isolated area with low traffic density and dense vegetation. In the investigated areas, the concentration of heavy metals was correlated with vehicular traffic, industrial activity and urbanization. The total metal concentration was highest in Sidi Yahya, followed by Mohammedia and Bouznika. The coefficient of variation was higher for Pb and lower for Cu, Zn and Fe. The concentrations of most heavy metals in the thalli differed significantly between sites (p<0.01). Principal component analysis (PCA) revealed a significant correlation between heavy metal accumulation and atmospheric purity index. This study demonstrated also that the factors most strongly affecting the lichen flora were traffic density, the petroleum industry and paper factories in these areas. Overall, these results suggest that the index of atmospheric purity and assessment of heavy metals in lichen thalli are good indicators of the air quality at the studied sites.
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Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.