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Component Analysis (component + analysis)
Kinds of Component Analysis Selected AbstractsINTERPRETATION OF THE RESULTS OF COMMON PRINCIPAL COMPONENTS ANALYSESEVOLUTION, Issue 3 2002David Houle Abstract Common principal components (CPC) analysis is a new tool for the comparison of phenotypic and genetic variance-covariance matrices. CPC was developed as a method of data summarization, but frequently biologists would like to use the method to detect analogous patterns of trait correlation in multiple populations or species. To investigate the properties of CPC, we simulated data that reflect a set of causal factors. The CPC method performs as expected from a statistical point of view, but often gives results that are contrary to biological intuition. In general, CPC tends to underestimate the degree of structure that matrices share. Differences of trait variances and covariances due to a difference in a single causal factor in two otherwise identically structured datasets often cause CPC to declare the two datasets unrelated. Conversely, CPC could identify datasets as having the same structure when causal factors are different. Reordering of vectors before analysis can aid in the detection of patterns. We urge caution in the biological interpretation of CPC analysis results. [source] A revision of Calvoa Hook. f. (Melastomataceae)BOTANICAL JOURNAL OF THE LINNEAN SOCIETY, Issue 2 2001ESTRELA FIGUEIREDO FLS A revision of the genus Calvoa Hook. f. (Melastomataceae) is presented. Principal Component Analyses (PCA) and Cluster Analyses (UPGMA) were performed to elucidate three cases of difficult species delimitation and infraspecific variation, with the following results. (1) The separation between C. crassinoda Hook. f. and C. grandifolia Cogn. was clear in the results obtained with both methods. (2) The group of the West-Central African species Calvoa angolensis A. Fern. & R. Fern., C. calliantha Jacq.-Fél., C. monticola A. Chev., C. pulcherrima Gilg ex Engl., C. sapinii De Wild., C. seretii De Wild., C. sinuata Hook. f. and C. subquinquenervia De Wild, proved difficult to resolve with either analysis, but the Cluster Analysis produced results which are more consistent with the identification of the specimens. (3) Neither of the two analyses supported the recognition of infraspecific categories in Calvoa orientalis Taub. Eighteen species are recognized in the genus. The new species Calvoa Jacques-felixii E. Figueiredo is described and the new combination Calvoa seretii subsp. wildemaniana (Exell) E. Figueiredo is made. Four lectotypes are designated. The conservation status of some taxa is discussed. Six species are considered rare and possibly under threat. [source] A Behavioral Component Analysis of Route Guidance Systems Using Neural NetworksCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 6 2003Khaled Hamad This article focuses on the behavioral component, one of the three components (the other two being dynamic traffic component and information supply strategy component) of a practical RGS developed through a 4-year project at the University of Delaware. Development of the behavioral model is based on the premise that different drivers perceive and behave differently in response to the information provided. Understanding the behavior of RGS-equipped drivers' acceptance or nonacceptance of provided information is essential for understanding the reliability of the system. Backpropagation neural network with its ability to map complex input,output relationships has been used to structure the model. This model was tested on two networks under both recurring and nonrecurring congestion. A comparative analysis of the measures of effectiveness revealed that the performance of the developed RGS is significantly better than the performance under existing non-RGS conditions. [source] Detecting the impact of oceano-climatic changes on marine ecosystems using a multivariate index: The case of the Bay of Biscay (North Atlantic-European Ocean)GLOBAL CHANGE BIOLOGY, Issue 1 2008GEORGES HEMERY Abstract Large-scale univariate climate indices (such as NAO) are thought to outperform local weather variables in the explanation of trends in animal numbers but are not always suitable to describe regional scale patterns. We advocate the use of a Multivariate Oceanic and Climatic index (MOCI), derived from ,synthetic' and independent variables from a linear combination of the total initial variables objectively obtained from Principal Component Analysis. We test the efficacy of the index using long-term data from marine animal populations. The study area is the southern half of the Bay of Biscay (43°,47°N; western Europe). Between 1974 and 2000 we monitored cetaceans and seabirds along 131000 standardized line transects from ships. Fish abundance was derived from commercial fishery landings. We used 44 initial variables describing the oceanic and atmospheric conditions and characterizing the four annual seasons in the Bay of Biscay. The first principal component of our MOCI is called the South Biscay Climate (SBC) index. The winter NAO index was correlated to this SBC index. Inter-annual fluctuations for most seabird, cetacean and fish populations were significant. Boreal species (e.g. gadiformes fish species, European storm petrel and Razorbill ,) with affinities to cold temperate waters declined significantly over time while two (Puffin and Killer Whale) totally disappeared from the area during the study period. Meridional species with affinities to hotter waters increased in population size. Those medium-term demographic trends may reveal a regime shift for this part of the Atlantic Ocean. Most of the specific observed trends were highly correlated to the SBC index and not to the NAO. Between 40% and 60% of temporal variations in species abundance were explained by the multivariate SBC index suggesting that the whole marine ecosystem is strongly affected by a limited number of physical parameters revealed by the multivariate SBC index. Aside the statistical error of the field measurements, the remaining variation unexplained by the physical characteristics of the environment correspond to the impact of anthropogenic activities such overfishing and oil-spills. [source] Functional source separation applied to induced visual gamma activityHUMAN BRAIN MAPPING, Issue 2 2008Giulia Barbati Abstract Objective of this work was to explore the performance of a recently introduced source extraction method, FSS (Functional Source Separation), in recovering induced oscillatory change responses from extra-cephalic magnetoencephalographic (MEG) signals. Unlike algorithms used to solve the inverse problem, FSS does not make any assumption about the underlying biophysical source model; instead, it makes use of task-related features (functional constraints) to estimate source/s of interest. FSS was compared with blind source separation (BSS) approaches such as Principal and Independent Component Analysis, PCA and ICA, which are not subject to any explicit forward solution or functional constraint, but require source uncorrelatedness (PCA), or independence (ICA). A visual MEG experiment with signals recorded from six subjects viewing a set of static horizontal black/white square-wave grating patterns at different spatial frequencies was analyzed. The beamforming technique Synthetic Aperture Magnetometry (SAM) was applied to localize task-related sources; obtained spatial filters were used to automatically select BSS and FSS components in the spatial area of interest. Source spectral properties were investigated by using Morlet-wavelet time-frequency representations and significant task-induced changes were evaluated by means of a resampling technique; the resulting spectral behaviours in the gamma frequency band of interest (20,70 Hz), as well as the spatial frequency-dependent gamma reactivity, were quantified and compared among methods. Among the tested approaches, only FSS was able to estimate the expected sustained gamma activity enhancement in primary visual cortex, throughout the whole duration of the stimulus presentation for all subjects, and to obtain sources comparable to invasively recorded data. Hum Brain Mapp 29:131,141, 2008. © 2007 Wiley-Liss, Inc. [source] Dimensionality estimate of the manifold in chemical composition space for a turbulent premixed H2 + air flame,INTERNATIONAL JOURNAL OF CHEMICAL KINETICS, Issue 6 2004Shaheen R. Tonse The dimensionality () of manifolds of active chemical composition space has been measured using three different approaches: the Hausdorff geometrical binning method, Principal Component Analysis, and the Grassberger-Procaccia cumulative distribution method. A series of artificial manifolds is also generated using a Monte Carlo approach to discern the advantages and limitations of the three methods. Dimensionality is quantified for different levels of turbulent intensity in a simulation of the interactions of a 2D premixed hydrogen flame with a localized region of turbulence superimposed over the cold region upstream of the flame front. The simulations are conducted using an adaptive mesh refinement code for low Mach number reacting flows. By treating the Ns species and temperature of the local thermo-chemical state as a point in multidimensional chemical composition space, a snapshot of a flame region is mapped into chemical composition space to generate the manifold associated with the 2-D flame system. An increase in was observed with increasing turbulent intensity for all three methods. Although each method provides useful information, the Grassberger-Procaccia method is subject to fewer artifacts than the other two thereby providing the most reliable quantification of . © 2004 Wiley Periodicals, Inc. Int J Chem Kinet 36: 326,336, 2004 [source] Ascertaining late-life depressive symptoms in Europe: an evaluation of the survey version of the EURO-D scale in 10 nations.INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, Issue 1 2008The SHARE project Abstract The reported prevalence of late-life depressive symptoms varies widely between studies, a finding that might be attributed to cultural as well as methodological factors. The EURO-D scale was developed to allow valid comparison of prevalence and risk associations between European countries. This study used Confirmatory Factor Analysis (CFA) and Rasch models to assess whether the goal of measurement invariance had been achieved; using EURO-D scale data collected in 10 European countries as part of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 22,777). The results suggested a two-factor solution (Affective Suffering and Motivation) after Principal Component Analysis (PCA) in 9 of the 10 countries. With CFA, in all countries, the two-factor solution had better overall goodness-of-fit than the one-factor solution. However, only the Affective Suffering subscale was equivalent across countries, while the Motivation subscale was not. The Rasch model indicated that the EURO-D was a hierarchical scale. While the calibration pattern was similar across countries, between countries agreement in item calibrations was stronger for the items loading on the affective suffering than the motivation factor. In conclusion, there is evidence to support the EURO-D as either a uni-dimensional or bi-dimensional scale measure of depressive symptoms in late-life across European countries. The Affective Suffering sub-component had more robust cross-cultural validity than the Motivation sub-component. Copyright © 2008 John Wiley & Sons, Ltd. [source] Trophic diversity of the otter (Lutra lutra L.) in temperate and Mediterranean freshwater habitatsJOURNAL OF BIOGEOGRAPHY, Issue 5 2003Miguel Clavero Abstract Aim To analyse the geographical patterns in the composition and diversity of otter's (Lutra lutra L.) diet and their relationship with climatic characteristics. Location European freshwater habitats under Mediterranean and temperate climatic regimes. Methods Thirty-seven otter diet studies were reviewed, twenty-one from temperate and sixteen from Mediterranean areas. All studies were based on spraint analysis and their results expressed as relative frequency of occurrence of seven main prey categories. Principal Component Analysis was performed to extract the main gradients of diet composition. Pearson's correlation and t -tests were used to assess the relationship between diet characteristics (composition, diversity and taxonomic richness) and geographical and climatic variables. Results A clear latitudinal gradient in diet composition was observed. Otter diet was more diverse and featured more prey classes in southern localities, while the species was more piscivorous towards the north, where it predated upon a higher number of fish families. This pattern was similar when temperate and Mediterranean localities of Europe were compared. Mediterranean otters behaved as more generalist predators than temperate ones, relying less on fish, and more on aquatic invertebrates and reptiles. Main conclusions Geographical differences in otter feeding ecology in Europe seem to be related with the two contrasted climatic conditions affecting prey populations. The otter can act as a highly specialized piscivorous predator in temperate freshwater ecosystems, which do not suffer a dry season and have a comparatively stable water regime compared to Mediterranean ones. However, the unpredictable prey availability in Mediterranean areas, affected by strong spatial and temporal water shortages, favours a diversification of the otter's diet. [source] When simplicity is not parsimonious: a priori and a posteriori methods in historical biogeographyJOURNAL OF BIOGEOGRAPHY, Issue 1 2001Marco G. P. Van Veller Despite using the same null hypothesis, a priori and a posteriori approaches in historical biogeography differ fundamentally. Methods such as Component Analysis (CA) and Reconciled Tree Analysis (RTA) may eliminate or modify input data in order to maximize fit to the null hypothesis, by invoking assumptions 1 and 2. Methods such as Brooks Parsimony Analysis (BPA) modify the null hypothesis, if necessary, to maintain the integrity of the input data, as required by assumption 0. Two exemplars illustrate critical empirical differences between CA/RTA and BPA: (1) CA rather than BPA may select the incorrect general area cladogram for a set of data (2) BPA, not RTA, provides the most parsimonious interpretation of all available data and (3) secondary BPA, proposed in 1990, applied to data sets for which dispersal producing areas with reticulate histories is most parsimonious, provides biologically realistic interpretations of area cladograms. These observations lead to the conclusion that BPA and CA/RTA are designed to implement different research programmes based on different conceptual frameworks. BPA is designed to assess the biogeographic context of speciation events, whereas CA/RTA are designed to find the best fitting pattern of relationships among areas based on the taxa that inhabit them. Unique distributional elements and reticulate (hybrid) histories of areas are essential for explaining complex histories of speciation. The conceptual framework for BPA, thus, assumes biogeographical complexity, relying on parsimony as an explanatory tool to summarize complex results, whereas CA/RTA assumes biogeographical simplicity, assuming conceptual parsimony a priori. [source] Multi-way models for sensory profiling dataJOURNAL OF CHEMOMETRICS, Issue 1 2008Rasmus Bro Abstract One of the problems in analyzing sensory profiling data is to handle the systematic individual differences in the assessments from different panelists. It is unavoidable that different persons have, at least to a certain degree, different perceptions of the samples as well as a different understanding of the attributes or of the scales used for quantifying the assessments. Hence, any model attempting to describe sensory profiling data needs to deal with individual differences; either implicitly or explicitly. In this paper, a unifying family of models is proposed based on (i) the assumption that latent variables are appropriate for sensory data, and (ii) that individual differences occur. Based on how individual differences occur, various mathematical models can be constructed, all aiming at modeling simultaneously the sample-specific variation and the panelist-specific variation. The model family includes Principal Component Analysis (PCA) and PARAllel FACtor analysis (PARAFAC). The paper can be viewed as extending the latent variable approach commonly based on PCA to multi-way models that specifically take certain panelist-variations into account. The proposed model family is focused on analyzing data from quantitative descriptive analysis with fixed vocabulary, but it also provides a foundation upon which comparisons, extensions and further developments can be made. An example is given which shows that even for well-working data, models handling individual differences can shed important light on differences between the quality of the data from individual panelists. Copyright © 2007 John Wiley & Sons, Ltd. [source] The past, present, and future of chemometrics worldwide: some etymological, linguistic, and bibliometric investigations,JOURNAL OF CHEMOMETRICS, Issue 6-7 2006R. Kiralj Abstract Internet surfing for the word chemometrics in national languages and, in the Science Citation Index (SCI), searching for articles containing chemometr * were performed. The bibliometric, webometric, and country development descriptors from literature were then treated by Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). In total, 82 written and 127 pronunciation forms of chemometrics were found in 48 languages worldwide. The forms ending in ,- y' (chemometry) and ,- ics' (chemometrics) can be grouped into at least three groups (I, J, K). Scientific collaboration, country development, geography, history, and language were shown to be important determinants in creation of form(s) of chemometrics in a particular country or language. PCA and HCA show that tradition in chemometrics, level of country development, and its scientific production are important for the existence of chemometric societies and laboratories worldwide. Today, the world tends toward becoming more homogeneous with respect to chemometric activity, and will reach a corresponding normal distribution in about 70 years from now. Copyright © 2007 John Wiley & Sons, Ltd. [source] Three-way component analysis of interval-valued dataJOURNAL OF CHEMOMETRICS, Issue 5 2004Paolo Giordani Abstract Vertices Principal Component Analysis (V-PCA) and Centers Principal Component Analysis (C-PCA) are variants of Principal Component Analysis (PCA) to deal with two-way interval-valued data. In this case the observation units are represented as hyperrectangles instead of points. Tucker3 and CANDECOMP/PARAFAC are component analysis techniques to analyze the underlying structure of three-way data sets. In the present paper, after recalling the above mentioned methods, we extend the C-PCA and V-PCA methods to deal with three-way interval-valued data by means of Tucker3 and CANDECOMP/PARAFAC and we describe how to represent the observation units in the obtained low-dimensional space. Furthermore, an application of the extended methods,called Three-way Vertices Principal Component Analysis (3V-PCA) and Three-way Centers Principal Component Analysis (3C-PCA),to three-way interval-valued air pollution data is described. Copyright © 2004 John Wiley & Sons, Ltd. [source] An investigation into the composition, complexity and functioning of snake communities in the mangroves of south-eastern NigeriaAFRICAN JOURNAL OF ECOLOGY, Issue 3 2002Luca Luiselli Abstract The structure of the snake community was studied between 1996 and 2000 on a transect in the mangrove ecological zone of southern Nigeria, West Africa. In three major habitats, both taxonomical diversity and frequency of observations in relation to sampling effort were investigated. In general terms, the complexity of the snake community appeared less than in other habitats of the same geographic region (i.e. swamp forest and forest,plantation mosaics). In fact, only eighteen species were recorded, whereas 43 species are known to inhabit neighbouring habitats. A Principal Component Analysis allowed arrangement of the various species into two main groups in relation to the habitats of capture: (1) a group of species of rainforest biota (i.e. Toxicodryas blandingii, Thelotornis kirtlandii, Thrasops flavigularis, Rhamnophis aethiopissa, Gastropyxis smaragdina, Grayia smythii, Pseudohaje goldii, Python sebae), and (2) a group of species that, at least in Niger Delta, are typically linked to altered habitats, including derived savannas, plantations and suburbia (i.e. Psammophis cf. phillipsi, Philothamnus cf. nitidus, Hapsidophrys lineatus, Crotaphopeltis hotamboeia, Boaedon lineatus, Naja nigricollis, Python regius). The community structure in terms of food habits and body sizes appeared similar to those of other snake assemblages from different habitats of southern Nigeria. The conservation implications of our results are also discussed. Résumé On a étudié entre 1996 et 2000 la structure de la communauté des serpents dans un transect de la zone écologique de mangroves du sud du Nigeria, en Afrique de l'Ouest. On a étudié, dans trois habitats importants, la diversité taxonomique et la fréquence des observations par rapport à l'importance des échantillonnages. En termes généraux, la communauté des serpents y semblait moins complexe que dans d'autres habitats de la même région géographique (c.-à-d. la forêt marécageuse et une mosaïque de plantations forestières). En fait, on n'a rapporté que 18 espèces, alors qu'on sait que 43 espèces vivent dans les habitats voisins. Une Analyse du Composant Principal a permis de ranger les différentes espèces en deux groupes principaux, liés aux habitats où se sont faites les captures : (1) un groupe avec les espèces des biotes de forêt pluviale (Toxicodryas blandingii, Thelotornis kirtlandii, Thrasops flavigularis, Rhamnophis aethiopissa, Gastropyxis smaragdina, Grayia smythii, Pseudohaje goldii, Python sebae) et (2) un groupe d'espèces qui, au moins dans le delta du Niger, sont typiquement liées à des habitats dégradés, y compris des savanes dérivées, des plantations et des faubourgs urbains (Psammophis phillipsi, Philothamnus cf. nitidus, Hapsidophrys lineatus, Crotaphopeltis hotamboeia, Boaedon lineatus, Naja nigricollis, Python regius). La structure de la communauté, en ce qui concerne les habitudes alimentaires et la taille corporelle, était semblable à celle des autres groupes de serpents dans différents habitats du sud du Nigeria. On discute de l'implication de nos résultats pour la conservation. [source] Weak phylogenetic effects on ecological niches of Sylvia warblersJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 5 2003K. Böhning-Gaese Abstract To understand the evolution of ecological niches it is important to know whether niche evolution is constrained by phylogeny. We approached this question for Sylvia warblers by testing if closely related species are more similar in 20 ecologically relevant morphological traits than distantly related species. Phylogenetic relatedness was quantified using a molecular phylogeny based on the mitochondrial cytochrome b gene. By Principal Component Analysis (PCA) two major niche axes were extracted. We tested the individual ecomorphological traits and the positions of the species on the PCA axes for phylogenetic effects using Mantel tests. The results demonstrated small but significant phylogenetic effects only for the length of the middle toe, a trait probably correlated with locomotion. In general, however, phylogenetic effects were very weak. This suggests that ecological niches in passerine birds have the potential to evolve rapidly and are not subject to major phylogenetic constraints. [source] IMPACT OF DRYING AND STORAGE TIME ON SENSORY CHARACTERISTICS OF ROSEMARY (ROSMARINUS OFFICINALIS L.)JOURNAL OF SENSORY STUDIES, Issue 1 2007M.C. DÍAZ-MAROTO ABSTRACT The effect of drying treatment on the aroma characteristics of rosemary (Rosmarinus Officinalis L.) was studied using the Quantitative Descriptive Analysis (QDA) with a trained panel and by Free Choice Profiling (FCP) analysis with a consumer group. Differences between samples were observed after applying Principal Component Analysis to the QDA data and Generalized Procrustes Analysis to the FCP data. The highest differences were found between fresh rosemary samples and dried samples. However, dried samples (obtained by oven-drying at 45C and commercial samples purchased at the markets and stored for 6 months) showed significant differences in their sensory characteristics. Odor detection thresholds of the fresh rosemary leaves were calculated in water and in potato sauce, and significant differences were found. [source] DATA ANALYTICAL METHODOLOGIES IN THE DEVELOPMENT OF A VOCABULARY FOR EVALUATION OF MEAT QUALITYJOURNAL OF SENSORY STUDIES, Issue 6 2002M.G. O'SULLIVAN ABSTRACT Pork patties from M. longissimus dorsi and M. psoas major were used by a sensory panel to develop a descriptive vocabulary to describe warmed-over flavor development. The patties were made from meat from animals supplemented with one of four dietary treatments, (I) control diet, (II) supplemental iron (7 g iron (II) sulfate/kg feed), (III) supplemental vitamin E (200 mg dl-,-tocopherol acetate/kg of feed) and (IV) supplemental vitamin E + supplemental iron. The sample set used for training reflected the variation in muscle type and degree of warmed-over flavor development (day 1 and 5). The sensory terms selected had to be relevant to the samples, discriminate between the samples, have cognitive clarity and be nonredundant. Based on these selection criteria an initial training list of 36 sensory terms consisting of odors, flavors, basic tastes and aftertastes was developed in a pretrial using experts with product knowledge. This list constituted the start of training the panel. Principle Component Analysis (PCA) and assessor suggestions were used for reducing the number of terms and after 5 days of training this list was reduced to 21 sensory terms. The discriminative ability of the sensory panel improved over the course of sensory training and was quantified by using the mean assessor signal to noise ratios (S/N) for the sensory terms for each training session. This signal to noise ratio is essentially the total initial variance divided by the residual cross-validated variance. Subsequent detailed multivariate analysis found that the bilinear descriptor leverage was a particularly efficient method for term reduction. [source] MATCHING RESULTS OF TWO INDEPENDENT HIGHLY TRAINED SENSORY PANELS USING DIFFERENT DESCRIPTIVE ANALYSIS METHODS,JOURNAL OF SENSORY STUDIES, Issue 5 2002VARAPHA LOTONG ABSTRACT Two independent, highly trained panels separately conducted descriptive analysis of orange juices using different descriptive analysis methods and sets of samples. Lexicons were developed independently. One panel evaluated 23 orange juice products and identified and referenced 24 attributes. The other panel evaluated 17 products and identified 17 attributes for testing. Though not identical, the lexicons developed by both panels were similar overall. To compare the sensory space of the product category, Principal Component Analysis (PCA) and sensory maps were developed separately for each panel. The comparison showed that the underlying sample spaces obtained from both panels were comparable in many ways. Key flavor characteristics for the same types of orange juice products were described similarly by both panels. These data indicate that the process of using highly trained panels that define attributes and use reference standards for descriptive sensory analysis can give objective and comparable information for a product category across different panels. [source] Chromatographic classification and comparison of commercially available perfluorinated stationary phases for reversed-phase liquid chromatography using Principal Component AnalysisJOURNAL OF SEPARATION SCIENCE, JSS, Issue 3-4 2003Melvin R. Euerby Abstract A range of ten perfluorophenyl and perfluoroalkyl stationary phases has been evaluated using standard chromatographic tests and probes. Principal Component Analysis of the data has indicated that the phases can be divided into distinct groupings. Extending the dataset to include standard alkyl and phenyl phases provided further data interpretation to support the orthogonal selectivity claims made for perfluorinated phases. The analysis of a range of basic analytes showed an unusual extended retention of hydrophilic basic analytes with perfluorophases. Furthermore, a non-linear relationship between the amount of organic modifier and the logarithm of the retention factor was observed, for the hydrophilic bases, which could not be modelled with LC prediction softwares. This was in sharp contrast to the alkyl and phenyl phases examined. Basic analyte retention on perfluoroalkyl phases could be modelled adequately for the lipophilic bases. Exploration of the retention mechanism of these perfluoro phases indicated that silanol interactions were important in retention and selectivity. Using a rapid, isocratic, high organic modifier methodology, it was possible to analyse a mixture containing a lipophilic steroid, hydrophilic base and an internal standard in < 4 minutes with a perfluorophenyl phase. This had previously only been achievable with an alkyl phase under gradient elution conditions. [source] INFLUENCE OF UNIAXIAL COMPRESSION RATE ON RHEOLOGICAL PARAMETERS AND SENSORY TEXTURE PREDICTION OF COOKED POTATOESJOURNAL OF TEXTURE STUDIES, Issue 1 2000ANETTE KISTRUP THYBO ABSTRACT The effect of uniaxial compression rate (20,1000 mm/min) on the parameters: Stress (,ftrue), strain (,fHencky) and work to fracture (Wf), modulus of deformability (Ed), maximum slope before fracture (Emax) and work during 75% compression (Wtotal) was investigated for ten potato varieties. Multivariate data analysis was used to study the correlation between and within the sensory and nonsensory measurements by Principal Component Analysis (PCA) which showed ,ftrue, Emax, Wf, and Wtotal to explain the same type of information in the data, and ,fHencky versus Ed another type of information in the data. The deformation rate had a large effect on ,fHencky. Nine sensory texture attributes covering the mechanical, geometrical and moistness attributes were evaluated. Relationships between uniaxial compression data at various deformation rates and the sensory texture attributes were studied by Partial Least Squares Regression (PLSR). A minor effect of deformation rate on the correlation with the sensory texture properties was obtained. Mechanical properties were predicted to a higher extent than the geometrical attributes and moistness. The prediction of the mechanical, geometrical and moistness attributes increased largely by using uniaxial compression supplemented by chemical measures such as dry matter and pectin methylesterase, but here no relevant effect of deformation rate was obtained. [source] Directional positive feedback and pattern at an alpine tree lineJOURNAL OF VEGETATION SCIENCE, Issue 1 2004Kathryn J. Alftine Lesica (2002) Abstract. The spatial pattern at alpine tree line may be part of a feedback process in which wind plays a central role. The basic aspects of such a feedback were embedded in a cellular automaton. Spatial metrics of the patterns generated by this simulation and those of observed patterns at a windy tree line site were ordinated using Principal Component Analysis. Only the simulations that included a directionally weighted feedback fell close to the observed sites in ordination space. MANOVA indicated that the directionally weighted feedback is most important in structuring the tree line pattern, but that random hotspots for establishment and the overall steepness of the environmental gradient from forest to tundra in space also have an effect. The importance of wind in determining feedback with the spatial pattern of a canopy indicates that nonlinear reactions to climatic change are likely. [source] Effects of selective logging on tree diversity, composition and plant functional type patterns in a Bornean rain forestJOURNAL OF VEGETATION SCIENCE, Issue 1 2003René Verburg Sidiyasa et al. (1999); Anon. (1955,1994) Abstract. The effects of selective logging on tree diversity, changes in tree species composition and plant functional types were studied with the use of seven permanent plots in virgin and in logged forest. All plots were located in a lowland dipterocarp rain forest in East Kalimantan on the island of Borneo. Just after logging and during the following 20 yr tree diversity measured as Fishers', was not significantly affected in logged forest plots. Temporal shifts in tree species composition were analysed with Principal Component Analysis (PCA). Logged forest plots had much larger changes over time than virgin forest plots. In the smallest diameter class, some logged forest plots showed a distinct trajectory in PCA space compared to virgin forest plots, while in larger diameter classes movement of logged plots in PCA space was random. This suggests that there is no predetermined community to which logged forest plots tend to shift when recovering from logging. We found a significant negative correlation between diameter increments and the species-specific wood densities of tree species. Species-specific wood density and potential tree height were used to assign species to five PFTs. As expected, logging increased the fraction of softwood stems in small diameter classes. In the largest diameter classes (, 50 cm DBH) a strong decrease of softwood emergent stems was found in logged forest plots. After more than 20 yr no recruitment was found of softwood emergent stems in selectively logged forest. [source] Floristic composition of a Swedish semi-natural grassland during six years of elevated atmospheric CO2JOURNAL OF VEGETATION SCIENCE, Issue 5 2002Mark Marissink Krok & Almquist (2001) Abstract. A semi-natural grassland in Sweden was exposed to an elevated CO2 concentration during a six-year open-top chamber experiment. Vegetation composition was assessed twice a year using the point-intercept method. The field had been grazed previously, but when the experiment started this was replaced with a cutting regime with one cut (down to ground level) each year in early August. From the third to the sixth year of the study the harvested material was divided into legumes, non-leguminous forbs and grasses, dried and weighed. Elevated CO2 had an effect on species composition (as analysed by Principal Component Analysis) that increased over time. It also tended to increase diversity (Shannon index) in summer, but reduce it in spring. However, the effects of the weather and/or time on species composition and diversity were much more prominent than CO2 effects. Since the weather was largely directional over time (from dry to wet), with the exception of the fifth year, it was difficult to distinguish between weather effects and changes caused by a changed management regime. In all treatments, grasses increased over time in both mass and point-intercept measurements, whereas non-leguminous forbs decreased in mass, but not in point-intercept measurements. Legumes increased in the point-intercept measurements, but not in biomass, at elevated CO2, but not in the other treatments. Overall, we found that elevated CO2 affected species composition; however, it was only one of many factors and a rather weak one. [source] Synoptic features associated with critical water level rises in the Río de la PlataMETEOROLOGICAL APPLICATIONS, Issue 2 2005A. P. Alessandro This study aims to describe the synoptic features that caused the water level in the Río de la Plata estuary to rise above critical levels between December 1989 and December 1998. Floods in the estuary can seriously affect the land beside the river from Punta Indio (35.22°S,57.17°W) to the Paraná delta, including the lowlands of Buenos Aires City. Surface pressure patterns associated with floods in the Río de la Plata estuary were obtained by using Quartimax rotated T-mode Principal Component Analysis (PCA) of 1000 hPa geopotential heights. The PCA patterns and 1000 hPa composite and anomaly fields show two main causes for overflows in the Río de la Plata estuary. First, the presence of a surface anticyclone, located south of Buenos Aires province and over northern Patagonia; and, second, cyclogenesis over northeastern Argentina or over Uruguay. The two synoptic features are often present simultaneously. Two representative points were selected in the area under study: one over the continent at the Aeroparque meteorological station (34.34°S,58.25°W) and another over the ocean between 36°S,56°W and 36°S,50°W. Predominant 1000 hPa wind directions associated with overflows were SE at the former location and SSW at the latter. Based on the analysis of the obtained fields, the relationship between the estuary overflow and blocking situations and/or positive pressure anomalies over southern South America and adjacent seas was studied. The zonal circulation index (I), used to detect blocking actions, was found to be useful for identifying synoptic situations related to the estuary swelling. The probability of water level rises in the Río de la Plata with a blocking or I > 0 at 70°W is 0.48, 0.72, 0.78 and 0.73, for summer, autumn, winter and spring, respectively. When I > 0 is observed over the Atlantic at 40°W the probability of flooding is 0.16 for the whole year, but it decreases to 0.028 in autumn, winter and spring. These results and weather charts from different numerical prediction models show that alerts of possible Río de la Plata estuary overflow can be released five days in advance. Copyright © 2005 Royal Meteorological Society [source] A PCR-based method for diet analysis in freshwater organisms using 18S rDNA barcoding on faecesMOLECULAR ECOLOGY RESOURCES, Issue 1 2010EMMANUEL CORSE Abstract The development of DNA barcoding from faeces represents a promising method for animal diet analysis. However, current studies mainly rely on prior knowledge of prey diversity for a specific predator rather than on a range of its potential prey species. Considering that the feeding behaviour of teleosts may evolve with their environment, it could prove difficult to establish an exhaustive listing of their prey. In this article, we extend the DNA barcoding approach to diet analysis to allow the inclusion of a wide taxonomic range of potential prey items. Thirty-four ecological clade-specific primer sets were designed to cover a large proportion of prey species found in European river ecosystems. Selected primers sets were tested on isolated animal, algal or plant tissues and thereafter on fish faeces using nested PCR to increase DNA detection sensitivity. The PCR products were sequenced and analysed to confirm the identity of the taxa and to validate the method. The methodology developed here was applied to a diet analysis of three freshwater cyprinid species that are assumed to have similar feeding behaviour [Chondrostoma toxostoma toxostoma (Vallot 1837), Chondrostoma nasus nasus (Linnaeus, 1758) and Barbus barbus, (Linneaus 1758)]. These three species were sampled in four different hydrographic basins. Principal Component Analysis based on prey proportions identified distinct perilithon grazer and benthophagous behaviours. Furthermore, our results were consistent with the available literature on feeding behaviour in these fish. The simplicity of the PCR-based method and its potential generalization to other freshwater organisms may open new perspectives in food web ecology. [source] Combined Use of PCA and QSAR/QSPR to Predict the Drugs Mechanism of Action.MOLECULAR INFORMATICS, Issue 4 2009An Application to the NCI ACAM Database Abstract During the years the National Cancer Institute (NCI) accumulated an enormous amount of information through the application of a complex protocol of drugs screening involving several tumor cell lines, grouped into panels according to the disease class. The Anti-cancer Agent Mechanism (ACAM) database is a set of 122 compounds with anti-cancer activity and a reasonably well known mechanism of action, for which are available drug screening data that measure their ability to inhibit growth of a panel of 60 human tumor lines, explicitly designed as a training set for neural network and multivariate analysis. The aim of this work is to adapt a methodology (previously developed for the analysis of DNA minor groove binders) for the analysis of NCI ACAM database, using Principal Component Analysis (PCA) and QSAR/QSPR for the prediction of the mechanism of action of anti-cancer drugs. The entire database was splitted in a training set of 60 structures and a test set of 48 ones, and each set was expressed in form of a matrix on which further procedures were performed. Three statistical parameters were calculated: First Attempt of Prediction (FAP) expresses the percentage of correct predictions at first attempt, Total Attempt of Prediction (TAP) expresses the total percentage of correct predictions across all the three attempts, Non-Classified (NC) expresses the percentage of compounds whose mechanism of action has failed to be predicted. The predictive ability of this approach is variable, but the results obtained are generally good; using 50% Growth Inhibiting concentration (GI50) values as training data, we were able to assign a correct mechanism of action with a good degree of reliability (more than 79%). [source] QSAR of Progestogens: Use of a Priori and Computed Molecular Descriptors and Molecular GraphicsMOLECULAR INFORMATICS, Issue 4 2003Rudolf Kiralj Abstract Quantitative Structure-Activity Relationship (QSAR) study of two sets of oral progestogens was carried out by using Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Partial Least Squares (PLS). A priori, computed (at DFT 6-31G** level) and molecular graphics and modeling descriptors were employed. Molecular graphics and modeling studies of crystal structures of complexes progesterone receptor (PR)-progesterone, Fab,-progesterone and PR-metribolone have been performed. QSAR of progestogens is a three-dimensional phenomenon (over 96% of information is explained by the first three Principal Components), which can be, although it exhibits significant non-linearity, treated well with linear methods such as PLS. Progestogen activity depends primarily on double bond contents and resonance effects which define the skeletal conformation, and also on substituent characteristics (size, conformational and electronic properties). Sterical relationships between a substituent at C6(sp2) or C6(sp3)-, and sulfur atom from Met 801 residue of PR are important for progesterone binding to the protein and can be quantified. Basically the same was observed for substituents at ,-C10 with respect to residue Met759. [source] Cosmic microwave background signal in Wilkinson Microwave Anisotropy Probe three-year data with fasticaMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 4 2007D. Maino ABSTRACT We present an application of the fast Independent Component Analysis (fastica) to the Wilkinson Microwave Anisotropy Probe (WMAP) three-year data with the goal of extracting the cosmic microwave background (CMB) signal. We evaluate the confidence of our results by means of Monte Carlo simulations including the CMB, foreground contaminations and instrumental noise specific to each WMAP frequency band. We perform a complete analysis involving all or a subset of the WMAP channels in order to select the optimal combination for CMB extraction, using the frequency scaling of the reconstructed component as a figure of merit. We find that the combination KQVW provides the best CMB frequency scaling, indicating that the low-frequency foreground contamination in Q, V and W bands is better traced by the emission in the K band. The CMB angular power spectrum is recovered up to the degree scale; it is consistent within errors for all WMAP channel combinations considered, and in close agreement with the WMAP three-year results. A power spectrum analysis is made of the sky map divided into two hemispheres that have been previously reported as showing evidence of an asymmetric ratio of power on large angular scales. We then confirm the findings of several previous works with independent techniques. [source] Y-specific microsatellites reveal an African subfamily in taurine (Bos taurus) cattleANIMAL GENETICS, Issue 3 2010L. Pérez-Pardal Summary Five cattle Y-specific microsatellites, totalling six loci, were selected from a set of 44 markers and genotyped on 608 Bos taurus males belonging to 45 cattle populations from Europe and Africa. A total of 38 haplotypes were identified. Haplogroups (Y1 and Y2) previously defined using single nucleotide polymorphisms did not share haplotypes. Nine of the 27 Y2-haplotypes were only present in African cattle. Network and correspondence analyses showed that this African-specific subfamily clustered separately from the main Y2-subfamily and the Y1 haplotypes. Within-breed genetic variability was generally low, with most breeds (78%) showing haplotypes belonging to a single haplogroup. amova analysis showed that partitioning of genetic variation among breeds can be mainly explained by their geographical and haplogroup assignment. Between-breed genetic variability summarized via Principal Component Analysis allowed the identification of three principal components explaining 94.2% of the available information. Projection of principal components on geographical maps illustrated that cattle populations located in mainland Europe, the three European Peninsulas and Mediterranean Africa presented similar genetic variation, whereas those breeds from Atlantic Europe and British Islands (mainly carrying Y1 haplotypes) and those from Sub-Saharan Africa (belonging to Y2-haplogroup) showed genetic variation of a different origin. Our study confirmed the existence of two large Y-chromosome lineages (Y1 and Y2) in taurine cattle. However, Y-specific microsatellites increased analytical resolution and allowed at least two different Y2-haplotypic subfamilies to be distinguished, one of them restricted to the African continent. [source] A Variable-Sized Sliding-Window Approach for Genetic Association Studies via Principal Component AnalysisANNALS OF HUMAN GENETICS, Issue 6 2009Rui Tang Summary Recently with the rapid improvements in high-throughout genotyping techniques, researchers are facing the very challenging task of analysing large-scale genetic associations, especially at the whole-genome level, without an optimal solution. In this study, we propose a new approach for genetic association analysis that is based on a variable-sized sliding-window framework and employs principal component analysis to find the optimum window size. With the help of the bisection algorithm in window-size searching, our method is more computationally efficient than available approaches. We evaluate the performance of the proposed method by comparing it with two other methods,a single-marker method and a variable-length Markov chain method. We demonstrate that, in most cases, the proposed method out-performs the other two methods. Furthermore, since the proposed method is based on genotype data, it does not require any computationally intensive phasing program to account for uncertain haplotype phase. [source] Multi-scale responses of plant species diversity in semi-natural buffer strips to agricultural landscapesAPPLIED VEGETATION SCIENCE, Issue 2 2008Maohua Ma Question: How does agricultural land usage affect plant species diversity in semi-natural buffer strips at multiple scales? Location: Lepsämä River watershed, Nurmijärvi, Southern Finland. Methods: Species diversity indicators included both richness and evenness. Plant communities in buffer strips were surveyed in 29 sampling sites. Using ArcGIS Desktop 9.0 (ArcInfo) and Fragstats 3.3 for GIS analysis, the landscape composition around each sampling site was characterized by seven parameters in square sectors at five scales: 4, 36, 100, 196, and 324ha. For each scale, Principle Component Analysis was used to examine the importance of each structural metric to diversity indicators using multiple regression and other simple analyses. Results: For all but the smallest scales (4 ha), two structural metrics including the diversity of land cover types and percentage of arable land were positively and negatively correlated with species richness, respectively. Both metrics had the highest correlation coefficients for species richness at the second largest scale (196 ha). The density of arable field edges between the fields was the only metric that correlated with species evenness for all scales, which had highest predictive power at the second smallest scale (36 ha). Conclusions: Species richness and evenness of buffer strips had scale-dependent relationships to land use in agricultural ecosystems. The results of this study indicated that species richness depends on the pattern of arable land use at large scales, which may relate to the regional species pool. Meanwhile, species evenness depended on the level of field edge density at small scales, which relates to how the nearby farmland was divided by the edges (e.g. many small-scale fields with high edge density or a few big-scale fields with low edge density). This implies that it is important to manage the biodiversity of buffer strips within a landscape context at multiple scales. [source] | ||||||||||||||||||||||||||||||||||||||||||||||||||||