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Selected AbstractsOut-of-core compression and decompression of large n -dimensional scalar fieldsCOMPUTER GRAPHICS FORUM, Issue 3 2003Lawrence Ibarria We present a simple method for compressing very large and regularly sampled scalar fields. Our method is particularlyattractive when the entire data set does not fit in memory and when the sampling rate is high relative to thefeature size of the scalar field in all dimensions. Although we report results foranddata sets, the proposedapproach may be applied to higher dimensions. The method is based on the new Lorenzo predictor, introducedhere, which estimates the value of the scalar field at each sample from the values at processed neighbors. The predictedvalues are exact when the n-dimensional scalar field is an implicit polynomial of degreen, 1. Surprisingly,when the residuals (differences between the actual and predicted values) are encoded using arithmetic coding,the proposed method often outperforms wavelet compression in anL,sense. The proposed approach may beused both for lossy and lossless compression and is well suited for out-of-core compression and decompression,because a trivial implementation, which sweeps through the data set reading it once, requires maintaining only asmall buffer in core memory, whose size barely exceeds a single (n,1)- dimensional slice of the data. Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Compression, scalar fields,out-of-core. [source] Dunefoot dynamics along the Dutch coastEARTH SURFACE PROCESSES AND LANDFORMS, Issue 10 2002B. G. Ruessink Abstract The dynamics of the dunefoot along a 160 km portion of the Dutch coast has been investigated based on a data set of annual surveys dating back to as early as 1850. The linearly detrended (or residual) dunefoot positions comprise an alongshore uniform and an alongshore non-uniform component. The former is expressed as 10 to 15 m of landward retreat along extensive (>10 km) stretches of coast during years with severe storm surges and as up to 5 m of seaward advance during years without significant storm activity. The latter, alongshore non-uniform component is organized in sandwave-like patterns, which may have a longevity of decades to up to the duration of the entire data set (150 years). Their wavelengths vary along the coast, from 3·5 to 10 km; migration rates are 0,200 m a,1. Dunefoot sandwaves are shown to be the shoreward extensions of similar sandwave patterns in the beach position. The non-uniform dunefoot behaviour constitutes at least 80 per cent of the total residual dunefoot dynamics, implying that along the Dutch coast residual dunefoot variability is controlled by temporal and spatial variability in beach characteristics, and not by storm-induced uniform erosion. Various potential mechanisms causing beach sandwaves are discussed. Copyright © 2002 John Wiley & Sons, Ltd. [source] Procedure for separating the selection effect from other effects in diversity,productivity relationshipECOLOGY LETTERS, Issue 6 2001paèková In a greenhouse pot experiment we cultivated six meadow species in a replacement series design. The plants were grown at two sowing densities in monocultures and all possible species combinations. Our aim was to separate the selection effect from other diversity effects. This distinction is based on the notion that true overyielding is not a consequence of the selection effect. We suggest a hierarchical procedure, which is based on a repeated division of samples into the pots with the most productive species present and missing. Overyielding can be then demonstrated by a positive dependence of productivity on species richness in the subsets with the most productive species present. Although we found a strong dependence of biomass on species richness in the entire data set, the hierarchical method revealed no evidence of overyielding. Above-ground biomass in a monoculture was a good predictor of species success in a species mix. [source] Proteomic analysis of osteogenic differentiation of dental follicle precursor cellsELECTROPHORESIS, Issue 7 2009Christian Morsczeck Abstract Recently, there has been an increased interest in unravelling the molecular mechanisms and cellular pathways controlling the differentiation and proliferation of human stem cell lines. Proteome analysis has proven to be an effective approach to comprehensive analysis of the regulatory network of differentiation. In the present study we applied 2-DE combined with capillary-LC-MS/MS analysis to profile differentially regulated proteins upon differentiation of dental follicle precursor cells (DFPCs). Out of 115 differentially regulated proteins, glutamine synthetase, lysosomal proteinase cathepsin B proteins, plastin 3 T-isoform, beta-actin, superoxide dismutases, and transgelin were found to be highly up-regulated, whereas cofilin-1, pro-alpha 1 collagen, destrin, prolyl 4-hydrolase and dihydrolipoamide dehydrogenase were found to be highly down-regulated. The group of up-regulated proteins is associated with actin-bundling and defence against oxidative cellular stress, whereas down-regulated proteins were associated with collagen biosynthesis. Bioinformatic analyses of the entire data set confirmed these findings that represent significant steps towards the understanding of DFPC differentiation. The bioinformatic analyses suggest that proteins associated with cell cycle progression and protein metabolism were down-regulated and proteins involved in catabolism, cell motility and biological quality were up-regulated. These results display the general physiological state of DFPCs before and after osteogenic differentiation. We also identified regulatory proteins, such as the transcription factors TP53 and Sp-1, associated with the differentiation process. Further studies will investigate the impact of identified regulatory proteins for cell proliferation and osteogenic differentiation in DFPCs. [source] Augmentation of a nearest neighbour clustering algorithm with a partial supervision strategy for biomedical data classificationEXPERT SYSTEMS, Issue 1 2009Sameh A. Salem Abstract: In this paper, a partial supervision strategy for a recently developed clustering algorithm, the nearest neighbour clustering algorithm (NNCA), is proposed. The proposed method (NNCA-PS) offers classification capability with a smaller amount of a priori knowledge, where a small number of data objects from the entire data set are used as labelled objects to guide the clustering process towards a better search space. Experimental results show that NNCA-PS gives promising results of 89% sensitivity at 95% specificity when used to segment retinal blood vessels, and a maximum classification accuracy of 99.5% with 97.2% average accuracy when applied to a breast cancer data set. Comparisons with other methods indicate the robustness of the proposed method in classification. Additionally, experiments on parallel environments indicate the suitability and scalability of NNCA-PS in handling larger data sets. [source] Measurement and correlation of microstructures: the case of foliation intersection axesJOURNAL OF METAMORPHIC GEOLOGY, Issue 3 2003A. R. Stallard Abstract Recent studies have used the relative rotation axis of sigmoidal and spiral-shaped inclusion trails, known as Foliation Inflexion/Intersection Axis (FIA), to investigate geological processes such as fold mechanisms and porphyroblast growth. The geological usefulness of this method depends upon the accurate measurement of FIA orientations and correct correlation of temporally related FIAs. This paper uses new data from the Canton Schist to assess the variation in FIA orientations within and between samples, and evaluates criteria for correlating FIAs. For the first time, an entire data set of FIA measurements is published, and data are presented in a way that reflects the variation in FIA orientations within individual samples and provides an indication of the reliability of the data. Analysis of 61 FIA trends determined from the Canton Schist indicate a minimum intrasample range in FIA orientations of 30°. Three competing models are presented for correlation of these FIAs, and each of the models employ different correlation criteria. Correlation of FIAs in Model 1 is based on relative timing and textural criteria, while Model 2 uses relative timing, orientation and patterns of changing FIA orientations, and Model 3 uses relative timing and FIA orientation as correlation criteria. Importantly, the three models differ in the spread of FIA orientations within individual sets, and the number of sets distinguished in the data. Relative timing is the most reliable criterion for correlation, followed by textural criteria and patterns of changing FIA orientations from core to rim of porphyroblasts. It is proposed that within a set of temporally related FIAs, the typical spread of orientations involves clustering of data in a 60° range, but outliers occur at other orientations including near-normal to the peak distribution. Consequently, in populations of FIA data that contain a wide range of orientations, correlation on the basis of orientation is unreliable in the absence of additional criteria. The results of this study suggest that FIAs are best used as semiquantitative indicators of bulk trends rather than an exact measurement for the purpose of quantitative analyses. [source] The Interaction of Reward Genes With Environmental Factors in Contribution to Alcoholism in Mexican AmericansALCOHOLISM, Issue 12 2009Yanlei Du Background:, Alcoholism is a polygenic disorder resulting from reward deficiency; polymorphisms in reward genes including serotonin transporter (5-HTT)-linked polymorphic region (5-HTTLPR), A118G in opioid receptor mu1 (OPRM1), and ,141C Insertion/Deletion (Ins/Del) in dopamine receptor D2 (DRD2) as well as environmental factors (education and marital status) might affect the risk of alcoholism. Objective of the current study was to examine the main and interacting effect of these 3 polymorphisms and 2 environmental factors in contribution to alcoholism in Mexican Americans. Methods:, Genotyping of 5-HTTLPR, OPRM1 A118G, and DRD2-141C Ins/Del was performed in 365 alcoholics and 338 nonalcoholic controls of Mexican Americans who were gender- and age-matched. Alcoholics were stratified according to tertiles of MAXDRINKS, which denotes the largest number of drinks consumed in one 24-hour period. Data analysis was done in the entire data set and in each alcoholic stratum. Multinomial logistic regression was conducted to explore the main effect of 3 polymorphisms and 2 environmental factors (education and marital status); classification tree, generalized multifactor dimensionality reduction (GMDR) analysis, and polymorphism interaction analysis version 2.0 (PIA 2) program were used to study factor interaction. Results:, Main effect of education, OPRM1, and DRD2 was detected in alcoholic stratum of moderate and/or largest MAXDRINKS with education ,12 years, OPRM1 118 A/A, and DRD2 ,141C Ins/Ins being risk factors. Classification tree analysis, GMDR analysis, and PIA 2 program all supported education*OPRM1 interaction in alcoholics of largest MAXDRINKS with education ,12 years coupled with OPRM1 A/A being a high risk factor; dendrogram showed synergistic interaction between these 2 factors; dosage-effect response was also observed for education*OPRM1 interaction. No definite effect of marital status and 5-HTTLPR in pathogenesis of alcoholism was observed. Conclusions:, Our results suggest main effect of education background, OPRM1 A118G, and DRD2 ,141C Ins/Del as well as education*OPRM1 interaction in contribution to moderate and/or severe alcoholism in Mexican Americans. Functional relevance of these findings still needs to be explored. [source] Statistical determination of diagnostic species for site groups of unequal sizeJOURNAL OF VEGETATION SCIENCE, Issue 6 2006Lubomír Tichy Abstract Aim: Concentration of species occurrences in groups of classified sites can be quantified with statistical measures of fidelity, which can be used for the determination of diagnostic species. However, for most available measures fidelity depends on the number of sites within individual groups. As the classified data sets typically contain site groups of unequal size, such measures do not enable a comparison of numerical fidelity values of species between different site groups. We therefore propose a new method of measuring fidelity with presence/absence data after equalization of the size of the site groups. We compare the properties of this new method with other measures of statistical fidelity, in particular with the Dufrêne-Legendre Indicator Value (IndVal) index. Methods: The size of site groups in the data set is equalized, while relative frequencies of species occurrence within and outside of these groups are kept constant. Then fidelity is calculated using the phi coefficient of association. Results: Fidelity values after equalization are independent of site group size, but their numerical values vary independently of the statistical significance of fidelity. By changing the size of the target site group relative to the size of the entire data set, the fidelity measure can be made more sensitive to either common or rare species. We show that there are two modifications of the IndVal index for presence/absence data, one of which is also independent of the size of site groups. Conclusion: The phi coefficient applied to site groups of equalized size has advantages over other statistical measures of fidelity based on presence/absence data. Its properties are close to an intuitive understanding of fidelity and diagnostic species in vegetation science. Statistical significance can be checked by calculation of another fidelity measure that is a function of statistical significance, or by direct calculation of the probability of observed species concentrations by Fisher's exact test. An advantage of the new method over IndVal is its ability to distinguish between positive and negative fidelity. One can also weight the relative importance of common and rare species by changing the equalized size of the site groups. [source] A microarray-based approach for the identification of epigenetic biomarkers for the noninvasive diagnosis of fetal diseasePRENATAL DIAGNOSIS, Issue 11 2009Tianjiao Chu Abstract Objectives We describe a novel microarray-based approach for the high-throughput discovery of epigenetic biomarkers for use in the noninvasive detection of fetal genetic disease. Methods We combined a 215 060-probe custom oligonucleotide microarray with a comprehensive library preparation method and novel statistical tools to compare DNA methylation patterns in chorionic villus samples (CVS) with gestational age-matched maternal blood cell (MBC) samples. Our custom microarray was designed to provide high-resolution coverage across human chromosomes 13, 18 and 21. Results We identified 6311 MspI/HpaII sites across all three chromosomes that displayed tissue-specific differential CpG methylation patterns. To maximize the probability of identifying biomarkers that have clinical utility we filtered our data to identify MspI/HpaII sites that are within 150 bp of a highly polymorphic single nucleotide polymorphism (SNP) so that its allelic ratio may be determined for the detection of fetal aneuploidy. Our microarray design and the computational tools used for data analysis are available for download as is the entire data set. Conclusions This high-resolution analysis of DNA methylation patterns in the human placenta during the first trimester of pregnancy identifies numerous potential biomarkers for the diagnosis of fetal aneuploidy on chromosomes 13, 18 and 21. Copyright © 2009 John Wiley & Sons, Ltd. [source] | |||||||||||||