Sampling procedures for inventory of commercial volume tree species in Amazon Forest.

PubMed

Netto, Sylvio P; Pelissari, Allan L; Cysneiros, Vinicius C; Bonazza, Marcelo; Sanquetta, Carlos R

2017-01-01

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Mayday - integrative analytics for expression data

PubMed Central

2010-01-01

Background DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files. Results We have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved. Conclusions We present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org. PMID:20214778

ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

PubMed Central

Metsalu, Tauno; Vilo, Jaak

2015-01-01

The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/. PMID:25969447

Evaluating and learning from RNA pseudotorsional space: quantitative validation of a reduced representation for RNA structure.

PubMed

Wadley, Leven M; Keating, Kevin S; Duarte, Carlos M; Pyle, Anna Marie

2007-09-28

Quantitatively describing RNA structure and conformational elements remains a formidable problem. Seven standard torsion angles and the sugar pucker are necessary to characterize the conformation of an RNA nucleotide completely. Progress has been made toward understanding the discrete nature of RNA structure, but classifying simple and ubiquitous structural elements such as helices and motifs remains a difficult task. One approach for describing RNA structure in a simple, mathematically consistent, and computationally accessible manner involves the invocation of two pseudotorsions, eta (C4'(n-1), P(n), C4'(n), P(n+1)) and theta (P(n), C4'(n), P(n+1), C4'(n+1)), which can be used to describe RNA conformation in much the same way that varphi and psi are used to describe backbone configuration of proteins. Here, we conduct an exploration and statistical evaluation of pseudotorsional space and of the Ramachandran-like eta-theta plot. We show that, through the rigorous quantitative analysis of the eta-theta plot, the pseudotorsional descriptors eta and theta, together with sugar pucker, are sufficient to describe RNA backbone conformation fully in most cases. These descriptors are also shown to contain considerable information about nucleotide base conformation, revealing a previously uncharacterized interplay between backbone and base orientation. A window function analysis is used to discern statistically relevant regions of density in the eta-theta scatter plot and then nucleotides in colocalized clusters in the eta-theta plane are shown to have similar 3-D structures through RMSD analysis of the RNA structural constituents. We find that major clusters in the eta-theta plot are few, underscoring the discrete nature of RNA backbone conformation. Like the Ramachandran plot, the eta-theta plot is a valuable system for conceptualizing biomolecular conformation, it is a useful tool for analyzing RNA tertiary structures, and it is a vital component of new approaches for solving the 3-D structures of large RNA molecules and RNA assemblies.

A technique for conducting point pattern analysis of cluster plot stem-maps

Treesearch

C.W. Woodall; J.M. Graham

2004-01-01

Point pattern analysis of forest inventory stem-maps may aid interpretation and inventory estimation of forest attributes. To evaluate the techniques and benefits of conducting point pattern analysis of forest inventory stem-maps, Ripley`s K(t) was calculated for simulated tree spatial distributions and for over 600 USDA Forest Service Forest...

Revealing the ecological content of long-duration audio-recordings of the environment through clustering and visualisation.

PubMed

Phillips, Yvonne F; Towsey, Michael; Roe, Paul

2018-01-01

Audio recordings of the environment are an increasingly important technique to monitor biodiversity and ecosystem function. While the acquisition of long-duration recordings is becoming easier and cheaper, the analysis and interpretation of that audio remains a significant research area. The issue addressed in this paper is the automated reduction of environmental audio data to facilitate ecological investigations. We describe a method that first reduces environmental audio to vectors of acoustic indices, which are then clustered. This can reduce the audio data by six to eight orders of magnitude yet retain useful ecological information. We describe techniques to visualise sequences of cluster occurrence (using for example, diel plots, rose plots) that assist interpretation of environmental audio. Colour coding acoustic clusters allows months and years of audio data to be visualised in a single image. These techniques are useful in identifying and indexing the contents of long-duration audio recordings. They could also play an important role in monitoring long-term changes in species abundance brought about by habitat degradation and/or restoration.

Revealing the ecological content of long-duration audio-recordings of the environment through clustering and visualisation

PubMed Central

Towsey, Michael; Roe, Paul

2018-01-01

Audio recordings of the environment are an increasingly important technique to monitor biodiversity and ecosystem function. While the acquisition of long-duration recordings is becoming easier and cheaper, the analysis and interpretation of that audio remains a significant research area. The issue addressed in this paper is the automated reduction of environmental audio data to facilitate ecological investigations. We describe a method that first reduces environmental audio to vectors of acoustic indices, which are then clustered. This can reduce the audio data by six to eight orders of magnitude yet retain useful ecological information. We describe techniques to visualise sequences of cluster occurrence (using for example, diel plots, rose plots) that assist interpretation of environmental audio. Colour coding acoustic clusters allows months and years of audio data to be visualised in a single image. These techniques are useful in identifying and indexing the contents of long-duration audio recordings. They could also play an important role in monitoring long-term changes in species abundance brought about by habitat degradation and/or restoration. PMID:29494629

GOplot: an R package for visually combining expression data with functional analysis.

PubMed

Walter, Wencke; Sánchez-Cabo, Fátima; Ricote, Mercedes

2015-09-01

Despite the plethora of methods available for the functional analysis of omics data, obtaining comprehensive-yet detailed understanding of the results remains challenging. This is mainly due to the lack of publicly available tools for the visualization of this type of information. Here we present an R package called GOplot, based on ggplot2, for enhanced graphical representation. Our package takes the output of any general enrichment analysis and generates plots at different levels of detail: from a general overview to identify the most enriched categories (bar plot, bubble plot) to a more detailed view displaying different types of information for molecules in a given set of categories (circle plot, chord plot, cluster plot). The package provides a deeper insight into omics data and allows scientists to generate insightful plots with only a few lines of code to easily communicate the findings. The R package GOplot is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/GOplot. The shiny web application of the Venn diagram can be found at: https://wwalter.shinyapps.io/Venn/. A detailed manual of the package with sample figures can be found at https://wencke.github.io/ fscabo@cnic.es or mricote@cnic.es. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Using cluster analysis and a classification and regression tree model to developed cover types in the Sky Islands of southeastern Arizona [Abstract

Treesearch

Jose M. Iniguez; Joseph L. Ganey; Peter J. Daugherty; John D. Bailey

2005-01-01

The objective of this study was to develop a rule based cover type classification system for the forest and woodland vegetation in the Sky Islands of southeastern Arizona. In order to develop such system we qualitatively and quantitatively compared a hierarchical (Ward’s) and a non-hierarchical (k-means) clustering method. Ecologically, unique groups and plots...

Applying Model Analysis to a Resource-Based Analysis of the Force and Motion Conceptual Evaluation

ERIC Educational Resources Information Center

Smith, Trevor I.; Wittmann, Michael C.; Carter, Tom

2014-01-01

Previously, we analyzed the Force and Motion Conceptual Evaluation in terms of a resources-based model that allows for clustering of questions so as to provide useful information on how students correctly or incorrectly reason about physics. In this paper, we apply model analysis to show that the associated model plots provide more information…

Nature of bonding and cooperativity in linear DMSO clusters: A DFT, AIM and NCI analysis.

PubMed

Venkataramanan, Natarajan Sathiyamoorthy; Suvitha, Ambigapathy

2018-05-01

This study aims to cast light on the nature of interactions and cooperativity that exists in linear dimethyl sulfoxide (DMSO) clusters using dispersion corrected density functional theory. In the linear DMSO, DMSO molecules in the middle of the clusters are bound strongly than at the terminal. The plot of the total binding energy of the clusters vs the cluster size and mean polarizabilities vs cluster size shows an excellent linearity demonstrating the presence of cooperativity effect. The computed incremental binding energy of the clusters remains nearly constant, implying that DMSO addition at the terminal site can happen to form an infinite chain. In the linear clusters, two σ-hole at the terminal DMSO molecules were found and the value on it was found to increase with the increase in cluster size. The quantum theory of atoms in molecules topography shows the existence of hydrogen and SO⋯S type in linear tetramer and larger clusters. In the dimer and trimer SO⋯OS type of interaction exists. In 2D non-covalent interactions plot, additional peaks in the regions which contribute to the stabilization of the clusters were observed and it splits in the trimer and intensifies in the larger clusters. In the trimer and larger clusters in addition to the blue patches due to hydrogen bonds, additional, light blue patches were seen between the hydrogen atom of the methyl groups and the sulphur atom of the nearby DMSO molecule. Thus, in addition to the strong H-bonds, strong electrostatic interactions between the sulphur atom and methyl hydrogens exists in the linear clusters. Copyright © 2018 Elsevier Inc. All rights reserved.

Towards a New Generation of Time-Series Visualization Tools in the ESA Heliophysics Science Archives

NASA Astrophysics Data System (ADS)

Perez, H.; Martinez, B.; Cook, J. P.; Herment, D.; Fernandez, M.; De Teodoro, P.; Arnaud, M.; Middleton, H. R.; Osuna, P.; Arviset, C.

2017-12-01

During the last decades a varied set of Heliophysics missions have allowed the scientific community to gain a better knowledge on the solar atmosphere and activity. The remote sensing images of missions such as SOHO have paved the ground for Helio-based spatial data visualization software such as JHelioViewer/Helioviewer. On the other hand, the huge amount of in-situ measurements provided by other missions such as Cluster provide a wide base for plot visualization software whose reach is still far from being fully exploited. The Heliophysics Science Archives within the ESAC Science Data Center (ESDC) already provide a first generation of tools for time-series visualization focusing on each mission's needs: visualization of quicklook plots, cross-calibration time series, pre-generated/on-demand multi-plot stacks (Cluster), basic plot zoom in/out options (Ulysses) and easy navigation through the plots in time (Ulysses, Cluster, ISS-Solaces). However, as the needs evolve and the scientists involved in new missions require to plot multi-variable data, heat maps stacks interactive synchronization and axis variable selection among other improvements. The new Heliophysics archives (such as Solar Orbiter) and the evolution of existing ones (Cluster) intend to address these new challenges. This paper provides an overview of the different approaches for visualizing time-series followed within the ESA Heliophysics Archives and their foreseen evolution.

Spatial Analysis of China Province-level Perinatal Mortality

PubMed Central

XIANG, Kun; SONG, Deyong

2016-01-01

Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors. Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors. Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions. PMID:27398334

Analysis of heart rate variability signal in meditation using second-order difference plot

NASA Astrophysics Data System (ADS)

Goswami, Damodar Prasad; Tibarewala, Dewaki Nandan; Bhattacharya, Dilip Kumar

2011-06-01

In this article, the heart rate variability signal taken from subjects practising different types of meditations have been investigated to find the underlying similarity among them and how they differ from the non-meditative condition. Four different groups of subjects having different meditation techniques are involved. The data have been obtained from the Physionet and also collected with our own ECG machine. For data analysis, the second order difference plot is applied. Each of the plots obtained from the second order differences form a single cluster which is nearly elliptical in shape except for some outliers. In meditation, the axis of the elliptical cluster rotates anticlockwise from the cluster formed from the premeditation data, although the amount of rotation is not of the same extent in every case. This form study reveals definite and specific changes in the heart rate variability of the subjects during meditation. All the four groups of subjects followed different procedures but surprisingly the resulting physiological effect is the same to some extent. It indicates that there is some commonness among all the meditative techniques in spite of their apparent dissimilarity and it may be hoped that each of them leads to the same result as preached by the masters of meditation. The study shows that meditative state has a completely different physiology and that it can be achieved by any meditation technique we have observed. Possible use of this tool in clinical setting such as in stress management and in the treatment of hypertension is also mentioned.

Side scatter versus CD45 flow cytometric plot can distinguish acute leukaemia subtypes.

PubMed

Saksena, Annapurna; Gautam, Parul; Desai, Parth; Gupta, Naresh; Dubey, A P; Singh, Tejinder

2016-05-01

Flow cytometry is an important tool to diagnose acute leukaemia. Attempts are being made to find the minimal number of antibodies for correctly diagnosing acute leukaemia subtypes. The present study was designed to evaluate the analysis of side scatter (SSC) versus CD45 flow dot plot to distinguish acute myeloid leukaemia (AML) from acute lymphoblastic leukaemia (ALL), with minimal immunological markers. One hundred consecutive cases of acute leukaemia were evaluated for blast cluster on SSC versus CD45 plots. The parameters studied included visual shape, CD45 and side scatter expression, continuity with residual granulocytes/lymphocytes/monocytes and ratio of maximum width to maximum height (w/h). The final diagnosis of ALL and AML and their subtypes was made by morphology, cytochemistry and immunophenotyping. Two sample Wilcoxon rank-sum (Mann Whitney) test and Kruskal-Wallis equality-of-populations rank tests were applied to elucidate the significance of the above ratios of blast cluster for diagnosis of ALL, AML and their subtypes. Receiver operating characteristic (ROC) curves were generated and the optimal cut-offs of the w/h ratio to distinguish between ALL and AML determined. Of the 100 cases, 57 of ALL and 43 cases of AML were diagnosed. The median w/h ratio of blast population was 3.8 for ALL and 1 for AML (P<0.001). ROC had area under curve of 0.9772.The optimal cut-off of the w/h ratio for distinction of ALL from AML was found to be 1.6. Our findings suggest that if w/h ratio on SSC versus CD45 plot is less than 1.6, AML may be considered, and if it is more than 1.6, ALL may be diagnosed. Using morphometric analysis of the blast cluster on SSC versus CD45, it was possible to distinguish between ALL and AML, and their subtypes.

Classification and ordination of understory vegetation using multivariate techniques in the Pinus wallichiana forests of Swat Valley, northern Pakistan

NASA Astrophysics Data System (ADS)

Rahman, Inayat Ur; Khan, Nasrullah; Ali, Kishwar

2017-04-01

An understory vegetation survey of the Pinus wallichiana-dominated temperate forests of Swat District was carried out to inspect the structure, composition and ecological associations of the forest vegetation. A quadrat method of sampling was used to record the floristic and phytosociological data necessary for the analysis using 300 quadrats of 10 × 10 m each. Some vegetation parameters viz. frequency and density for trees (overstory vegetation) as well as for the understory vegetation were recorded. The results revealed that in total, 92 species belonging to 77 different genera and 45 families existed in the area. The largest families were Asteraceae, Rosaceae and Lamiaceae with 12, ten and nine species, respectively. Ward's agglomerative cluster analysis for tree species resulted in three floristically and ecologically distinct community types along different topographic and soil variables. Importance value indices (IVI) were also calculated for understory vegetation and were subjected to ordination techniques, i.e. canonical correspondence analysis (CCA) and detrended correspondence analysis (DCA). DCA bi-plots for stands show that most of the stands were scattered around the centre of the DCA bi-plot, identified by two slightly scattered clusters. DCA for species bi-plot clearly identified three clusters of species revealing three types of understory communities in the study area. Results of the CCA were somewhat different from the DCA showing the impact of environmental variables on the understory species. CCA results reveal that three environmental variables, i.e. altitude, slope and P (mg/kg), have a strong influence on distribution of stands and species. Impact of tree species on the understory vegetation was also tested by CCA which showed that four tree species, i.e. P. wallichiana A.B. Jackson, Juglans regia Linn., Quercus dilatata Lindl. ex Royle and Cedrus deodara (Roxb. ex Lamb.) G. Don, have strong influences on associated understory vegetation. It is therefore concluded that Swat District has various microclimatic zones with suitable environmental variables to support distinct flora.

Identification of subsurface microorganisms at Yucca Mountain; Second quarterly report, October 1, 1993--December 31, 1993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stetzenbach, L.D.

1993-12-31

The primary effort of this past quarter was to develop a procedure where accumulated data files could be evaluated to determine the naming consistency and inter-relationships of the various species which have been identified by the Microbial Identification System (MIDI) system. This involved a series of steps, including the clustering of similarly named organisms in a dendrogram format to determine how closely similarly named isolates are related. The experience of other researchers using the MIDI system has shown that clusters which are joined at a Euclidian distance of 10 or less belong to the same species. Strains which are verymore » similar cluster at less than 6 Euclidian units and clusters below two units have nearly identical fatty acid patterns. When the dendrograms derived from the springs were scrutinized, some organisms were found which did not match the pattern of their named group. Then a decision was made whether to rename the isolates and exclude them from the group or redefine the group. This decision was assisted by plotting the principal components derived from an analysis of the fatty acid composition of members of the genus. Each species can be examined by the same procedure to determine group homogeneity. In these 2-dimensional plots members of the same species are roughly bounded by a box of 100 squared units while closely related strains are grouped more tightly together. The 2-dimensional plot of isolates of Micrococcus luteus demonstrates the presence of three identifiable sub-species.« less

Robust statistical methods for hit selection in RNA interference high-throughput screening experiments.

PubMed

Zhang, Xiaohua Douglas; Yang, Xiting Cindy; Chung, Namjin; Gates, Adam; Stec, Erica; Kunapuli, Priya; Holder, Dan J; Ferrer, Marc; Espeseth, Amy S

2006-04-01

RNA interference (RNAi) high-throughput screening (HTS) experiments carried out using large (>5000 short interfering [si]RNA) libraries generate a huge amount of data. In order to use these data to identify the most effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods. To address the questions in hit selection of RNAi HTS, we proposed a quartile-based method which is robust to outliers, true hits and nonsymmetrical data. We compared it with the more traditional tests, mean +/- k standard deviation (SD) and median +/- 3 median of absolute deviation (MAD). The results suggested that the quartile-based method selected more hits than mean +/- k SD under the same preset error rate. The number of hits selected by median +/- k MAD was close to that by the quartile-based method. Further analysis suggested that the quartile-based method had the greatest power in detecting true hits, especially weak or moderate true hits. Our investigation also suggested that platewise analysis (determining effective siRNAs on a plate-by-plate basis) can adjust for systematic errors in different plates, while an experimentwise analysis, in which effective siRNAs are identified in an analysis of the entire experiment, cannot. However, experimentwise analysis may detect a cluster of true positive hits placed together in one or several plates, while platewise analysis may not. To display hit selection results, we designed a specific figure called a plate-well series plot. We thus suggest the following strategy for hit selection in RNAi HTS experiments. First, choose the quartile-based method, or median +/- k MAD, for identifying effective siRNAs. Second, perform the chosen method experimentwise on transformed/normalized data, such as percentage inhibition, to check the possibility of hit clusters. If a cluster of selected hits are observed, repeat the analysis based on untransformed data to determine whether the cluster is due to an artifact in the data. If no clusters of hits are observed, select hits by performing platewise analysis on transformed data. Third, adopt the plate-well series plot to visualize both the data and the hit selection results, as well as to check for artifacts.

CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets

PubMed Central

Nowicka, Malgorzata; Krieg, Carsten; Weber, Lukas M.; Hartmann, Felix J.; Guglietta, Silvia; Becher, Burkhard; Levesque, Mitchell P.; Robinson, Mark D.

2017-01-01

High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals). PMID:28663787

Cluster Analysis and Gaussian Mixture Estimation of Correlated Time-Series by Means of Multi-dimensional Scaling

NASA Astrophysics Data System (ADS)

Ibuki, Takero; Suzuki, Sei; Inoue, Jun-ichi

We investigate cross-correlations between typical Japanese stocks collected through Yahoo!Japan website ( http://finance.yahoo.co.jp/ ). By making use of multi-dimensional scaling (MDS) for the cross-correlation matrices, we draw two-dimensional scattered plots in which each point corresponds to each stock. To make a clustering for these data plots, we utilize the mixture of Gaussians to fit the data set to several Gaussian densities. By minimizing the so-called Akaike Information Criterion (AIC) with respect to parameters in the mixture, we attempt to specify the best possible mixture of Gaussians. It might be naturally assumed that all the two-dimensional data points of stocks shrink into a single small region when some economic crisis takes place. The justification of this assumption is numerically checked for the empirical Japanese stock data, for instance, those around 11 March 2011.

Auger parameter and Wagner plot studies of small copper clusters

NASA Astrophysics Data System (ADS)

Moretti, Giuliano; Palma, Amedeo; Paparazzo, Ernesto; Satta, Mauro

2016-04-01

We discuss application of the Auger parameter and Wagner plot concepts to the study of small copper clusters deposited on various supports such as C(graphite), SiO2 and Al2O3. We demonstrate that the cluster size and the electronic properties of the support influence the shifts of both the binding energy of the Cu 2p3/2 transition and the kinetic energy of the Cu L3M45M45; 1G Auger transition. We find that the Cu L3M45M45; 1G-2p3/2 Auger parameter and Wagner plot allow one to single out and measure both initial- and final-state effects with a detail which is superior to that achieved in photoemission studies.

Soil phosphorus heterogeneity promotes tree species diversity and phylogenetic clustering in a tropical seasonal rainforest.

PubMed

Xu, Wumei; Ci, Xiuqin; Song, Caiyun; He, Tianhua; Zhang, Wenfu; Li, Qiaoming; Li, Jie

2016-12-01

The niche theory predicts that environmental heterogeneity and species diversity are positively correlated in tropical forests, whereas the neutral theory suggests that stochastic processes are more important in determining species diversity. This study sought to investigate the effects of soil nutrient (nitrogen and phosphorus) heterogeneity on tree species diversity in the Xishuangbanna tropical seasonal rainforest in southwestern China. Thirty-nine plots of 400 m 2 (20 × 20 m) were randomly located in the Xishuangbanna tropical seasonal rainforest. Within each plot, soil nutrient (nitrogen and phosphorus) availability and heterogeneity, tree species diversity, and community phylogenetic structure were measured. Soil phosphorus heterogeneity and tree species diversity in each plot were positively correlated, while phosphorus availability and tree species diversity were not. The trees in plots with low soil phosphorus heterogeneity were phylogenetically overdispersed, while the phylogenetic structure of trees within the plots became clustered as heterogeneity increased. Neither nitrogen availability nor its heterogeneity was correlated to tree species diversity or the phylogenetic structure of trees within the plots. The interspecific competition in the forest plots with low soil phosphorus heterogeneity could lead to an overdispersed community. However, as heterogeneity increase, more closely related species may be able to coexist together and lead to a clustered community. Our results indicate that soil phosphorus heterogeneity significantly affects tree diversity in the Xishuangbanna tropical seasonal rainforest, suggesting that deterministic processes are dominant in this tropical forest assembly.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Chemometrics-based Approach in Analysis of Arnicae flos

PubMed Central

Zheleva-Dimitrova, Dimitrina Zh.; Balabanova, Vessela; Gevrenova, Reneta; Doichinova, Irini; Vitkova, Antonina

2015-01-01

Introduction: Arnica montana flowers have a long history as herbal medicines for external use on injuries and rheumatic complaints. Objective: To investigate Arnicae flos of cultivated accessions from Bulgaria, Poland, Germany, Finland, and Pharmacy store for phenolic derivatives and sesquiterpene lactones (STLs). Materials and Methods: Samples of Arnica from nine origins were prepared by ultrasound-assisted extraction with 80% methanol for phenolic compounds analysis. Subsequent reverse-phase high-performance liquid chromatography (HPLC) separation of the analytes was performed using gradient elution and ultraviolet detection at 280 and 310 nm (phenolic acids), and 360 nm (flavonoids). Total STLs were determined in chloroform extracts by solid-phase extraction-HPLC at 225 nm. The HPLC generated chromatographic data were analyzed using principal component analysis (PCA) and hierarchical clustering (HC). Results: The highest total amount of phenolic acids was found in the sample from Botanical Garden at Joensuu University, Finland (2.36 mg/g dw). Astragalin, isoquercitrin, and isorhamnetin 3-glucoside were the main flavonol glycosides being present up to 3.37 mg/g (astragalin). Three well-defined clusters were distinguished by PCA and HC. Cluster C1 comprised of the German and Finnish accessions characterized by the highest content of flavonols. Cluster C2 included the Bulgarian and Polish samples presenting a low content of flavonoids. Cluster C3 consisted only of one sample from a pharmacy store. Conclusion: A validated HPLC method for simultaneous determination of phenolic acids, flavonoid glycosides, and aglycones in A. montana flowers was developed. The PCA loading plot showed that quercetin, kaempferol, and isorhamnetin can be used to distinguish different Arnica accessions. SUMMARY A principal component analysis (PCA) on 13 phenolic compounds and total amount of sesquiterpene lactones in Arnicae flos collection tended to cluster the studied 9 accessions into three main groups. The profiles obtained demonstrated that the samples from Germany and Finland are characterized by greater amounts of phenolic derivatives than the Bulgarian and Polish ones. The PCA loading plot showed that quercetin, kaemferol and isorhamnetin can be used to distinguish different arnica accessions. PMID:27013791

Seismicity map tools for earthquake studies

NASA Astrophysics Data System (ADS)

Boucouvalas, Anthony; Kaskebes, Athanasios; Tselikas, Nikos

2014-05-01

We report on the development of new and online set of tools for use within Google Maps, for earthquake research. We demonstrate this server based and online platform (developped with PHP, Javascript, MySQL) with the new tools using a database system with earthquake data. The platform allows us to carry out statistical and deterministic analysis on earthquake data use of Google Maps and plot various seismicity graphs. The tool box has been extended to draw on the map line segments, multiple straight lines horizontally and vertically as well as multiple circles, including geodesic lines. The application is demonstrated using localized seismic data from the geographic region of Greece as well as other global earthquake data. The application also offers regional segmentation (NxN) which allows the studying earthquake clustering, and earthquake cluster shift within the segments in space. The platform offers many filters such for plotting selected magnitude ranges or time periods. The plotting facility allows statistically based plots such as cumulative earthquake magnitude plots and earthquake magnitude histograms, calculation of 'b' etc. What is novel for the platform is the additional deterministic tools. Using the newly developed horizontal and vertical line and circle tools we have studied the spatial distribution trends of many earthquakes and we here show for the first time the link between Fibonacci Numbers and spatiotemporal location of some earthquakes. The new tools are valuable for examining visualizing trends in earthquake research as it allows calculation of statistics as well as deterministic precursors. We plan to show many new results based on our newly developed platform.

The rainfall plot: its motivation, characteristics and pitfalls.

PubMed

Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

2017-05-18

A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

Network visualization of conformational sampling during molecular dynamics simulation.

PubMed

Ahlstrom, Logan S; Baker, Joseph Lee; Ehrlich, Kent; Campbell, Zachary T; Patel, Sunita; Vorontsov, Ivan I; Tama, Florence; Miyashita, Osamu

2013-11-01

Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone. We compare the results of network visualization against 11 clustering algorithms and principal component conformer plots. Several MD simulations of proteins undergoing different conformational changes demonstrate the effectiveness of networks in reaching functional conclusions. Copyright © 2013 Elsevier Inc. All rights reserved.

Regression analysis on the variation in efficiency frontiers for prevention stage of HIV/AIDS.

PubMed

Kamae, Maki S; Kamae, Isao; Cohen, Joshua T; Neumann, Peter J

2011-01-01

To investigate how the cost effectiveness of preventing HIV/AIDS varies across possible efficiency frontiers (EFs) by taking into account potentially relevant external factors, such as prevention stage, and how the EFs can be characterized using regression analysis given uncertainty of the QALY-cost estimates. We reviewed cost-effectiveness estimates for the prevention and treatment of HIV/AIDS published from 2002-2007 and catalogued in the Tufts Medical Center Cost-Effectiveness Analysis (CEA) Registry. We constructed efficiency frontier (EF) curves by plotting QALYs against costs, using methods used by the Institute for Quality and Efficiency in Health Care (IQWiG) in Germany. We stratified the QALY-cost ratios by prevention stage, country of study, and payer perspective, and estimated EF equations using log and square-root models. A total of 53 QALY-cost ratios were identified for HIV/AIDS in the Tufts CEA Registry. Plotted ratios stratified by prevention stage were visually grouped into a cluster consisting of primary/secondary prevention measures and a cluster consisting of tertiary measures. Correlation coefficients for each cluster were statistically significant. For each cluster, we derived two EF equations - one based on the log model, and one based on the square-root model. Our findings indicate that stratification of HIV/AIDS interventions by prevention stage can yield distinct EFs, and that the correlation and regression analyses are useful for parametrically characterizing EF equations. Our study has certain limitations, such as the small number of included articles and the potential for study populations to be non-representative of countries of interest. Nonetheless, our approach could help develop a deeper appreciation of cost effectiveness beyond the deterministic approach developed by IQWiG.

Evaluating elevated levels of crown dieback among northern white-cedar (Thuja occidentalis L.) trees in Maine and Michigan: a summary of evaluation monitoring

Treesearch

KaDonna Randolph; William A. Bechtold; Randall S. Morin; Stanley J. Zarnoch

2012-01-01

Analysis of crown condition data for the 2006 national technical report of the Forest Health Monitoring (FHM) Program of the Forest Service, U.S. Department of Agriculture, exposed clusters of phase 3 plots (by the Forest Inventory and Analysis [FIA] Program of the Forest Service) with northern white-cedar (Thuja occidentalis L.) crown dieback...

Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

NASA Astrophysics Data System (ADS)

Di Vittorio, Alan V.; Negrón-Juárez, Robinson I.; Higuchi, Niro; Chambers, Jeffrey Q.

2014-03-01

Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies.

A novel unsupervised spike sorting algorithm for intracranial EEG.

PubMed

Yadav, R; Shah, A K; Loeb, J A; Swamy, M N S; Agarwal, R

2011-01-01

This paper presents a novel, unsupervised spike classification algorithm for intracranial EEG. The method combines template matching and principal component analysis (PCA) for building a dynamic patient-specific codebook without a priori knowledge of the spike waveforms. The problem of misclassification due to overlapping classes is resolved by identifying similar classes in the codebook using hierarchical clustering. Cluster quality is visually assessed by projecting inter- and intra-clusters onto a 3D plot. Intracranial EEG from 5 patients was utilized to optimize the algorithm. The resulting codebook retains 82.1% of the detected spikes in non-overlapping and disjoint clusters. Initial results suggest a definite role of this method for both rapid review and quantitation of interictal spikes that could enhance both clinical treatment and research studies on epileptic patients.

Patterns of forest phylogenetic community structure across the United States and their possible forest health implications

Treesearch

Kevin M. Potter; Frank H. Koch

2014-01-01

The analysis of phylogenetic relationships among co-occurring tree species offers insights into the ecological organization of forest communities from an evolutionary perspective and, when employed regionally across thousands of plots, can assist in forest health assessment. Phylogenetic clustering of species, when species are more closely related than expected by...

Positive associations among riparian bird species correspond to elevational changes in plant communities

Treesearch

Deborah M. Finch

1991-01-01

Bird count data were used to characterize patterns of abundance and distribution among 20 bird species occupying streamside habitats of the central Rocky Mountains. Cluster analysis classified bird assemblages from 10 study plots into three elevational zones that varied in bird species diversity. Monotonic declines in total bird densities over the elevational gradient...

A comparison of IQ and memory cluster solutions in moderate and severe pediatric traumatic brain injury.

PubMed

Thaler, Nicholas S; Terranova, Jennifer; Turner, Alisa; Mayfield, Joan; Allen, Daniel N

2015-01-01

Recent studies have examined heterogeneous neuropsychological outcomes in childhood traumatic brain injury (TBI) using cluster analysis. These studies have identified homogeneous subgroups based on tests of IQ, memory, and other cognitive abilities that show some degree of association with specific cognitive, emotional, and behavioral outcomes, and have demonstrated that the clusters derived for children with TBI are different from those observed in normal populations. However, the extent to which these subgroups are stable across abilities has not been examined, and this has significant implications for the generalizability and clinical utility of TBI clusters. The current study addressed this by comparing IQ and memory profiles of 137 children who sustained moderate-to-severe TBI. Cluster analysis of IQ and memory scores indicated that a four-cluster solution was optimal for the IQ scores and a five-cluster solution was optimal for the memory scores. Three clusters on each battery differed primarily by level of performance, while the others had pattern variations. Cross-plotting the clusters across respective IQ and memory test scores indicated that clusters defined by level were generally stable, while clusters defined by pattern differed. Notably, children with slower processing speed exhibited low-average to below-average performance on memory indexes. These results provide some support for the stability of previously identified memory and IQ clusters and provide information about the relationship between IQ and memory in children with TBI.

Short-Term Response of Soil Spiders to Cover-Crop Removal in an Organic Olive Orchard in a Mediterranean Setting

PubMed Central

Cárdenas, Manuel; Castro, Juan; Campos, Mercedes

2012-01-01

This study shows that disturbance caused by cover-crop removal (CCR) in an organic olive orchard affects ground-spider populations. The effect of CCR on various organic olive-orchard plots was assessed by monitoring the abundance and diversity of ground-dwelling spiders. Covered plots in the organic olive orchard were compared with uncovered plots where the covers had been removed mechanically. CCR positively affected the most abundant spider species Zodarion styliferum (Simon) (Araneae: Zodariidae) as well as other species of running spiders belonging to the families Gnaphosidae and Lycosidae. Over time, the two types of plots did not significantly differ in diversity or dominance. Similarly, no differences were detected between the study plots in terms of the distribution of individuals when a cluster-similarity analysis was performed. This lack of difference in diversity might be due to the spatial scale used in the study or climatology. Because of their general effects, CCR profoundly changed the abundance of spiders in the olive orchard, but with no clear impact on spider diversity. PMID:22938154

Large-Scale Genomic Analysis of Codon Usage in Dengue Virus and Evaluation of Its Phylogenetic Dependence

PubMed Central

Lara-Ramírez, Edgar E.; Salazar, Ma Isabel; López-López, María de Jesús; Salas-Benito, Juan Santiago; Sánchez-Varela, Alejandro

2014-01-01

The increasing number of dengue virus (DENV) genome sequences available allows identifying the contributing factors to DENV evolution. In the present study, the codon usage in serotypes 1–4 (DENV1–4) has been explored for 3047 sequenced genomes using different statistics methods. The correlation analysis of total GC content (GC) with GC content at the three nucleotide positions of codons (GC1, GC2, and GC3) as well as the effective number of codons (ENC, ENCp) versus GC3 plots revealed mutational bias and purifying selection pressures as the major forces influencing the codon usage, but with distinct pressure on specific nucleotide position in the codon. The correspondence analysis (CA) and clustering analysis on relative synonymous codon usage (RSCU) within each serotype showed similar clustering patterns to the phylogenetic analysis of nucleotide sequences for DENV1–4. These clustering patterns are strongly related to the virus geographic origin. The phylogenetic dependence analysis also suggests that stabilizing selection acts on the codon usage bias. Our analysis of a large scale reveals new feature on DENV genomic evolution. PMID:25136631

Interactive visual exploration and analysis of origin-destination data

NASA Astrophysics Data System (ADS)

Ding, Linfang; Meng, Liqiu; Yang, Jian; Krisp, Jukka M.

2018-05-01

In this paper, we propose a visual analytics approach for the exploration of spatiotemporal interaction patterns of massive origin-destination data. Firstly, we visually query the movement database for data at certain time windows. Secondly, we conduct interactive clustering to allow the users to select input variables/features (e.g., origins, destinations, distance, and duration) and to adjust clustering parameters (e.g. distance threshold). The agglomerative hierarchical clustering method is applied for the multivariate clustering of the origin-destination data. Thirdly, we design a parallel coordinates plot for visualizing the precomputed clusters and for further exploration of interesting clusters. Finally, we propose a gradient line rendering technique to show the spatial and directional distribution of origin-destination clusters on a map view. We implement the visual analytics approach in a web-based interactive environment and apply it to real-world floating car data from Shanghai. The experiment results show the origin/destination hotspots and their spatial interaction patterns. They also demonstrate the effectiveness of our proposed approach.

Progress in adapting k-NN methods for forest mapping and estimation using the new annual Forest Inventory and Analysis data

Treesearch

Reija Haapanen; Kimmo Lehtinen; Jukka Miettinen; Marvin E. Bauer; Alan R. Ek

2002-01-01

The k-nearest neighbor (k-NN) method has been undergoing development and testing for applications with USDA Forest Service Forest Inventory and Analysis (FIA) data in Minnesota since 1997. Research began using the 1987-1990 FIA inventory of the state, the then standard 10-point cluster plots, and Landsat TM imagery. In the past year, research has moved to examine...

Molecular Eigensolution Symmetry Analysis and Fine Structure

PubMed Central

Harter, William G.; Mitchell, Justin C.

2013-01-01

Spectra of high-symmetry molecules contain fine and superfine level cluster structure related to J-tunneling between hills and valleys on rovibronic energy surfaces (RES). Such graphic visualizations help disentangle multi-level dynamics, selection rules, and state mixing effects including widespread violation of nuclear spin symmetry species. A review of RES analysis compares it to that of potential energy surfaces (PES) used in Born–Oppenheimer approximations. Both take advantage of adiabatic coupling in order to visualize Hamiltonian eigensolutions. RES of symmetric and D2 asymmetric top rank-2-tensor Hamiltonians are compared with Oh spherical top rank-4-tensor fine-structure clusters of 6-fold and 8-fold tunneling multiplets. Then extreme 12-fold and 24-fold multiplets are analyzed by RES plots of higher rank tensor Hamiltonians. Such extreme clustering is rare in fundamental bands but prevalent in hot bands, and analysis of its superfine structure requires more efficient labeling and a more powerful group theory. This is introduced using elementary examples involving two groups of order-6 (C6 and D3~C3v), then applied to families of Oh clusters in SF6 spectra and to extreme clusters. PMID:23344041

Spatial Field Variability Mapping of Rice Crop using Clustering Technique from Space Borne Hyperspectral Data

NASA Astrophysics Data System (ADS)

Moharana, S.; Dutta, S.

2015-12-01

Precision farming refers to field-specific management of an agricultural crop at a spatial scale with an aim to get the highest achievable yield and to achieve this spatial information on field variability is essential. The difficulty in mapping of spatial variability occurring within an agriculture field can be revealed by employing spectral techniques in hyperspectral imagery rather than multispectral imagery. However an advanced algorithm needs to be developed to fully make use of the rich information content in hyperspectral data. In the present study, potential of hyperspectral data acquired from space platform was examined to map the field variation of paddy crop and its species discrimination. This high dimensional data comprising 242 spectral narrow bands with 30m ground resolution Hyperion L1R product acquired for Assam, India (30th Sept and 3rd Oct, 2014) were allowed for necessary pre-processing steps followed by geometric correction using Hyperion L1GST product. Finally an atmospherically corrected and spatially deduced image consisting of 112 band was obtained. By employing an advanced clustering algorithm, 12 different clusters of spectral waveforms of the crop were generated from six paddy fields for each images. The findings showed that, some clusters were well discriminated representing specific rice genotypes and some clusters were mixed treating as a single rice genotype. As vegetation index (VI) is the best indicator of vegetation mapping, three ratio based VI maps were also generated and unsupervised classification was performed for it. The so obtained 12 clusters of paddy crop were mapped spatially to the derived VI maps. From these findings, the existence of heterogeneity was clearly captured in one of the 6 rice plots (rice plot no. 1) while heterogeneity was observed in rest of the 5 rice plots. The degree of heterogeneous was found more in rice plot no.6 as compared to other plots. Subsequently, spatial variability of paddy field was observed in different plot levels in the paddy fields from the two images. However, no such significant variation in rice genotypes at growth level was observed. Hence, the spectral information acquired from space platform can be linearly scaled to map the variation in field levels of rice crop which will be act as an informative system for rice agriculture practice.

Data set for phylogenetic tree and RAMPAGE Ramachandran plot analysis of SODs in Gossypium raimondii and G. arboreum.

PubMed

Wang, Wei; Xia, Minxuan; Chen, Jie; Deng, Fenni; Yuan, Rui; Zhang, Xiaopei; Shen, Fafu

2016-12-01

The data presented in this paper is supporting the research article "Genome-Wide Analysis of Superoxide Dismutase Gene Family in Gossypium raimondii and G. arboreum" [1]. In this data article, we present phylogenetic tree showing dichotomy with two different clusters of SODs inferred by the Bayesian method of MrBayes (version 3.2.4), "Bayesian phylogenetic inference under mixed models" [2], Ramachandran plots of G. raimondii and G. arboreum SODs, the protein sequence used to generate 3D sructure of proteins and the template accession via SWISS-MODEL server, "SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information." [3] and motif sequences of SODs identified by InterProScan (version 4.8) with the Pfam database, "Pfam: the protein families database" [4].

Hail Size Distribution Mapping

NASA Technical Reports Server (NTRS)

2008-01-01

A 3-D weather radar visualization software program was developed and implemented as part of an experimental Launch Pad 39 Hail Monitor System. 3DRadPlot, a radar plotting program, is one of several software modules that form building blocks of the hail data processing and analysis system (the complete software processing system under development). The spatial and temporal mapping algorithms were originally developed through research at the University of Central Florida, funded by NASA s Tropical Rainfall Measurement Mission (TRMM), where the goal was to merge National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD) volume reflectivity data with drop size distribution data acquired from a cluster of raindrop disdrometers. In this current work, we adapted these algorithms to process data from a cluster of hail disdrometers positioned around Launch Pads 39A or 39B, along with the corresponding NWS radar data. Radar data from all NWS NEXRAD sites is archived at the National Climatic Data Center (NCDC). That data can be readily accessed at . 3DRadPlot plots Level III reflectivity data at four scan elevations (this software is available at Open Channel Software, ). By using spatial and temporal interpolation/extrapolation based on hydrometeor fall dynamics, we can merge the hail disdrometer array data coupled with local Weather Surveillance Radar-1988, Doppler (WSR-88D) radial velocity and reflectivity data into a 4-D (3-D space and time) picture of hail size distributions. Hail flux maps can then be generated and used for damage prediction and assessment over specific surfaces corresponding to structures within the disdrometer array volume. Immediately following a hail storm, specific damage areas and degree of damage can be identified for inspection crews.

Comparative analysis of DNA polymorphisms and phylogenetic relationships among Syzygium cumini Skeels based on phenotypic characters and RAPD technique.

PubMed

Singh, Jitendra P; Singh, Ak; Bajpai, Anju; Ahmad, Iffat Zareen

2014-01-01

The Indian black berry (Syzygium cumini Skeels) has a great nutraceutical and medicinal properties. As in other fruit crops, the fruit characteristics are important attributes for differentiation were also determined for different accessions of S. cumini. The fruit weight, length, breadth, length: breadth ratio, pulp weight, pulp content, seed weight and pulp: seed ratio significantly varied in different accessions. Molecular characterization was carried out using PCR based RAPD technique. Out of 80 RAPD primers, only 18 primers produced stable polymorphisms that were used to examine the phylogenetic relationship. A sum of 207 loci were generated out of which 201 loci found polymorphic. The average genetic dissimilarity was 97 per cent among jamun accessions. The phylogenetic relationship was also determined by principal coordinates analysis (PCoA) that explained 46.95 per cent cumulative variance. The two-dimensional PCoA analysis showed grouping of the different accessions that were plotted into four sub-plots, representing clustering of accessions. The UPGMA (r = 0.967) and NJ (r = 0.987) dendrogram constructed based on the dissimilarity matrix revealed a good degree of fit with the cophenetic correlation value. The dendrogram grouped the accessions into three main clusters according to their eco-geographical regions which given useful insight into their phylogenetic relationships.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of Landsat digital data. [mapping of hydrothermally altered volcanic rocks

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Effects of variable-density thinning on understory diversity and heterogeneity in young Douglas-fir forests.

Treesearch

Juliann E. Aukema; Andrew B. Carey

2008-01-01

Nine years after variable-density thinning (VDT) on the Forest Ecosystem Study, we examined low understory vegetation in 60 plots of eight stands (four pairs of VDT and control). We compared native, exotic, ruderal, and nonforest species richness among the stands. We used clustering, ordination, and indicator species analysis to look for distinctive patches of plant...

Using sperm morphometry and multivariate analysis to differentiate species of gray Mazama

PubMed Central

Duarte, José Maurício Barbanti

2016-01-01

There is genetic evidence that the two species of Brazilian gray Mazama, Mazama gouazoubira and Mazama nemorivaga, belong to different genera. This study identified significant differences that separated them into distinct groups, based on characteristics of the spermatozoa and ejaculate of both species. The characteristics that most clearly differentiated between the species were ejaculate colour, white for M. gouazoubira and reddish for M. nemorivaga, and sperm head dimensions. Multivariate analysis of sperm head dimension and format data accurately discriminated three groups for species with total percentage of misclassified of 0.71. The individual analysis, by animal, and the multivariate analysis have also discriminated correctly all five animals (total percentage of misclassified of 13.95%), and the canonical plot has shown three different clusters: Cluster 1, including individuals of M. nemorivaga; Cluster 2, including two individuals of M. gouazoubira; and Cluster 3, including a single individual of M. gouazoubira. The results obtained in this work corroborate the hypothesis of the formation of new genera and species for gray Mazama. Moreover, the easily applied method described herein can be used as an auxiliary tool to identify sibling species of other taxonomic groups. PMID:28018612

A recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure.

PubMed

Liao, Fuyuan; Jan, Yih-Kuen

2012-06-01

This paper presents a recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure. Recurrence is a fundamental property of many dynamical systems, which can be explored in phase spaces constructed from observational time series. A visualization tool of recurrence analysis called recurrence plot (RP) has been proved to be highly effective to detect transitions in the dynamics of the system. However, it was found that delay embedding can produce spurious structures in RPs. Network-based concepts have been applied for the analysis of nonlinear time series recently. We demonstrate that time series with different types of dynamics exhibit distinct global clustering coefficients and distributions of local clustering coefficients and that the global clustering coefficient is robust to the embedding parameters. We applied the approach to study skin blood flow oscillations (BFO) response to loading pressure. The results showed that global clustering coefficients of BFO significantly decreased in response to loading pressure (p<0.01). Moreover, surrogate tests indicated that such a decrease was associated with a loss of nonlinearity of BFO. Our results suggest that the recurrence network approach can practically quantify the nonlinear dynamics of BFO.

Assessment of environmental and occupational exposure to heavy metals in Taranto and other provinces of Southern Italy by means of scalp hair analysis.

PubMed

Buononato, Elena Viola; De Luca, Daniela; Galeandro, Innocenzo Cataldo; Congedo, Maria Luisa; Cavone, Domenica; Intranuovo, Graziana; Guastadisegno, Chiara Monica; Corrado, Vincenzo; Ferri, Giovanni Maria

2016-06-01

The monitoring of heavy metals in industrialized areas to study their association with different occupational and environmental factors is carried out in different ways. In this study, scalp hair analysis was used for the assessment of exposure to these metals in the industrial city of Taranto, characterized by a severe environmental pollution. The highest median values were observed for aluminum, barium, cadmium, lead, mercury, and uranium. Moreover, in the industrial area of Taranto, high levels of barium, cadmium, lead, mercury, nickel, and silver were observed in comparison with other Apulia areas. The risk odds ratios (ORs) for observing values above the 50th percentile were elevated for mercury and fish consumption, uranium and milk consumption, lead and female sex, and aluminum and mineral water consumption. No significant increased risk was observed for occupational activities. In a dendrogram of a cluster analysis, three clusters were observed for the different areas of Taranto (Borgo, San Vito, and Statte). A scree plot and score variables plot underline the presence of two principal components: the first regarding antimony, lead, tin, aluminum and silver; the second regarding mercury and uranium. The observed clusters (Borgo, San Vito, and Statte) showed that lead, antimony, tin, aluminum, and silver were the main component. The highest values above the 50th percentile of these minerals, especially lead, were observed in the Borgo area. The observed metal concentration in the Borgo area is compatible with the presence in Taranto of a military dockyard and a reported increase of lung cancer risk among residents of that area.

imDEV: a graphical user interface to R multivariate analysis tools in Microsoft Excel.

PubMed

Grapov, Dmitry; Newman, John W

2012-09-01

Interactive modules for Data Exploration and Visualization (imDEV) is a Microsoft Excel spreadsheet embedded application providing an integrated environment for the analysis of omics data through a user-friendly interface. Individual modules enables interactive and dynamic analyses of large data by interfacing R's multivariate statistics and highly customizable visualizations with the spreadsheet environment, aiding robust inferences and generating information-rich data visualizations. This tool provides access to multiple comparisons with false discovery correction, hierarchical clustering, principal and independent component analyses, partial least squares regression and discriminant analysis, through an intuitive interface for creating high-quality two- and a three-dimensional visualizations including scatter plot matrices, distribution plots, dendrograms, heat maps, biplots, trellis biplots and correlation networks. Freely available for download at http://sourceforge.net/projects/imdev/. Implemented in R and VBA and supported by Microsoft Excel (2003, 2007 and 2010).

Determining the trophic guilds of fishes and macroinvertebrates in a seagrass food web

USGS Publications Warehouse

Luczkovich, J.J.; Ward, G.P.; Johnson, J.C.; Christian, R.R.; Baird, D.; Neckles, H.; Rizzo, W.M.

2002-01-01

We established trophic guilds of macroinvertebrate and fish taxa using correspondence analysis and a hierarchical clustering strategy for a seagrass food web in winter in the northeastern Gulf of Mexico. To create the diet matrix, we characterized the trophic linkages of macroinvertebrate and fish taxa present in Halodule wrightii seagrass habitat areas within the St. Marks National Wildlife Refuge (Florida) using binary data, combining dietary links obtained from relevant literature for macroinvertebrates with stomach analysis of common fishes collected during January and February of 1994. Heirarchical average-linkage cluster analysis of the 73 taxa of fishes and macroinvertebrates in the diet matrix yielded 14 clusters with diet similarity ??? 0.60. We then used correspondence analysis with three factors to jointly plot the coordinates of the consumers (identified by cluster membership) and of the 33 food sources. Correspondence analysis served as a visualization tool for assigning each taxon to one of eight trophic guilds: herbivores, detritivores, suspension feeders, omnivores, molluscivores, meiobenthos consumers, macrobenthos consumers, and piscivores. These trophic groups, cross-classified with major taxonomic groups, were further used to develop consumer compartments in a network analysis model of carbon flow in this seagrass ecosystem. The method presented here should greatly improve the development of future network models of food webs by providing an objective procedure for aggregating trophic groups.

Q-mode versus R-mode principal component analysis for linear discriminant analysis (LDA)

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2017-05-01

Many literature apply Principal Component Analysis (PCA) as either preliminary visualization or variable con-struction methods or both. Focus of PCA can be on the samples (R-mode PCA) or variables (Q-mode PCA). Traditionally, R-mode PCA has been the usual approach to reduce high-dimensionality data before the application of Linear Discriminant Analysis (LDA), to solve classification problems. Output from PCA composed of two new matrices known as loadings and scores matrices. Each matrix can then be used to produce a plot, i.e. loadings plot aids identification of important variables whereas scores plot presents spatial distribution of samples on new axes that are also known as Principal Components (PCs). Fundamentally, the scores matrix always be the input variables for building classification model. A recent paper uses Q-mode PCA but the focus of analysis was not on the variables but instead on the samples. As a result, the authors have exchanged the use of both loadings and scores plots in which clustering of samples was studied using loadings plot whereas scores plot has been used to identify important manifest variables. Therefore, the aim of this study is to statistically validate the proposed practice. Evaluation is based on performance of external error obtained from LDA models according to number of PCs. On top of that, bootstrapping was also conducted to evaluate the external error of each of the LDA models. Results show that LDA models produced by PCs from R-mode PCA give logical performance and the matched external error are also unbiased whereas the ones produced with Q-mode PCA show the opposites. With that, we concluded that PCs produced from Q-mode is not statistically stable and thus should not be applied to problems of classifying samples, but variables. We hope this paper will provide some insights on the disputable issues.

Impact of leather industries on fluoride dynamics in groundwater around a tannery cluster in South India.

PubMed

Sajil Kumar, P J

2013-03-01

The aim of this study was to investigate the controls of leather industries on fluoride contamination in and around a tannery cluster in Vaniyambadi. Hydrochemical analysis, mineral saturation indices and statistical methods were used to evaluate the intervening factors that controls the contamination processes. Fluoride in groundwater is exceeded the WHO guideline value (1.5 mg/L), in 62 % of the samples, mostly with Na-HCO3 and Na-Cl type of water. Results of the principal component analysis grouped Na, F, HCO3 and NO3 under component 1. This result was in agreement with the cross plot indicating high positive correlation between F and Na (r (2)  = 0.87), HCO3 (r (2)  = 0.84) and NO3 (r (2)  = 0.55). Fluorite (CaF2) and Halite (NaCl) was undersaturated, while calcite (CaCO3) was oversaturated for all the samples. This suggest more dissolution of F-rich minerals under the active supports of Na. Bivariate plots of Na versus Cl and Na + K versus HCO3 showed a combined origin of Na from tannery effluent as well as silicate weathering. Two major clusters, based on the Na, HCO3 and F concentration showed that groundwater is affected by tanneries and silicate weathering. Fluoride concentration in 38 % of samples (n = 5) have significantly affected by the high Na concentration from tanneries.

An empirical, hierarchical typology of tree species assemblages for assessing forest dynamics under global change scenarios

Treesearch

Jennifer K. Costanza; John W. Coulston; David N. Wear

2017-01-01

The composition of tree species occurring in a forest is important and can be affected by global change drivers such as climate change. To inform assessment and projection of global change impacts at broad extents, we used hierarchical cluster analysis and over 120,000 recent forest inventory plots to empirically define forest tree assemblages across the U.S., and...

Aerial Images and Convolutional Neural Network for Cotton Bloom Detection.

PubMed

Xu, Rui; Li, Changying; Paterson, Andrew H; Jiang, Yu; Sun, Shangpeng; Robertson, Jon S

2017-01-01

Monitoring flower development can provide useful information for production management, estimating yield and selecting specific genotypes of crops. The main goal of this study was to develop a methodology to detect and count cotton flowers, or blooms, using color images acquired by an unmanned aerial system. The aerial images were collected from two test fields in 4 days. A convolutional neural network (CNN) was designed and trained to detect cotton blooms in raw images, and their 3D locations were calculated using the dense point cloud constructed from the aerial images with the structure from motion method. The quality of the dense point cloud was analyzed and plots with poor quality were excluded from data analysis. A constrained clustering algorithm was developed to register the same bloom detected from different images based on the 3D location of the bloom. The accuracy and incompleteness of the dense point cloud were analyzed because they affected the accuracy of the 3D location of the blooms and thus the accuracy of the bloom registration result. The constrained clustering algorithm was validated using simulated data, showing good efficiency and accuracy. The bloom count from the proposed method was comparable with the number counted manually with an error of -4 to 3 blooms for the field with a single plant per plot. However, more plots were underestimated in the field with multiple plants per plot due to hidden blooms that were not captured by the aerial images. The proposed methodology provides a high-throughput method to continuously monitor the flowering progress of cotton.

An empirical, hierarchical typology of tree species assemblages for assessing forest dynamics under global change scenarios

PubMed Central

Coulston, John W.; Wear, David N.

2017-01-01

The composition of tree species occurring in a forest is important and can be affected by global change drivers such as climate change. To inform assessment and projection of global change impacts at broad extents, we used hierarchical cluster analysis and over 120,000 recent forest inventory plots to empirically define forest tree assemblages across the U.S., and identified the indicator and dominant species associated with each. Cluster typologies in two levels of a hierarchy of forest assemblages, with 29 and 147 groups respectively, were supported by diagnostic criteria. Groups in these two levels of the hierarchy were labeled based on the top indicator species in each, and ranged widely in size. For example, in the 29-cluster typology, the sugar maple-red maple assemblage contained the largest number of plots (30,068), while the butternut-sweet birch and sourwood-scarlet oak assemblages were both smallest (6 plots each). We provide a case-study demonstration of the utility of the typology for informing forest climate change impact assessment. For five assemblages in the 29-cluster typology, we used existing projections of changes in importance value (IV) for the dominant species under one low and one high climate change scenario to assess impacts to the assemblages. Results ranged widely for each scenario by the end of the century, with each showing an average decrease in IV for dominant species in some assemblages, including the balsam fir-quaking aspen assemblage, and an average increase for others, like the green ash-American elm assemblage. Future work should assess adaptive capacity of these forest assemblages and investigate local population- and community-level dynamics in places where dominant species may be impacted. This typology will be ideal for monitoring, assessing, and projecting changes to forest communities within the emerging framework of macrosystems ecology, which emphasizes hierarchies and broad extents. PMID:28877258

Analysis of precipitation data in Bangladesh through hierarchical clustering and multidimensional scaling

NASA Astrophysics Data System (ADS)

Rahman, Md. Habibur; Matin, M. A.; Salma, Umma

2017-12-01

The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.

Building for the future: influence of housing on intelligence quotients of children in an urban slum.

PubMed

Choudhary, R; Sharma, Abhinav; Agarwal, Kishore S; Kumar, Amod; Sreenivas, V; Puliyel, Jacob M

2002-12-01

Interventions on behalf of the marginalized in society can assume many formats. In an urban slum the Government of Delhi built one-room houses for some of the residents in what is termed a 'plot area'. Not all residents could be accommodated in the project and the remainder continued to live next door in shanty houses of the slum. Nineteen years later, young children who had migrated with their parents, have grown up and have children of their own. We looked at the development of the children living in the two types of accommodation. A total of 373 children were studied. All children (n = 200) between the ages of 3.5 and 5.5 years in a cluster of five residential blocks in the plot area were studied. As a control, children in two large clusters of shanty houses (n = 173) were also studied. For development assessment the Central Institute of Education (CIE) Test was performed. This is an Indian adaptation of the Standford-Binet Test. Multiple regression analysis was utilized to determine the factors that influenced IQ most. The mean IQ of the children in the plot area was 92.5 (s.d. 13.38) and in the shanty houses 89.5 (s.d. 12.9) (p = 0.05). Analysis showed that the most significant factors affecting IQ were malnutrition in the first 6 months of life and attendance of the child at pre-school. For nutrition in the first 6 months, there was no difference between the groups. For attendance at pre-school, 110 of 200 in the plot area and 47 of 173 in the shanty houses were attending pre-school (p < 0.01). We find that children living in the permanent houses had a significantly better IQ than those in shanty houses. A review of the literature did not reveal a comparable study.

Combination of multivariate curve resolution and multivariate classification techniques for comprehensive high-performance liquid chromatography-diode array absorbance detection fingerprints analysis of Salvia reuterana extracts.

PubMed

Hakimzadeh, Neda; Parastar, Hadi; Fattahi, Mohammad

2014-01-24

In this study, multivariate curve resolution (MCR) and multivariate classification methods are proposed to develop a new chemometric strategy for comprehensive analysis of high-performance liquid chromatography-diode array absorbance detection (HPLC-DAD) fingerprints of sixty Salvia reuterana samples from five different geographical regions. Different chromatographic problems occurred during HPLC-DAD analysis of S. reuterana samples, such as baseline/background contribution and noise, low signal-to-noise ratio (S/N), asymmetric peaks, elution time shifts, and peak overlap are handled using the proposed strategy. In this way, chromatographic fingerprints of sixty samples are properly segmented to ten common chromatographic regions using local rank analysis and then, the corresponding segments are column-wise augmented for subsequent MCR analysis. Extended multivariate curve resolution-alternating least squares (MCR-ALS) is used to obtain pure component profiles in each segment. In general, thirty-one chemical components were resolved using MCR-ALS in sixty S. reuterana samples and the lack of fit (LOF) values of MCR-ALS models were below 10.0% in all cases. Pure spectral profiles are considered for identification of chemical components by comparing their resolved spectra with the standard ones and twenty-four components out of thirty-one components were identified. Additionally, pure elution profiles are used to obtain relative concentrations of chemical components in different samples for multivariate classification analysis by principal component analysis (PCA) and k-nearest neighbors (kNN). Inspection of the PCA score plot (explaining 76.1% of variance accounted for three PCs) showed that S. reuterana samples belong to four clusters. The degree of class separation (DCS) which quantifies the distance separating clusters in relation to the scatter within each cluster is calculated for four clusters and it was in the range of 1.6-5.8. These results are then confirmed by kNN. In addition, according to the PCA loading plot and kNN dendrogram of thirty-one variables, five chemical constituents of luteolin-7-o-glucoside, salvianolic acid D, rosmarinic acid, lithospermic acid and trijuganone A are identified as the most important variables (i.e., chemical markers) for clusters discrimination. Finally, the effect of different chemical markers on samples differentiation is investigated using counter-propagation artificial neural network (CP-ANN) method. It is concluded that the proposed strategy can be successfully applied for comprehensive analysis of chromatographic fingerprints of complex natural samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Non-targeted analyses of animal plasma: betaine and choline represent the nutritional and metabolic status.

PubMed

Katayama, K; Sato, T; Arai, T; Amao, H; Ohta, Y; Ozawa, T; Kenyon, P R; Hickson, R E; Tazaki, H

2013-02-01

Simple liquid chromatography-mass spectrometry (LC-MS) was applied to non-targeted metabolic analyses to discover new metabolic markers in animal plasma. Principle component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) were used to analyse LC-MS multivariate data. PCA clearly generated two separate clusters for artificially induced diabetic mice and healthy control mice. PLS-DA of time-course changes in plasma metabolites of chicks after feeding generated three clusters (pre- and immediately after feeding, 0.5-3 h after feeding and 4 h after feeding). Two separate clusters were also generated for plasma metabolites of pregnant Angus heifers with differing live-weight change profiles (gaining or losing). The accompanying PLS-DA loading plot detailed the metabolites that contribute the most to the cluster separation. In each case, the same highly hydrophilic metabolite was strongly correlated to the group separation. The metabolite was identified as betaine by LC-MS/MS. This result indicates that betaine and its metabolic precursor, choline, may be useful biomarkers to evaluate the nutritional and metabolic status of animals. © 2011 Blackwell Verlag GmbH.

Combinations of elevated tissue miRNA-17-92 cluster expression and serum prostate-specific antigen as potential diagnostic biomarkers for prostate cancer.

PubMed

Feng, Sujuan; Qian, Xiaosong; Li, Han; Zhang, Xiaodong

2017-12-01

The aim of the present study was to investigate the effectiveness of the miR-17-92 cluster as a disease progression marker in prostate cancer (PCa). Reverse transcription-quantitative polymerase chain reaction analysis was used to detect the microRNA (miR)-17-92 cluster expression levels in tissues from patients with PCa or benign prostatic hyperplasia (BPH), in addition to in PCa and BPH cell lines. Spearman correlation was used for comparison and estimation of correlations between miRNA expression levels and clinicopathological characteristics such as the Gleason score and prostate-specific antigen (PSA). Receiver operating curve (ROC) analysis was performed for evaluation of specificity and sensitivity of miR-17-92 cluster expression levels for discriminating patients with PCa from patients with BPH. Kaplan-Meier analysis was plotted to investigate the predictive potential of miR-17-92 cluster for PCa biochemical recurrence. Expression of the majority of miRNAs in the miR-17-92 cluster was identified to be significantly increased in PCa tissues and cell lines. Bivariate correlation analysis indicated that the high expression of unregulated miRNAs was positively correlated with Gleason grade, but had no significant association with PSA. ROC curves demonstrated that high expression of miR-17-92 cluster predicted a higher diagnostic accuracy compared with PSA. Improved discriminating quotients were observed when combinations of unregulated miRNAs with PSA were used. Survival analysis confirmed a high combined miRNA score of miR-17-92 cluster was associated with shorter biochemical recurrence interval. miR-17-92 cluster could be a potential diagnostic and prognostic biomarker for PCa, and the combination of the miR-17-92 cluster and serum PSA may enhance the accuracy for diagnosis of PCa.

Time-Hierarchical Clustering and Visualization of Weather Forecast Ensembles.

PubMed

Ferstl, Florian; Kanzler, Mathias; Rautenhaus, Marc; Westermann, Rudiger

2017-01-01

We propose a new approach for analyzing the temporal growth of the uncertainty in ensembles of weather forecasts which are started from perturbed but similar initial conditions. As an alternative to traditional approaches in meteorology, which use juxtaposition and animation of spaghetti plots of iso-contours, we make use of contour clustering and provide means to encode forecast dynamics and spread in one single visualization. Based on a given ensemble clustering in a specified time window, we merge clusters in time-reversed order to indicate when and where forecast trajectories start to diverge. We present and compare different visualizations of the resulting time-hierarchical grouping, including space-time surfaces built by connecting cluster representatives over time, and stacked contour variability plots. We demonstrate the effectiveness of our visual encodings with forecast examples of the European Centre for Medium-Range Weather Forecasts, which convey the evolution of specific features in the data as well as the temporally increasing spatial variability.

Determining the trophic guilds of fishes and macroinvertebrates in a seagrass food web

USGS Publications Warehouse

Luczkovich, J.J.; Ward, G.P.; Johnson, J.C.; Christian, R.R.; Baird, D.; Neckles, H.; Rizzo, W.M.

2002-01-01

We established trophic guilds of macroinvertebrate and fish taxa using correspondence analysis and a hierarchical clustering strategy for a seagrass food web in winter in the northeastern Gulf of Mexico. To create the diet matrix, we characterized the trophic linkages of macroinvertebrate and fish taxa. present in Hatodule wrightii seagrass habitat areas within the St. Marks National Wildlife Refuge (Florida) using binary data, combining dietary links obtained from relevant literature for macroinvertebrates with stomach analysis of common fishes collected during January and February of 1994. Heirarchical average-linkage cluster analysis of the 73 taxa of fishes and macroinvertebrates in the diet matrix yielded 14 clusters with diet similarity greater than or equal to 0.60. We then used correspondence analysis with three factors to jointly plot the coordinates of the consumers (identified by cluster membership) and of the 33 food sources. Correspondence analysis served as a visualization tool for assigning each taxon to one of eight trophic guilds: herbivores, detritivores, suspension feeders, omnivores, molluscivores, meiobenthos consumers, macrobenthos consumers, and piscivores. These trophic groups, cross-classified with major taxonomic groups, were further used to develop consumer compartments in a network analysis model of carbon flow in this seagrass ecosystem. The method presented here should greatly improve the development of future network models of food webs by providing an objective procedure for aggregating trophic groups.

UNCLES: method for the identification of genes differentially consistently co-expressed in a specific subset of datasets.

PubMed

Abu-Jamous, Basel; Fa, Rui; Roberts, David J; Nandi, Asoke K

2015-06-04

Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.

Toward structure prediction of cyclic peptides.

PubMed

Yu, Hongtao; Lin, Yu-Shan

2015-02-14

Cyclic peptides are a promising class of molecules that can be used to target specific protein-protein interactions. A computational method to accurately predict their structures would substantially advance the development of cyclic peptides as modulators of protein-protein interactions. Here, we develop a computational method that integrates bias-exchange metadynamics simulations, a Boltzmann reweighting scheme, dihedral principal component analysis and a modified density peak-based cluster analysis to provide a converged structural description for cyclic peptides. Using this method, we evaluate the performance of a number of popular protein force fields on a model cyclic peptide. All the tested force fields seem to over-stabilize the α-helix and PPII/β regions in the Ramachandran plot, commonly populated by linear peptides and proteins. Our findings suggest that re-parameterization of a force field that well describes the full Ramachandran plot is necessary to accurately model cyclic peptides.

GATA: A graphic alignment tool for comparative sequenceanalysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nix, David A.; Eisen, Michael B.

2005-01-01

Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved sequence elements are collinear. This assumption appears valid when comparing orthologous protein coding sequences. Functional constraints on proteins provide strong selective pressure against sequence inversions, and minimize sequence duplications and feature shuffling. For non-coding sequences this collinearity assumption is often invalid. For example, enhancers contain clusters of transcription factor binding sites that change in number, orientation, and spacing during evolution yet the enhancer retains its activity. Dotplot analysis is often used to estimate non-coding sequence relatedness. Yet dotmore » plots do not actually align sequences and thus cannot account well for base insertions or deletions. Moreover, they lack an adequate statistical framework for comparing sequence relatedness and are limited to pairwise comparisons. Lastly, dot plots and dynamic programming text outputs fail to provide an intuitive means for visualizing DNA alignments.« less

Cluster Analysis of Acute Care Use Yields Insights for Tailored Pediatric Asthma Interventions.

PubMed

Abir, Mahshid; Truchil, Aaron; Wiest, Dawn; Nelson, Daniel B; Goldstick, Jason E; Koegel, Paul; Lozon, Marie M; Choi, Hwajung; Brenner, Jeffrey

2017-09-01

We undertake this study to understand patterns of pediatric asthma-related acute care use to inform interventions aimed at reducing potentially avoidable hospitalizations. Hospital claims data from 3 Camden city facilities for 2010 to 2014 were used to perform cluster analysis classifying patients aged 0 to 17 years according to their asthma-related hospital use. Clusters were based on 2 variables: asthma-related ED visits and hospitalizations. Demographics and a number of sociobehavioral and use characteristics were compared across clusters. Children who met the criteria (3,170) were included in the analysis. An examination of a scree plot showing the decline in within-cluster heterogeneity as the number of clusters increased confirmed that clusters of pediatric asthma patients according to hospital use exist in the data. Five clusters of patients with distinct asthma-related acute care use patterns were observed. Cluster 1 (62% of patients) showed the lowest rates of acute care use. These patients were least likely to have a mental health-related diagnosis, were less likely to have visited multiple facilities, and had no hospitalizations for asthma. Cluster 2 (19% of patients) had a low number of asthma ED visits and onetime hospitalization. Cluster 3 (11% of patients) had a high number of ED visits and low hospitalization rates, and the highest rates of multiple facility use. Cluster 4 (7% of patients) had moderate ED use for both asthma and other illnesses, and high rates of asthma hospitalizations; nearly one quarter received care at all facilities, and 1 in 10 had a mental health diagnosis. Cluster 5 (1% of patients) had extreme rates of acute care use. Differences observed between groups across multiple sociobehavioral factors suggest these clusters may represent children who differ along multiple dimensions, in addition to patterns of service use, with implications for tailored interventions. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Mapping Arctic plant functional type distributions in the Barrow Environmental Observatory using WorldView-2 and LiDAR datasets

DOE PAGES

Langford, Zachary; Kumar, Jitendra; Hoffman, Forrest; ...

2016-09-06

Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landscape in and around the Barrow Environmental Observatory (BEO), a 3021-hectare research reserve located at the northern edge of the Alaskan Arctic Coastal Plain. Vegetation surveys were conducted during the growing season (June August) of 2012 from 48 1 m 1 m plots in the study region for estimating the percent cover ofmore » PFTs (i.e., sedges, grasses, forbs, shrubs, lichens and mosses). Statistical relationships were developed between spectral and topographic remote sensing characteristics and PFT fractions at the vegetation plots from field surveys. These derived relationships were employed to statistically upscale PFT fractions for our study region of 586 hectares at 0.25-m resolution around the sampling areas within the BEO, which was bounded by the LiDAR footprint. We employed an unsupervised clustering for stratification of this polygonal tundra landscape and used the clusters for segregating the field data for our upscaling algorithm over our study region, which was an inverse distance weighted (IDW) interpolation. We describe two versions of PFT distribution maps upscaled by IDW from WorldView-2 imagery and LiDAR: (1) a version computed from a single image in the middle of the growing season; and (2) a version computed from multiple images through the growing season. This approach allowed us to quantify the value of phenology for improving PFT distribution estimates. We also evaluated the representativeness of the field surveys by measuring the Euclidean distance between every pixel. This guided the ground-truthing campaign in late July of 2014 for addressing uncertainty based on representativeness analysis by selecting 24 1 m 1 m plots that were well and poorly represented. Ground-truthing indicated that including phenology had a better accuracy (R 2=0.75, RMSE=9.94) than the single image upscaling (R 2=0.63 , RMSE=12.05) predicted from IDW. We also updated our upscaling approach to include the 24 ground-truthing plots, and a second ground-truthing campaign in late August of 2014 indicated a better accuracy for the phenology model (R 2=0.61 , RMSE=13.78 ) than only using the original 48 plots for the phenology model (R 2=0.23 , RMSE=17.49). After all, we believe that the cluster-based IDW upscaling approach and the representativeness analysis offer new insights for upscaling high-resolution data in fragmented landscapes. This analysis and approach provides PFT maps needed to inform land surface models in Arctic ecosystems.« less

R-CMap-An open-source software for concept mapping.

PubMed

Bar, Haim; Mentch, Lucas

2017-02-01

Planning and evaluating projects often involves input from many stakeholders. Fusing and organizing many different ideas, opinions, and interpretations into a coherent and acceptable plan or project evaluation is challenging. This is especially true when seeking contributions from a large number of participants, especially when not all can participate in group discussions, or when some prefer to contribute their perspectives anonymously. One of the major breakthroughs in the area of evaluation and program planning has been the use of graphical tools to represent the brainstorming process. This provides a quantitative framework for organizing ideas and general concepts into simple-to-interpret graphs. We developed a new, open-source concept mapping software called R-CMap, which is implemented in R. This software provides a graphical user interface to guide users through the analytical process of concept mapping. The R-CMap software allows users to generate a variety of plots, including cluster maps, point rating and cluster rating maps, as well as pattern matching and go-zone plots. Additionally, R-CMap is capable of generating detailed reports that contain useful statistical summaries of the data. The plots and reports can be embedded in Microsoft Office tools such as Word and PowerPoint, where users may manually adjust various plot and table features to achieve the best visual results in their presentations and official reports. The graphical user interface of R-CMap allows users to define cluster names, change the number of clusters, select rating variables for relevant plots, and importantly, select subsets of respondents by demographic criteria. The latter is particularly useful to project managers in order to identify different patterns of preferences by subpopulations. R-CMap is user-friendly, and does not require any programming experience. However, proficient R users can add to its functionality by directly accessing built-in functions in R and sharing new features with the concept mapping community. Copyright © 2016 Elsevier Ltd. All rights reserved.

Isocratic and gradient impedance plot analysis and comparison of some recently introduced large size core-shell and fully porous particles.

PubMed

Vanderheyden, Yoachim; Cabooter, Deirdre; Desmet, Gert; Broeckhoven, Ken

2013-10-18

The intrinsic kinetic performance of three recently commercialized large size (≥4μm) core-shell particles packed in columns with different lengths has been measured and compared with that of standard fully porous particles of similar and smaller size (5 and 3.5μm, respectively). The kinetic performance is compared in both absolute (plot of t0 versus the plate count N or the peak capacity np for isocratic and gradient elution, respectively) and dimensionless units. The latter is realized by switching to so-called impedance plots, a format which has been previously introduced (as a plot of t0/N(2) or E0 versus Nopt/N) and has in the present study been extended from isocratic to gradient elution (where the impedance plot corresponds to a plot of t0/np(4) versus np,opt(2)/np(2)). Both the isocratic and gradient impedance plot yielded a very similar picture: the clustered impedance plot curves divide into two distinct groups, one for the core-shell particles (lowest values, i.e. best performance) and one for the fully porous particles (highest values), confirming the clear intrinsic kinetic advantage of core-shell particles. If used around their optimal flow rate, the core-shell particles displayed a minimal separation impedance that is about 40% lower than the fully porous particles. Even larger gains in separation speed can be achieved in the C-term regime. Copyright © 2013 Elsevier B.V. All rights reserved.

1H-NMR and UPLC-MS metabolomics: Functional tools for exploring chemotypic variation in Sceletium tortuosum from two provinces in South Africa.

PubMed

Zhao, Jianping; Khan, Ikhlas A; Combrinck, Sandra; Sandasi, Maxleene; Chen, Weiyang; Viljoen, Alvaro M

2018-05-17

Sceletium tortuosum (Aizoaceae) is widely recognised for the treatment of stress, anxiety and depression, as well as for obsessive compulsive disorders. A comprehensive intraspecies chemotypic variation study, using samples harvested from two distinct regions of South Africa, was done using both proton nuclear magnetic resonance ( 1 H-NMR) spectroscopy of methanol extracts (N = 145) and ultra performance liquid chromatography-mass spectrometry (UPLC-MS) of acid/base extracts (N = 289). Chemometric analysis of the 1 H-NMR data indicated two main clusters that were region-specific (Northern Cape and Western Cape provinces). Two dimensional (2D) NMR was used to identify analytes that contributed to the clustering as revealed by the S-plot. The sceletium alkaloids, pinitol and two alkylamines, herein reported for the first time from S. tortuosum, were identified as markers that distinguished the two groups. Relative quantification of the marker analytes conducted by qNMR indicated that samples from the Northern Cape generally contained higher concentrations of all the markers than samples from the Western Cape. Quantitative analysis of the four mesembrine alkaloids using a validated UPLC-photo diode array (PDA) detection method confirmed the results of qNMR with regard to the total alkaloid concentrations. Samples from the Northern Cape Province were found to contain, on average, very high total alkaloids, ranging from 4938.0 to 9376.8 mg/kg dry w. Regarding the Western Cape samples, the total yields of the four mesembrine alkaloids were substantially lower (averages 16.4-4143.2 mg/kg). Hierarchical cluster analysis of the UPLC-MS data, based on the alkaloid chemistry, revealed three branches, with one branch comprising samples primarily from the Northern Cape that seemed somewhat chemically conserved, while the other two branches represented mainly samples from the Western Cape. The construction of an orthogonal projections to latent structures-discriminant analysis model and subsequent loadings plot, allowed alkaloid markers to be identified for each cluster. The diverse sceletium alkaloid chemistry of samples from the three clusters may facilitate the recognition of alkaloid profiles, rather than individual compounds, that exert targeted effects on various brain receptors involved in stress, anxiety or depression. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of Resistant Starches in Rat Cecal Contents Using Fourier Transform Infrared Photoacoustic Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Timothy J.; Ai, Yongfeng; Jones, Roger W.

Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) qualitatively and quantitatively measured resistant starch (RS) in rat cecal contents. Fisher 344 rats were fed diets of 55% (w/w, dry basis) starch for 8 weeks. Cecal contents were collected from sacrificed rats. A corn starch control was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. To calibrate the FTIR-PAS analysis, samples from each diet were analyzed using an enzymatic assay. A partial least-squares cross-validation plot generated from the enzymatic assay and FTIR-PAS spectral results for starch fitmore » the ideal curve with a R2 of 0.997. A principal component analysis plot of components 1 and 2 showed that spectra from diets clustered significantly from each other. This study clearly showed that FTIR-PAS can accurately quantify starch content and identify the form of starch in complex matrices.« less

imDEV: a graphical user interface to R multivariate analysis tools in Microsoft Excel

PubMed Central

Grapov, Dmitry; Newman, John W.

2012-01-01

Summary: Interactive modules for Data Exploration and Visualization (imDEV) is a Microsoft Excel spreadsheet embedded application providing an integrated environment for the analysis of omics data through a user-friendly interface. Individual modules enables interactive and dynamic analyses of large data by interfacing R's multivariate statistics and highly customizable visualizations with the spreadsheet environment, aiding robust inferences and generating information-rich data visualizations. This tool provides access to multiple comparisons with false discovery correction, hierarchical clustering, principal and independent component analyses, partial least squares regression and discriminant analysis, through an intuitive interface for creating high-quality two- and a three-dimensional visualizations including scatter plot matrices, distribution plots, dendrograms, heat maps, biplots, trellis biplots and correlation networks. Availability and implementation: Freely available for download at http://sourceforge.net/projects/imdev/. Implemented in R and VBA and supported by Microsoft Excel (2003, 2007 and 2010). Contact: John.Newman@ars.usda.gov Supplementary Information: Installation instructions, tutorials and users manual are available at http://sourceforge.net/projects/imdev/. PMID:22815358

A primer on stand and forest inventory designs

Treesearch

H. Gyde Lund; Charles E. Thomas

1989-01-01

Covers designs for the inventory of stands and forests in detail and with worked-out examples. For stands, random sampling, line transects, ricochet plot, systematic sampling, single plot, cluster, subjective sampling and complete enumeration are discussed. For forests inventory, the main categories are subjective sampling, inventories without prior stand mapping,...

Techniques and computations for mapping plot clusters that straddle stand boundaries

Treesearch

Charles T. Scott; William A. Bechtold

1995-01-01

Many regional (extensive) forest surveys use clusters of subplots or prism points to reduce survey costs. Two common methods of handling clusters that straddle stand boundaries entail: (1) moving all subplots into a single forest cover type, or (2)"averaging" data across multiple conditions without regard to the boundaries. these methods result in biased...

NeatMap--non-clustering heat map alternatives in R.

PubMed

Rajaram, Satwik; Oono, Yoshi

2010-01-22

The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the detection of hidden structures and relations in the data. However, it is hampered by its use of cluster analysis which does not always respect the intrinsic relations in the data, often requiring non-standardized reordering of rows/columns to be performed post-clustering. This sometimes leads to uninformative and/or misleading conclusions. Often it is more informative to use dimension-reduction algorithms (such as Principal Component Analysis and Multi-Dimensional Scaling) which respect the topology inherent in the data. Yet, despite their proven utility in the analysis of biological data, they are not as widely used. This is at least partially due to the lack of user-friendly visualization methods with the visceral impact of the heat map. NeatMap is an R package designed to meet this need. NeatMap offers a variety of novel plots (in 2 and 3 dimensions) to be used in conjunction with these dimension-reduction techniques. Like the heat map, but unlike traditional displays of such results, it allows the entire dataset to be displayed while visualizing relations between elements. It also allows superimposition of cluster analysis results for mutual validation. NeatMap is shown to be more informative than the traditional heat map with the help of two well-known microarray datasets. NeatMap thus preserves many of the strengths of the clustered heat map while addressing some of its deficiencies. It is hoped that NeatMap will spur the adoption of non-clustering dimension-reduction algorithms.

Land Reclamation in Brazilian Amazônia: A chronosequence study of floristic development in the national forest of Jamiri-RO mined areas

NASA Astrophysics Data System (ADS)

Fengler, Felipe; Ribeiro, Admilson; Longo, Regina; Merides, Marcela; Soares, Herlon; Melo, Wanderley

2017-04-01

Although reclamation techniques for forest ecosystems recovery have been developed over the past decades, there is still a great difficulty in the establishment on environment assessment, especially when compared to the non-disturbed ecosystems. This work evaluated the results and limitations on cassiterite-mined areas in reclamation, at Brazilian Amazônia. Floristic variables from 29 plots located on 15-year-old native species reforestation sites and two plots from preserved open/closed canopy forests were analyzed in a chronosequece way (2010-2015). Regeneration density, species richness, average girth, and average height were evaluated every year, by means of cluster analysis (Euclidian distance, Ward method) and submitted to multiscale bootstrap resampling (a=5%). It was conduced the regression analysis for each identified group in 2015 in order to verify differences between the chronosequece development. The results showed the existence of two main groups in 2010, one witch all mined plots were allocated and other with open/closed canopy plots. After 2011 some mined areas became allocated in the open/closed canopy plots group. From 2013 and on open/closed canopy plots appeared shuffled in the formed groups, indicating the reclamation sites conditions became similar to natural areas. Finally, in 2015 three main groups were formed. The regression analysis showed that group three had a higher trend of development for regeneration density, with higher angular coefficient and higher values. For species richness all the groups had a similar trend, with values lower than open/closed canopy forest. In average girth higher trends were observed in group one and all values were near to open canopy forest in 2015. Average height showed better trends and higher values in group two. It was concluded that all mined sites had a forest recovery process. However, different responses to reclamation process were observed due to the differences in the degraded soils characteristics. Keywords: Recovery, Restoration, Forest, Chronosequece, Cassiterite.

Infrared spectroscopy of water clusters isolated in methane matrices: Effects of isotope substitution and annealing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamakawa, Koichiro, E-mail: koichiro.yamakawa@gakushuin.ac.jp; Ehara, Namika; Ozawa, Nozomi

2016-07-15

Using infrared-active solvents of CH{sub 4} and CD{sub 4} for matrix isolation, we measured infrared spectra of H{sub 2}O and D{sub 2}O clusters at 7 K. The solute-concentration dependence of the spectrum of H{sub 2}O clusters in a CH{sub 4} matrix was investigated and was used for the peak assignment. Annealing procedures were found to promote the size growth of water clusters in methane matrices for all the combinations of (H{sub 2}O, CH{sub 4}), (H{sub 2}O, CD{sub 4}), (D{sub 2}O, CH{sub 4}), and (D{sub 2}O, CD{sub 4}). We also monitored the ν{sub 3} absorption due to methane to find themore » annealing-induced structural change only of solid CH{sub 4}. The matrix effects on the vibrations of the clusters are discussed on the basis of “T{sub c} plots”, where their frequencies are plotted as a function of the square root of the matrix critical temperature, T{sub c}. The obtained plots assure the validity of the assignment of the cluster peaks.« less

The Efficacy of Multidimensional Line-Printer Graphics for Cluster Recovery.

ERIC Educational Resources Information Center

Brown, R. L.

The plotting of multivariate data using computer line-printers has become a popular means of quickly representing multidimensional data. While many plotting programs are available, there is a paucity of research regarding the validity and reliability of interpretations made by viewing such graphics. This study explores the validity of four…

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

PubMed

Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando

2018-01-01

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.

Graphical classification of DNA sequences of HLA alleles by deep learning.

PubMed

Miyake, Jun; Kaneshita, Yuhei; Asatani, Satoshi; Tagawa, Seiichi; Niioka, Hirohiko; Hirano, Takashi

2018-04-01

Alleles of human leukocyte antigen (HLA)-A DNAs are classified and expressed graphically by using artificial intelligence "Deep Learning (Stacked autoencoder)". Nucleotide sequence data corresponding to the length of 822 bp, collected from the Immuno Polymorphism Database, were compressed to 2-dimensional representation and were plotted. Profiles of the two-dimensional plots indicate that the alleles can be classified as clusters are formed. The two-dimensional plot of HLA-A DNAs gives a clear outlook for characterizing the various alleles.

Iterative direct inversion: An exact complementary solution for inverting fault-slip data to obtain palaeostresses

NASA Astrophysics Data System (ADS)

Mostafa, Mostafa E.

2005-10-01

The present study shows that reconstructing the reduced stress tensor (RST) from the measurable fault-slip data (FSD) and the immeasurable shear stress magnitudes (SSM) is a typical iteration problem. The result of direct inversion of FSD presented by Angelier [1990. Geophysical Journal International 103, 363-376] is considered as a starting point (zero step iteration) where all SSM are assigned constant value ( λ=√{3}/2). By iteration, the SSM and RST update each other until they converge to fixed values. Angelier [1990. Geophysical Journal International 103, 363-376] designed the function upsilon ( υ) and the two estimators: relative upsilon (RUP) and (ANG) to express the divergence between the measured and calculated shear stresses. Plotting individual faults' RUP at successive iteration steps shows that they tend to zero (simulated data) or to fixed values (real data) at a rate depending on the orientation and homogeneity of the data. FSD of related origin tend to aggregate in clusters. Plots of the estimators ANG versus RUP show that by iteration, labeled data points are disposed in clusters about a straight line. These two new plots form the basis of a technique for separating FSD into homogeneous clusters.

Biological Characterization and Clinical Utilization of Metastatic ProstateCancer Associated lincRNA SchLAP1

DTIC Science & Technology

2017-07-01

followed by RNA isolation and qPCR analysis. CRISPR Based Overexpression of PCAT14 Stable cell lines overexpressing PCAT14 endogenously were made using...Supplementary Figure 2B, C). To overexpress PCAT14, we used a CRISPR (clustered regularly interspaced short palindromic repeat)- Cas9 Synergistic...the workflow to endogenously overexpress PCAT14 in prostate cancer cells using CRISPR /SAM system. B. Bar plots represent fold increase in PCAT14 level

Space-time cluster analysis of sea lice infestation (Caligus clemensi and Lepeophtheirus salmonis) on wild juvenile Pacific salmon in the Broughton Archipelago of Canada.

PubMed

Patanasatienkul, Thitiwan; Sanchez, Javier; Rees, Erin E; Pfeiffer, Dirk; Revie, Crawford W

2015-06-15

Sea lice infestation levels on wild chum and pink salmon in the Broughton Archipelago region are known to vary spatially and temporally; however, the locations of areas associated with a high infestation level had not been investigated yet. In the present study, the multivariate spatial scan statistic based on a Poisson model was used to assess spatial clustering of elevated sea lice (Caligus clemensi and Lepeophtheirus salmonis) infestation levels on wild chum and pink salmon sampled between March and July of 2004 to 2012 in the Broughton Archipelago and Knight Inlet regions of British Columbia, Canada. Three covariates, seine type (beach and purse seining), fish size, and year effect, were used to provide adjustment within the analyses. The analyses were carried out across the five months/datasets and between two fish species to assess the consistency of the identified clusters. Sea lice stages were explored separately for the early life stages (non-motile) and the late life stages of sea lice (motile). Spatial patterns in fish migration were also explored using monthly plots showing the average number of each fish species captured per sampling site. The results revealed three clusters for non-motile C. clemensi, two clusters for non-motile L. salmonis, and one cluster for the motile stage in each of the sea lice species. In general, the location and timing of clusters detected for both fish species were similar. Early in the season, the clusters of elevated sea lice infestation levels on wild fish are detected in areas closer to the rivers, with decreasing relative risks as the season progresses. Clusters were detected further from the estuaries later in the season, accompanied by increasing relative risks. In addition, the plots for fish migration exhibit similar patterns for both fish species in that, as expected, the juveniles move from the rivers toward the open ocean as the season progresses The identification of space-time clustering of infestation on wild fish from this study can help in targeting investigations of factors associated with these infestations and thereby support the development of more effective sea lice control measures. Copyright © 2015 Elsevier B.V. All rights reserved.

Direct analysis in real time mass spectrometry and multivariate data analysis: a novel approach to rapid identification of analytical markers for quality control of traditional Chinese medicine preparation.

PubMed

Zeng, Shanshan; Wang, Lu; Chen, Teng; Wang, Yuefei; Mo, Huanbiao; Qu, Haibin

2012-07-06

The paper presents a novel strategy to identify analytical markers of traditional Chinese medicine preparation (TCMP) rapidly via direct analysis in real time mass spectrometry (DART-MS). A commonly used TCMP, Danshen injection, was employed as a model. The optimal analysis conditions were achieved by measuring the contribution of various experimental parameters to the mass spectra. Salvianolic acids and saccharides were simultaneously determined within a single 1-min DART-MS run. Furthermore, spectra of Danshen injections supplied by five manufacturers were processed with principal component analysis (PCA). Obvious clustering was observed in the PCA score plot, and candidate markers were recognized from the contribution plots of PCA. The suitability of potential markers was then confirmed by contrasting with the results of traditional analysis methods. Using this strategy, fructose, glucose, sucrose, protocatechuic aldehyde and salvianolic acid A were rapidly identified as the markers of Danshen injections. The combination of DART-MS with PCA provides a reliable approach to the identification of analytical markers for quality control of TCMP. Copyright © 2012 Elsevier B.V. All rights reserved.

Direct seeding of brushbox, lemon-gum eucalyptus, and cluster pine in Hawaii

Treesearch

Gerald A. Walters

1969-01-01

Seeds of brushbox, lemon-gum eucalyptus, and cluster pine were sown in separate seed spots on the Mokuleia Forest Reserve, Oahu. Half the seed spots were mulched. After 1 year, only two brushbox seed spots were stocked; lemon-gum eucalyptus had significantly (5 percent level) more seed spots stocked in the mulched plots; cluster pine had significantly less. These two...

The forest resources of West Virginia

Treesearch

James T. Bones

1978-01-01

A statistical and analytical report of the third forest survey of West Virginia by the Forest Service, U. S. Department of Agriculture. Findings are based on the remeasurement of 1/5-acre plots and new 10-point cluster plots. This report analyzes trends in forest land area, timber volume, annual growth, and timber removals. Timber- products output by forest industries...

The forest resources of New Hampshire

Treesearch

Neil P. Kingsley

1976-01-01

A statistical and analytical report on the third forest survey of New Hampshire. Statistical findings are based on the remeasurement of 1/5-acre plots and new 10-point cluster plots. Trends in forest-land area, timber volume, annual growth, and timber removals are discussed; also timber-products output by forest industries, based upon a canvass of industries in 1973,...

The forest resources of Vermont

Treesearch

Neal P. Kingsley

1977-01-01

A statistical and analytical report on the third forest survey of Vermont by the USDA Forest Service. Statistical findings are based on the remeasurement of 1/5-acre plots and 10-point cluster plots. This report discusses and analyzes trends in forest-land area, timber volume, annual growth, and timber removals. Timber-products output by forest industries, based upon a...

Untangling Magmatic Processes and Hydrothermal Alteration of in situ Superfast Spreading Ocean Crust at ODP/IODP Site 1256 with Fuzzy c-means Cluster Analysis of Rock Magnetic Properties

NASA Astrophysics Data System (ADS)

Dekkers, M. J.; Heslop, D.; Herrero-Bervera, E.; Acton, G.; Krasa, D.

2014-12-01

Ocean Drilling Program (ODP)/Integrated ODP (IODP) Hole 1256D (6.44.1' N, 91.56.1' W) on the Cocos Plate occurs in 15.2 Ma oceanic crust generated by superfast seafloor spreading. Presently, it is the only drill hole that has sampled all three oceanic crust layers in a tectonically undisturbed setting. Here we interpret down-hole trends in several rock-magnetic parameters with fuzzy c-means cluster analysis, a multivariate statistical technique. The parameters include the magnetization ratio, the coercivity ratio, the coercive force, the low-field susceptibility, and the Curie temperature. By their combined, multivariate, analysis the effects of magmatic and hydrothermal processes can be evaluated. The optimal number of clusters - a key point in the analysis because there is no a priori information on this - was determined through a combination of approaches: by calculation of several cluster validity indices, by testing for coherent cluster distributions on non-linear-map plots, and importantly by testing for stability of the cluster solution from all possible starting points. Here, we consider a solution robust if the cluster allocation is independent of the starting configuration. The five-cluster solution appeared to be robust. Three clusters are distinguished in the extrusive segment of the Hole that express increasing hydrothermal alteration of the lavas. The sheeted dike and gabbro portions are characterized by two clusters, both with higher coercivities than in lava samples. Extensive alteration, however, can obliterate magnetic property differences between lavas, dikes, and gabbros. The imprint of thermochemical alteration on the iron-titanium oxides is only partially related to the porosity of the rocks. All clusters display rock magnetic characteristics in line with a stable NRM. This implies that the entire sampled sequence of ocean crust can contribute to marine magnetic anomalies. Determination of the absolute paleointensity with thermal techniques is not straightforward because of the propensity of oxyexsolution during laboratory heating and/or the presence of intergrowths. The upper part of the extrusive sequence, the granoblastic portion of the dikes, and moderately altered gabbros may contain a comparatively uncontaminated thermoremanent magnetization.

Correlates of the categories of adolescent attachment styles: Perceived rearing, family function, early life events, and personality.

PubMed

Tanaka, Nao; Hasui, Chieko; Uji, Masayo; Hiramura, Hidetoshi; Chen, Zi; Shikai, Noriko; Kitamura, Toshinori

2008-02-01

To identify the psychosocial correlates of adolescents. Unmarried university students (n = 4226) aged 18-23 years were examined in a questionnaire survey. Four clusters of people (indifferent, secure, fearful, and preoccupied) identified by cluster analysis were plotted in 2-D using discriminant function analysis with the first function (father's and mother's Care, Cooperativeness, and family Cohesion on the positive end and Harm Avoidance and father's and mother's Overprotection on the negative end) representing the Self-model and the second function (Reward Dependence and experience of Peer Victimization on the positive end and Self-directedness on the negative end) representing the Other model. These findings partially support Bartholomew's notion that adult attachment is based on the good versus bad representations of the self and the other and that it is influenced by psychosocial environments experienced over the course of development.

Spectrally resolved infrared microscopy and chemometric tools to reveal the interaction between blue light (470nm) and methicillin-resistant Staphylococcus aureus.

PubMed

Bumah, Violet V; Aboualizadeh, Ebrahim; Masson-Meyers, Daniela S; Eells, Janis T; Enwemeka, Chukuka S; Hirschmugl, Carol J

2017-02-01

Blue light inactivates methicillin-resistant Staphylococcus aureus (MRSA), a Gram-positive antibiotic resistant bacterium that leads to fatal infections; however, the mechanism of bacterial death remains unclear. In this paper, to uncover the mechanism underlying the bactericidal effect of blue light, a combination of Fourier transform infrared (FTIR) spectroscopy and chemometric tools is employed to detect the photoreactivity of MRSA and its distinctive pathway toward apoptosis after treatment. The mechanism of action of UV light and vancomycin against MRSA is also investigated to support the findings. Principal component analysis followed by linear discriminant analysis (PCA- LDA) is employed to reveal clustering of five groups of MRSA samples, namely untreated (control I), untreated and incubated at ambient air (control II), irradiated with 470nm blue light, irradiated with 253.5 UV light, and vancomycin-treated MRSA. Loadings plot from PCA-LDA analysis reveals important functional groups in proteins (1683, 1656, 1596, 1542cm -1 ), lipids (1743, 1409cm -1 ), and nucleic acids region of the spectrum (1060, 1087cm -1 ) that are responsible for the classification of blue light irradiated spectra and control spectra. Cluster vector plots and scores plot reveals that UV light-irradiated spectra are the most biochemically similar to blue light- irradiated spectra; however, some wavenumbers experience a shift. The shifts between blue light and UV light irradiated loadings plot at ν asym PO 2- band (from 1228 to 1238cm -1 ), DNA backbone (from 970 to 966cm -1 ) and base pairing vibration of DNA (from 1717 to 1712cm -1 ) suggest distinctive changes in DNA conformation in response to irradiation. Our findings indicate that irradiation of MRSA with 470nm light induces A-DNA cleavage and that B-DNA is more resistant to damage by blue light. Blue light and UV light treatment of MRSA are complementary and distinct from the known antimicrobial effect of vancomycin. Moreover, it is known that UV-induced cleavage of DNA predominantly targets B-DNA, which is in agreement with the FTIR findings. Overall the results suggest that the combination of light and vancomycin could be a more robust approach in treating MRSA infections. Published by Elsevier B.V.

A Refined Methodology for Defining Plant Communities Using Postagricultural Data from the Neotropics

PubMed Central

Myster, Randall W.

2012-01-01

How best to define and quantify plant communities was investigated using long-term plot data sampled from a recovering pasture in Puerto Rico and abandoned sugarcane and banana plantations in Ecuador. Significant positive associations between pairs of old field species were first computed and then clustered together into larger and larger species groups. I found that (1) no pasture or plantation had more than 5% of the possible significant positive associations, (2) clustering metrics showed groups of species participating in similar clusters among the five pasture/plantations over a gradient of decreasing association strength, and (3) there was evidence for repeatable communities—especially after banana cultivation—suggesting that past crops not only persist after abandonment but also form significant associations with invading plants. I then showed how the clustering hierarchy could be used to decide if any two pasture/plantation plots were in the same community, that is, to define old field communities. Finally, I suggested a similar procedure could be used for any plant community where the mechanisms and tolerances of species form the “cohesion” that produces clustering, making plant communities different than random assemblages of species. PMID:22536137

Resolution of coi-dominant phytoplankton species in a eutrophiclake using synchrotron-based Fourier transform infraredspectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dean, A.P.; Martin, Michael C.; Sigee, D.C.

2006-10-09

Synchrotron-based Fourier-transform infrared (FTIR)microspectroscopy was used to distinguish micropopulations of thecodominant algae Microcystis aeruginosa (Cyanophyceae) and Ceratiumhirundinella (Dinophyceae) in mixed phytoplankton samples taken from thewater column of a stratified eutrophic lake (Rostherne Mere, UK). FTIRspectra of the two algae showed a closely similar sequence of 10 bandsover the wave-number range 4000-900 cm-1. These were assigned to a rangeof vibrationally active chemical groups using published band assignmentsand on the basis of correlation and factor analysis. In both algae,intracellular concentrations of macromolecular components (determined asband intensity) varied considerably within the same population,indicating substantial intraspecific heterogeneity. Interspecificdifferences were separately analysed in relation tomore » discrete bands and bymultivariate analysis of the entire spectral region 1750-900 cm-1. Interms of discrete bands, comparison of individual intensities (normalisedto amide 1) demonstrated significant (99 percent probability level)differences in relation to six bands between the two algal species. Keyinterspecific differences were also noted in relation to the positions ofbands 2, 10 (carbohydrate) and 7 (protein) and in the 3-D plots derivedby principal component analysis (PCA) of the sequence of bandintensities. PCA of entire spectral regions showed clear resolutionofspecies in the PCA plot, with indication of separation on the basis ofprotein (region 1700-1500 cm1) and carbohydrate (region 1150-900 cm1)composition in the loading plot. Hierarchical cluster analysis (Wardalgorithm) of entire spectral regions also showed clear discrimination ofthe two species within the resulting dendrogram.« less

US forests are showing increased rates of decline in response to a changing climate

Treesearch

Warren B. Cohen; Zhiqiang Yang; David M. Bell; Stephen V. Stehman

2015-01-01

How vulnerable are US forest to a changing climate? We answer this question using Landsat time series data and a unique interpretation approach, TimeSync, a plot-based Landsat visualization and data collection tool. Original analyses were based on a stratified two-stage cluster sample design that included interpretation of 3858 forested plots. From these data, we...

Automated Classification and Analysis of Non-metallic Inclusion Data Sets

NASA Astrophysics Data System (ADS)

Abdulsalam, Mohammad; Zhang, Tongsheng; Tan, Jia; Webler, Bryan A.

2018-05-01

The aim of this study is to utilize principal component analysis (PCA), clustering methods, and correlation analysis to condense and examine large, multivariate data sets produced from automated analysis of non-metallic inclusions. Non-metallic inclusions play a major role in defining the properties of steel and their examination has been greatly aided by automated analysis in scanning electron microscopes equipped with energy dispersive X-ray spectroscopy. The methods were applied to analyze inclusions on two sets of samples: two laboratory-scale samples and four industrial samples from a near-finished 4140 alloy steel components with varying machinability. The laboratory samples had well-defined inclusions chemistries, composed of MgO-Al2O3-CaO, spinel (MgO-Al2O3), and calcium aluminate inclusions. The industrial samples contained MnS inclusions as well as (Ca,Mn)S + calcium aluminate oxide inclusions. PCA could be used to reduce inclusion chemistry variables to a 2D plot, which revealed inclusion chemistry groupings in the samples. Clustering methods were used to automatically classify inclusion chemistry measurements into groups, i.e., no user-defined rules were required.

MetaPlotR: a Perl/R pipeline for plotting metagenes of nucleotide modifications and other transcriptomic sites.

PubMed

Olarerin-George, Anthony O; Jaffrey, Samie R

2017-05-15

An increasing number of studies are mapping protein binding and nucleotide modifications sites throughout the transcriptome. Often, these sites cluster in certain regions of the transcript, giving clues to their function. Hence, it is informative to summarize where in the transcript these sites occur. A metagene is a simple and effective tool for visualizing the distribution of sites along a simplified transcript model. In this work, we introduce MetaPlotR, a Perl/R pipeline for creating metagene plots. The code and associated tutorial are available at https://github.com/olarerin/metaPlotR . srj2003@med.cornell.edu. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Crossmaps: Visualization of overlapping relationships in collections of journal papers

PubMed Central

Morris, Steven A.; Yen, Gary G.

2004-01-01

A crossmapping technique is introduced for visualizing multiple and overlapping relations among entity types in collections of journal articles. Groups of entities from two entity types are crossplotted to show correspondence of relations. For example, author collaboration groups are plotted on the x axis against groups of papers (research fronts) on the y axis. At the intersection of each pair of author group/research front pairs a circular symbol is plotted whose size is proportional to the number of times that authors in the group appear as authors in papers in the research front. Entity groups are found by agglomerative hierarchical clustering using conventional similarity measures. Crossmaps comprise a simple technique that is particularly suited to showing overlap in relations among entity groups. Particularly useful crossmaps are: research fronts against base reference clusters, research fronts against author collaboration groups, and research fronts against term co-occurrence clusters. When exploring the knowledge domain of a collection of journal papers, it is useful to have several crossmaps of different entity pairs, complemented by research front timelines and base reference cluster timelines. PMID:14762168

Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.

PubMed

Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria

2017-10-01

Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

Automatic classification of canine PRG neuronal discharge patterns using K-means clustering.

PubMed

Zuperku, Edward J; Prkic, Ivana; Stucke, Astrid G; Miller, Justin R; Hopp, Francis A; Stuth, Eckehard A

2015-02-01

Respiratory-related neurons in the parabrachial-Kölliker-Fuse (PB-KF) region of the pons play a key role in the control of breathing. The neuronal activities of these pontine respiratory group (PRG) neurons exhibit a variety of inspiratory (I), expiratory (E), phase spanning and non-respiratory related (NRM) discharge patterns. Due to the variety of patterns, it can be difficult to classify them into distinct subgroups according to their discharge contours. This report presents a method that automatically classifies neurons according to their discharge patterns and derives an average subgroup contour of each class. It is based on the K-means clustering technique and it is implemented via SigmaPlot User-Defined transform scripts. The discharge patterns of 135 canine PRG neurons were classified into seven distinct subgroups. Additional methods for choosing the optimal number of clusters are described. Analysis of the results suggests that the K-means clustering method offers a robust objective means of both automatically categorizing neuron patterns and establishing the underlying archetypical contours of subtypes based on the discharge patterns of group of neurons. Published by Elsevier B.V.

Landscape context and scale differentially impact coffee leaf rust, coffee berry borer, and coffee root-knot nematodes.

PubMed

Avelino, Jacques; Romero-Gurdián, Alí; Cruz-Cuellar, Héctor F; Declerck, Fabrice A J

2012-03-01

Crop pest and disease incidences at plot scale vary as a result of landscape effects. Two main effects can be distinguished. First, landscape context provides habitats of variable quality for pests, pathogens, and beneficial and vector organisms. Second, the movements of these organisms are dependent on the connectivity status of the landscape. Most of the studies focus on indirect effects of landscape context on pest abundance through their predators and parasitoids, and only a few on direct effects on pests and pathogens. Here we studied three coffee pests and pathogens, with limited or no pressure from host-specific natural enemies, and with widely varying life histories, to test their relationships with landscape context: a fungus, Hemileia vastatrix, causal agent of coffee leaf rust; an insect, the coffee berry borer, Hypothenemus hampei (Coleoptera: Curculionidae); and root-knot nematodes, Meloidogyne spp. Their incidence was assessed in 29 coffee plots from Turrialba, Costa Rica. In addition, we characterized the landscape context around these coffee plots in 12 nested circular sectors ranging from 50 to 1500 m in radius. We then performed correlation analysis between proportions of different land uses at different scales and coffee pest and disease incidences. We obtained significant positive correlations, peaking at the 150 m radius, between coffee berry borer abundance and proportion of coffee in the landscape. We also found significant positive correlations between coffee leaf rust incidence and proportion of pasture, peaking at the 200 m radius. Even after accounting for plot level predictors of coffee leaf rust and coffee berry borer through covariance analysis, the significance of landscape structure was maintained. We hypothesized that connected coffee plots favored coffee berry borer movements and improved its survival. We also hypothesized that wind turbulence, produced by low-wind-resistance land uses such as pasture, favored removal of coffee leaf rust spore clusters from host surfaces, resulting in increased epidemics. In contrast, root-knot nematode population density was not correlated to landscape context, possibly because nematodes are almost immobile in the soil. We propose fragmenting coffee plots with forest corridors to control coffee berry borer movements between coffee plots without favoring coffee leaf rust dispersal.

Increasing the perceptual salience of relationships in parallel coordinate plots.

PubMed

Harter, Jonathan M; Wu, Xunlei; Alabi, Oluwafemi S; Phadke, Madhura; Pinto, Lifford; Dougherty, Daniel; Petersen, Hannah; Bass, Steffen; Taylor, Russell M

2012-01-01

We present three extensions to parallel coordinates that increase the perceptual salience of relationships between axes in multivariate data sets: (1) luminance modulation maintains the ability to preattentively detect patterns in the presence of overplotting, (2) adding a one-vs.-all variable display highlights relationships between one variable and all others, and (3) adding a scatter plot within the parallel-coordinates display preattentively highlights clusters and spatial layouts without strongly interfering with the parallel-coordinates display. These techniques can be combined with one another and with existing extensions to parallel coordinates, and two of them generalize beyond cases with known-important axes. We applied these techniques to two real-world data sets (relativistic heavy-ion collision hydrodynamics and weather observations with statistical principal component analysis) as well as the popular car data set. We present relationships discovered in the data sets using these methods.

Visualization and unsupervised predictive clustering of high-dimensional multimodal neuroimaging data.

PubMed

Mwangi, Benson; Soares, Jair C; Hasan, Khader M

2014-10-30

Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data. We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm. t-SNE was evaluated against classical principal component analysis. Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders. Copyright © 2014 Elsevier B.V. All rights reserved.

Computation of neutron fluxes in clusters of fuel pins arranged in hexagonal assemblies (2D and 3D)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prabha, H.; Marleau, G.

2012-07-01

For computations of fluxes, we have used Carvik's method of collision probabilities. This method requires tracking algorithms. An algorithm to compute tracks (in 2D and 3D) has been developed for seven hexagonal geometries with cluster of fuel pins. This has been implemented in the NXT module of the code DRAGON. The flux distribution in cluster of pins has been computed by using this code. For testing the results, they are compared when possible with the EXCELT module of the code DRAGON. Tracks are plotted in the NXT module by using MATLAB, these plots are also presented here. Results are presentedmore » with increasing number of lines to show the convergence of these results. We have numerically computed volumes, surface areas and the percentage errors in these computations. These results show that 2D results converge faster than 3D results. The accuracy on the computation of fluxes up to second decimal is achieved with fewer lines. (authors)« less

Global Tree Range Shifts Under Forecasts from Two Alternative GCMs Using Two Future Scenarios

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Kumar, J.; Potter, K. M.; Hoffman, F. M.

2013-12-01

Global shifts in the environmentally suitable ranges of 215 tree species were predicted under forecasts from two GCMs (the Parallel Climate Model (PCM), and the Hadley Model), each under two IPCC future climatic scenarios (A1 and B1), each at two future dates (2050 and 2100). The analysis considers all global land surface at a resolution of 4 km2. A statistical multivariate clustering procedure was used to quantitatively delineate 30 thousand environmentally homogeneous ecoregions across present and 8 potential future global locations at once, using global maps of 17 environmental characteristics describing temperature, precipitation, soils, topography and solar insolation. Presence of each tree species on Forest Inventory Analysis (FIA) plots and in Global Biodiversity Information Facility (GBIF) samples was used to select a subset of suitable ecoregions from the full set of 30 thousand. Once identified, this suitable subset of ecoregions was compared to the known current range of the tree species under present conditions. Predicted present ranges correspond well with current understanding for all but a few of the 215 tree species. The subset of suitable ecoregions for each tree species can then be tracked into the future to determine whether the suitable home range for this species remains the same, moves, grows, shrinks, or disappears under each model/scenario combination. Occurrence and growth performance measurements for various tree species across the U.S. are limited to FIA plots. We present a new, general-purpose empirical imputation method which associates sparse measurements of dependent variables with particular multivariate clustered combinations of the independent variables, and then estimates values for unmeasured clusters, based on directional proximity in multidimensional data space, at both the cluster and map-cell levels of resolution. Using Associative Clustering, we scaled up the FIA point measurements into contonuous maps that show the expected growth and suitability for individual tree species across the continental US. Maps were generated for each tree species showing the Minimum Required Movement (MRM) straight-line distance from each currently suitable location to the geographically nearest "lifeboat" location having suitable conditions in the future. Locations that are the closest "lifeboats" for many MRM propagules originating from wide surrounding areas may constitute high-priority preservation targets as a refugium against climatic change.

Spatial Variation of Soil Respiration in a Cropland under Winter Wheat and Summer Maize Rotation in the North China Plain.

PubMed

Huang, Ni; Wang, Li; Hu, Yongsen; Tian, Haifeng; Niu, Zheng

2016-01-01

Spatial variation of soil respiration (Rs) in cropland ecosystems must be assessed to evaluate the global terrestrial carbon budget. This study aims to explore the spatial characteristics and controlling factors of Rs in a cropland under winter wheat and summer maize rotation in the North China Plain. We collected Rs data from 23 sample plots in the cropland. At the late jointing stage, the daily mean Rs of summer maize (4.74 μmol CO2 m-2 s-1) was significantly higher than that of winter wheat (3.77μmol CO2 m-2 s-1). However, the spatial variation of Rs in summer maize (coefficient of variation, CV = 12.2%) was lower than that in winter wheat (CV = 18.5%). A similar trend in CV was also observed for environmental factors but not for biotic factors, such as leaf area index, aboveground biomass, and canopy chlorophyll content. Pearson's correlation analyses based on the sampling data revealed that the spatial variation of Rs was poorly explained by the spatial variations of biotic factors, environmental factors, or soil properties alone for winter wheat and summer maize. The similarly non-significant relationship was observed between Rs and the enhanced vegetation index (EVI), which was used as surrogate for plant photosynthesis. EVI was better correlated with field-measured leaf area index than the normalized difference vegetation index and red edge chlorophyll index. All the data from the 23 sample plots were categorized into three clusters based on the cluster analysis of soil carbon/nitrogen and soil organic carbon content. An apparent improvement was observed in the relationship between Rs and EVI in each cluster for both winter wheat and summer maize. The spatial variation of Rs in the cropland under winter wheat and summer maize rotation could be attributed to the differences in spatial variations of soil properties and biotic factors. The results indicate that applying cluster analysis to minimize differences in soil properties among different clusters can improve the role of remote sensing data as a proxy of plant photosynthesis in semi-empirical Rs models and benefit the acquisition of Rs in cropland ecosystems at large scales.

Dynamical relationship between wind speed magnitude and meridional temperature contrast: Application to an interannual oscillation in Venusian middle atmosphere GCM

NASA Astrophysics Data System (ADS)

Yamamoto, Masaru; Takahashi, Masaaki

2018-03-01

We derive simple dynamical relationships between wind speed magnitude and meridional temperature contrast. The relationship explains scatter plot distributions of time series of three variables (maximum zonal wind speed UMAX, meridional wind speed VMAX, and equator-pole temperature contrast dTMAX), which are obtained from a Venus general circulation model with equatorial Kelvin-wave forcing. Along with VMAX and dTMAX, UMAX likely increases with the phase velocity and amplitude of a forced wave. In the scatter diagram of UMAX versus dTMAX, points are plotted along a linear equation obtained from a thermal-wind relationship in the cloud layer. In the scatter diagram of VMAX versus UMAX, the apparent slope is somewhat steep in the high UMAX regime, compared with the low UMAX regime. The scatter plot distributions are qualitatively consistent with a quadratic equation obtained from a diagnostic equation of the stream function above the cloud top. The plotted points in the scatter diagrams form a linear cluster for weak wave forcing, whereas they form a small cluster for strong wave forcing. An interannual oscillation of the general circulation forming the linear cluster in the scatter diagram is apparent in the experiment of weak 5.5-day wave forcing. Although a pair of equatorial Kelvin and high-latitude Rossby waves with a same period (Kelvin-Rossby wave) produces equatorward heat and momentum fluxes in the region below 60 km, the equatorial wave does not contribute to the long-period oscillation. The interannual fluctuation of the high-latitude jet core leading to the time variation of UMAX is produced by growth and decay of a polar mixed Rossby-gravity wave with a 14-day period.

A web portal for hydrodynamical, cosmological simulations

NASA Astrophysics Data System (ADS)

Ragagnin, A.; Dolag, K.; Biffi, V.; Cadolle Bel, M.; Hammer, N. J.; Krukau, A.; Petkova, M.; Steinborn, D.

2017-07-01

This article describes a data centre hosting a web portal for accessing and sharing the output of large, cosmological, hydro-dynamical simulations with a broad scientific community. It also allows users to receive related scientific data products by directly processing the raw simulation data on a remote computing cluster. The data centre has a multi-layer structure: a web portal, a job control layer, a computing cluster and a HPC storage system. The outer layer enables users to choose an object from the simulations. Objects can be selected by visually inspecting 2D maps of the simulation data, by performing highly compounded and elaborated queries or graphically by plotting arbitrary combinations of properties. The user can run analysis tools on a chosen object. These services allow users to run analysis tools on the raw simulation data. The job control layer is responsible for handling and performing the analysis jobs, which are executed on a computing cluster. The innermost layer is formed by a HPC storage system which hosts the large, raw simulation data. The following services are available for the users: (I) CLUSTERINSPECT visualizes properties of member galaxies of a selected galaxy cluster; (II) SIMCUT returns the raw data of a sub-volume around a selected object from a simulation, containing all the original, hydro-dynamical quantities; (III) SMAC creates idealized 2D maps of various, physical quantities and observables of a selected object; (IV) PHOX generates virtual X-ray observations with specifications of various current and upcoming instruments.

Polychromatic plots: graphical display of multidimensional data.

PubMed

Roederer, Mario; Moody, M Anthony

2008-09-01

Limitations of graphical displays as well as human perception make the presentation and analysis of multidimensional data challenging. Graphical display of information on paper or by current projectors is perforce limited to two dimensions; the encoding of information from other dimensions must be overloaded into the two physical dimensions. A number of alternative means of encoding this information have been implemented, such as offsetting data points at an angle (e.g., three-dimensional projections onto a two-dimensional surface) or generating derived parameters that are combinations of other variables (e.g., principal components). Here, we explore the use of color to encode additional dimensions of data. PolyChromatic Plots are standard dot plots, where the color of each event is defined by the values of one, two, or three of the measurements for that event. The measurements for these parameters are mapped onto an intensity value for each primary color (red, green, or blue) based on different functions. In addition, differential weighting of the priority with which overlapping events are displayed can be defined by these same measurements. PolyChromatic Plots can encode up to five independent dimensions of data in a single display. By altering the color mapping function and the priority function, very different displays that highlight or de-emphasize populations of events can be generated. As for standard black-and-white dot plots, frequency information can be significantly biased by this display; care must be taken to ensure appropriate interpretation of the displays. PolyChromatic Plots are a powerful display type that enables rapid data exploration. By virtue of encoding as many as five dimensions of data independently, an enormous amount of information can be gleaned from the displays. In many ways, the display performs somewhat like an unsupervised cluster algorithm, by highlighting events of similar distributions in multivariate space.

Visual analytics of large multidimensional data using variable binned scatter plots

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Sharma, Ratnesh K.; Keim, Daniel A.; Janetzko, Halldór

2010-01-01

The scatter plot is a well-known method of visualizing pairs of two-dimensional continuous variables. Multidimensional data can be depicted in a scatter plot matrix. They are intuitive and easy-to-use, but often have a high degree of overlap which may occlude a significant portion of data. In this paper, we propose variable binned scatter plots to allow the visualization of large amounts of data without overlapping. The basic idea is to use a non-uniform (variable) binning of the x and y dimensions and plots all the data points that fall within each bin into corresponding squares. Further, we map a third attribute to color for visualizing clusters. Analysts are able to interact with individual data points for record level information. We have applied these techniques to solve real-world problems on credit card fraud and data center energy consumption to visualize their data distribution and cause-effect among multiple attributes. A comparison of our methods with two recent well-known variants of scatter plots is included.

Optical nonlinearity and charge transfer analysis of pyrene adsorbed on silver: Computational and experimental investigations

NASA Astrophysics Data System (ADS)

Reeta Felscia, U.; Rajkumar, Beulah J. M.; Sankar, Pranitha; Philip, Reji; Briget Mary, M.

2017-09-01

The interaction of pyrene on silver has been investigated using both experimental and computational methods. Hyperpolarizabilities computed theoretically together with experimental nonlinear absorption from open aperture Z-scan measurements, point towards a possible use of pyrene adsorbed on silver in the rational design of NLO devices. Presence of a red shift in both simulated and experimental UV-Vis spectra confirms the adsorption on silver, which is due to the electrostatic interaction between silver and pyrene, inducing variations in the structural parameters of pyrene. Fukui calculations along with MEP plot predict the electrophilic nature of the silver cluster in the presence of pyrene, with NBO analysis revealing that the adsorption causes charge redistribution from the first three rings of pyrene towards the fourth ring, from where the 2p orbitals of carbon interact with the valence 5s orbitals of the cluster. This is further confirmed by the downshifting of ring breathing modes in both the experimental and theoretical Raman spectra.

Spatio-Temporal Epidemiology of Viral Hepatitis in China (2003-2015): Implications for Prevention and Control Policies.

PubMed

Zhu, Bin; Liu, Jinlin; Fu, Yang; Zhang, Bo; Mao, Ying

2018-04-02

Viral hepatitis, as one of the most serious notifiable infectious diseases in China, takes heavy tolls from the infected and causes a severe economic burden to society, yet few studies have systematically explored the spatio-temporal epidemiology of viral hepatitis in China. This study aims to explore, visualize and compare the epidemiologic trends and spatial changing patterns of different types of viral hepatitis (A, B, C, E and unspecified, based on the classification of CDC) at the provincial level in China. The growth rates of incidence are used and converted to box plots to visualize the epidemiologic trends, with the linear trend being tested by chi-square linear by linear association test. Two complementary spatial cluster methods are used to explore the overall agglomeration level and identify spatial clusters: spatial autocorrelation analysis (measured by global and local Moran's I) and space-time scan analysis. Based on the spatial autocorrelation analysis, the hotspots of hepatitis A remain relatively stable and gradually shrunk, with Yunnan and Sichuan successively moving out the high-high (HH) cluster area. The HH clustering feature of hepatitis B in China gradually disappeared with time. However, the HH cluster area of hepatitis C has gradually moved towards the west, while for hepatitis E, the provincial units around the Yangtze River Delta region have been revealing HH cluster features since 2005. The space-time scan analysis also indicates the distinct spatial changing patterns of different types of viral hepatitis in China. It is easy to conclude that there is no one-size-fits-all plan for the prevention and control of viral hepatitis in all the provincial units. An effective response requires a package of coordinated actions, which should vary across localities regarding the spatial-temporal epidemic dynamics of each type of virus and the specific conditions of each provincial unit.

Novel Flood Detection and Analysis Method Using Recurrence Property

NASA Astrophysics Data System (ADS)

Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert

2016-04-01

Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.

[Discrimination of varieties of brake fluid using visual-near infrared spectra].

PubMed

Jiang, Lu-lu; Tan, Li-hong; Qiu, Zheng-jun; Lu, Jiang-feng; He, Yong

2008-06-01

A new method was developed to fast discriminate brands of brake fluid by means of visual-near infrared spectroscopy. Five different brands of brake fluid were analyzed using a handheld near infrared spectrograph, manufactured by ASD Company, and 60 samples were gotten from each brand of brake fluid. The samples data were pretreated using average smoothing and standard normal variable method, and then analyzed using principal component analysis (PCA). A 2-dimensional plot was drawn based on the first and the second principal components, and the plot indicated that the clustering characteristic of different brake fluid is distinct. The foregoing 6 principal components were taken as input variable, and the band of brake fluid as output variable to build the discriminate model by stepwise discriminant analysis method. Two hundred twenty five samples selected randomly were used to create the model, and the rest 75 samples to verify the model. The result showed that the distinguishing rate was 94.67%, indicating that the method proposed in this paper has good performance in classification and discrimination. It provides a new way to fast discriminate different brands of brake fluid.

Use of Fatty Acid Methyl Ester Profiles to Compare Copper-Tolerant and Copper-Sensitive Strains of Pantoea ananatis.

PubMed

Nischwitz, C; Gitaitis, R; Sanders, H; Langston, D; Mullinix, B; Torrance, R; Boyhan, G; Zolobowska, L

2007-10-01

ABSTRACT A survey was conducted to evaluate differences in fatty acid methyl ester (FAME) profiles among strains of Pantoea ananatis, causal agent of center rot of onion (Allium cepa), isolated from 15 different onion cultivars in three different sites in Georgia. Differences in FAME composition were determined by plotting principal components (PCs) in two-dimensional plots. Euclidean distance squared (ED(2)) values indicated a high degree of similarity among strains. Plotting of PCs calculated from P. ananatis strains capable of growing on media amended with copper sulfate pentahydrate (200 mug/ml) indicated that copper-tolerant strains grouped into tight clusters separate from clusters formed by wild-type strains. However, unlike copper-sensitive strains, the copper-tolerant strains tended to cluster by location. A total of 80, 60, and 73% of the strains from Tift1, Tift2, and Tattnall, respectively, exhibited either confluent growth or partial growth on copper-amended medium. However, all strains were sensitive to a mixture of copper sulfate pentahydrate (200 mug/ml) and maneb (40 mug/ml). When copper-tolerant clones were analyzed and compared with their wild-type parents, in all cases the plotting of PCs developed from copper-tolerant clones formed tight clusters separate from clusters formed by the parents. Eigenvalues generated from these tests indicated that two components provided a good summary of the data, accounting for 98, 98, and 96% of the standardized variance for strains Pna 1-15B, Pna 1-12B, and Pna 2-5A, respectively. Furthermore, feature 4 (cis-9-hexadecenoic acid/2-hydroxy-13-methyltetradecanoic acid) and feature 7 (cis-9/trans-12/cis-7-octadecenoic acid) were the highest or second highest absolute values for PC1 in all three strains of the parents versus copper-tolerant clones, and hexadecanoic acid was the highest absolute value for PC2 in all three strains. Along with those fatty acids, dodecanoic acid and feature 3 (3-hydroxytetradecanoic acid/14-methylpentadecenoic acid) also had an impact on the differences observed between copper-sensitive parents and copper-resistant mutants. Finding these changes in bacterial fatty acid composition could lead to the development of a laboratory assay to identify copper-tolerant strains using gas chromatography as well as providing clues to further elucidate the mode of action of copper tolerance.

Data and animal management software for large-scale phenotype screening.

PubMed

Ching, Keith A; Cooke, Michael P; Tarantino, Lisa M; Lapp, Hilmar

2006-04-01

The mouse N-ethyl-N-nitrosourea (ENU) mutagenesis program at the Genomics Institute of the Novartis Research Foundation (GNF) uses MouseTRACS to analyze phenotype screens and manage animal husbandry. MouseTRACS is a Web-based laboratory informatics system that electronically records and organizes mouse colony operations, prints cage cards, tracks inventory, manages requests, and reports Institutional Animal Care and Use Committee (IACUC) protocol usage. For efficient phenotype screening, MouseTRACS identifies mutants, visualizes data, and maps mutations. It displays and integrates phenotype and genotype data using likelihood odds ratio (LOD) plots of genetic linkage between genotype and phenotype. More detailed mapping intervals show individual single nucleotide polymorphism (SNP) markers in the context of phenotype. In addition, dynamically generated pedigree diagrams and inventory reports linked to screening results summarize the inheritance pattern and the degree of penetrance. MouseTRACS displays screening data in tables and uses standard charts such as box plots, histograms, scatter plots, and customized charts looking at clustered mice or cross pedigree comparisons. In summary, MouseTRACS enables the efficient screening, analysis, and management of thousands of animals to find mutant mice and identify novel gene functions. MouseTRACS is available under an open source license at http://www.mousetracs.sourceforge.net.

Clustering, hierarchical organization, and the topography of abstract and concrete nouns.

PubMed

Troche, Joshua; Crutch, Sebastian; Reilly, Jamie

2014-01-01

The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are "disembodied" in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N = 365) rated target words (n = 400 English nouns) across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence). Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

On Identifying Clusters Within the C-type Asteroids of the Sloan Digital Sky Survey

NASA Astrophysics Data System (ADS)

Poole, Renae; Ziffer, J.; Harvell, T.

2012-10-01

We applied AutoClass, a data mining technique based upon Bayesian Classification, to C-group asteroid colors in the Sloan Digital Sky Survey (SDSS). Previous taxonomic studies relied mostly on Principal Component Analysis (PCA) to differentiate asteroids within the C-group (e.g. B, G, F, Ch, Cg and Cb). AutoClass's advantage is that it calculates the most probable classification for us, removing the human factor from this part of the analysis. In our results, AutoClass divided the C-groups into two large classes and six smaller classes. The two large classes (n=4974 and 2033, respectively) display distinct regions with some overlap in color-vs-color plots. Each cluster's average spectrum is compared to 'typical' spectra of the C-group subtypes as defined by Tholen (1989) and each cluster's members are evaluated for consistency with previous taxonomies. Of the 117 asteroids classified as B-type in previous taxonomies, only 12 were found with SDSS colors that matched our criteria of having less than 0.1 magnitude error in u and 0.05 magnitude error in g, r, i, and z colors. Although this is a relatively small group, 11 of the 12 B-types were placed by AutoClass in the same cluster. By determining the C-group sub-classifications in the large SDSS database, this research furthers our understanding of the stratigraphy and composition of the main-belt.

“Local” Dark Energy Outflows Around Galaxy Groups and Rich Clusters

NASA Astrophysics Data System (ADS)

Byrd, Gene G.; Chernin, A. D.; Teerikorpi, P.; Dolgachev, V. P.; Kanter, A. A.; Domozhilova, L. M.; Valtonen, M.

2013-01-01

First detected at large Gpc distances, dark energy is a vacuum energy formulated as Einstein's cosmological constant, Λ. We have found its effects on “small” 1-3 Mpc scales in our Local Group. We have now found these effects in other nearby groups using member Doppler shifts and 3D distances from group centers (Cen A-M83; M81-M82; CV I). For the larger 20-30 Mpc Virgo and Fornax clusters, we now have found similar effects. Observationally, for both groups and clusters, gravity dominates a bound central system. The system gravitation and dark energy create a “zero-gravity” radius (R_{ZG}) from the center where the two balance. Smaller members bound inside R_{ZG} may be pulled out along with the less bound members which recede farther. A linear increase of recession with distance results which approaches a linear global Hubble law. These outflows are seen around groups in cosmological simulations which include galaxies as small as ~10^{-4} of the group mass. Scaled plots of asymptotic recessional velocity, V/(H(R_{ZG})), versus distance/ R_{ZG} of the outer galaxies are very similar for both the small groups and large clusters. This similarity on 1-30 Mpc scales suggests that a quasi-stationary bound central component and an expanding outflow applies to a wide range of groups and clusters due to small scale action of dark energy. Our new text book: Byrd, G., Chernin, A., Terrikorpi, P. and Valtonen, M. 2012, "Paths to Dark Energy: Theory and Observation," de Gruyter, Berlin/Boston, contains background and cosmological simulation plots. Group data and scaled plots are in our new article: A. D. Chernin, P. Teerikorpi, V. P. Dolgachev, A. A. Kanter, L. M. Domozhilova, M. J. Valtonen, and G. G. Byrd, 2012, Astronomy Reports, Vol. 56 , p. 653-669.

A method to associate all possible combinations of genetic and environmental factors using GxE landscape plot.

PubMed

Nagaie, Satoshi; Ogishima, Soichi; Nakaya, Jun; Tanaka, Hiroshi

2015-01-01

Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis. GxE - Gene-environment interactions, GWAS - Genome-wide association study, MAFs - Minor allele frequencies, SNPs - Single nucleotide polymorphisms, EWAS - Environment-wide association study, FDR - False discovery rate, JPT+CHB - HapMap population of Japanese in Tokyo, Japan - Han Chinese in Beijing.

Van Allen Probes Science Gateway: Single-Point Access to Long-Term Radiation Belt Measurements and Space Weather Nowcasting

NASA Astrophysics Data System (ADS)

Romeo, G.; Barnes, R. J.; Ukhorskiy, A. Y.; Sotirelis, T.; Stephens, G.

2017-12-01

The Science Gateway gives single-point access to over 4.5 years of comprehensive wave and particle measurements from the Van Allen Probes NASA twin-spacecraft mission. The Gateway provides a set of visualization and data analysis tools including: HTML5-based interactive visualization of high-level data products from all instrument teams in the form of: line plots, orbital content plots, dynamical energy spectra, L-shell context plots (including two-spacecraft plotting), FFT spectra of wave data, solar wind and geomagnetic indices data, etc.; download custom multi-instrument CDF data files of selected data products; publication quality plots of digital data; combined orbit predicts for mission planning and coordination including: Van Allen Probes, MMS, THEMIS, Arase (ERG), Cluster, GOES, Geotail, FIREBIRD; magnetic footpoint calculator for coordination with LEO and ground-based assets; real-time computation and processing of empirical magnetic field models - computation of magnetic ephemeris, computation of adiabatic invariants. Van Allen Probes is the first spacecraft mission to provide a nowcast of the radiation environment in the heart of the radiation belts, where the radiation levels are the highest and most dangerous for spacecraft operations. For this purpose, all instruments continuously broadcast a subset of their science data in real time. Van Allen Probes partners with four foreign institutions who operate ground stations that receive the broadcast: Korea (KASI), the Czech republic (CAS), Argentina (CONAE), and Brazil (INPE). The SpWx broadcast is then collected at APL and delivered to the community via the Science Gateway.

A Comparison of Vertical Stiffness Values Calculated from Different Measures of Center of Mass Displacement in Single-Leg Hopping.

PubMed

Mudie, Kurt L; Gupta, Amitabh; Green, Simon; Hobara, Hiroaki; Clothier, Peter J

2017-02-01

This study assessed the agreement between K vert calculated from 4 different methods of estimating vertical displacement of the center of mass (COM) during single-leg hopping. Healthy participants (N = 38) completed a 10-s single-leg hopping effort on a force plate, with 3D motion of the lower limb, pelvis, and trunk captured. Derived variables were calculated for a total of 753 hop cycles using 4 methods, including: double integration of the vertical ground reaction force, law of falling bodies, a marker cluster on the sacrum, and a segmental analysis method. Bland-Altman plots demonstrated that K vert calculated using segmental analysis and double integration methods have a relatively small bias (0.93 kN⋅m -1 ) and 95% limits of agreement (-1.89 to 3.75 kN⋅m -1 ). In contrast, a greater bias was revealed between sacral marker cluster and segmental analysis (-2.32 kN⋅m -1 ), sacral marker cluster and double integration (-3.25 kN⋅m -1 ), and the law of falling bodies compared with all methods (17.26-20.52 kN⋅m -1 ). These findings suggest the segmental analysis and double integration methods can be used interchangeably for the calculation of K vert during single-leg hopping. The authors propose the segmental analysis method to be considered the gold standard for the calculation of K vert during single-leg, on-the-spot hopping.

A study on the impact of hydroxypropyl methylcellulose on the viscosity of PEG melt suspensions using surface plots and principal component analysis.

PubMed

Oh, Ching Mien; Heng, Paul Wan Sia; Chan, Lai Wah

2015-04-01

An understanding of the rheological behaviour of polymer melt suspensions is crucial in pharmaceutical manufacturing, especially when processed by spray congealing or melt extruding. However, a detailed comparison of the viscosities at each and every temperature and concentration between the various grades of adjuvants in the formulation will be tedious and time-consuming. Therefore, the statistical method, principal component analysis (PCA), was explored in this study. The composite formulations comprising polyethylene glycol (PEG) 3350 and hydroxypropyl methylcellulose (HPMC) of ten different grades (K100 LV, K4M, K15M, K100M, E15 LV, E50 LV, E4M, F50 LV, F4M and Methocel VLV) at various concentrations were prepared and their viscosities at different temperatures determined. Surface plots showed that concentration of HPMC had a greater effect on the viscosity compared to temperature. Particle size and size distribution of HPMC played an important role in the viscosity of melt suspensions. Smaller particles led to a greater viscosity than larger particles. PCA was used to evaluate formulations of different viscosities. The complex viscosity profiles of the various formulations containing HPMC were successfully classified into three clusters of low, moderate and high viscosity. Formulations within each group showed similar viscosities despite differences in grade or concentration of HPMC. Formulations in the low viscosity cluster were found to be sprayable. PCA was able to differentiate the complex viscosity profiles of different formulations containing HPMC in an efficient and time-saving manner and provided an excellent visualisation of the data.

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses.

PubMed

Montenegro-Burke, J Rafael; Phommavongsay, Thiery; Aisporna, Aries E; Huan, Tao; Rinehart, Duane; Forsberg, Erica; Poole, Farris L; Thorgersen, Michael P; Adams, Michael W W; Krantz, Gregory; Fields, Matthew W; Northen, Trent R; Robbins, Paul D; Niedernhofer, Laura J; Lairson, Luke; Benton, H Paul; Siuzdak, Gary

2016-10-04

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

PubMed Central

2016-01-01

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process. Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism. PMID:27560777

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

DOE PAGES

Montenegro-Burke, J. Rafael; Phommavongsay, Thiery; Aisporna, Aries E.; ...

2016-08-25

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process.more » Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.« less

Smartphone Analytics: Mobilizing the Lab into the Cloud for Omic-Scale Analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montenegro-Burke, J. Rafael; Phommavongsay, Thiery; Aisporna, Aries E.

Active data screening is an integral part of many scientific activities, and mobile technologies have greatly facilitated this process by minimizing the reliance on large hardware instrumentation. In order to meet with the increasingly growing field of metabolomics and heavy workload of data processing, we designed the first remote metabolomic data screening platform for mobile devices. Two mobile applications (apps), XCMS Mobile and METLIN Mobile, facilitate access to XCMS and METLIN, which are the most important components in the computer-based XCMS Online platforms. These mobile apps allow for the visualization and analysis of metabolic data throughout the entire analytical process.more » Specifically, XCMS Mobile and METLIN Mobile provide the capabilities for remote monitoring of data processing, real time notifications for the data processing, visualization and interactive analysis of processed data (e.g., cloud plots, principle component analysis, box-plots, extracted ion chromatograms, and hierarchical cluster analysis), and database searching for metabolite identification. These apps, available on Apple iOS and Google Android operating systems, allow for the migration of metabolomic research onto mobile devices for better accessibility beyond direct instrument operation. The utility of XCMS Mobile and METLIN Mobile functionalities was developed and is demonstrated here through the metabolomic LC-MS analyses of stem cells, colon cancer, aging, and bacterial metabolism.« less

The Effect of Resolution on Detecting Visually Salient Preattentive Features

DTIC Science & Technology

2015-06-01

resolutions in descending order (a–e). The plot compiles the areas of interest displayed in the images and each symbol represents 1 of the images. Data...to particular regions in a scene by highly salient 2 features, for example, the color of the flower discussed in the previous example. These...descending order (a–e). The plot compiles the areas of interest displayed in the images and each symbol represents 1 of the images. Data clusters

Inference from clustering with application to gene-expression microarrays.

PubMed

Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

2002-01-01

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

Automatised data quality monitoring of the LHCb Vertex Locator

NASA Astrophysics Data System (ADS)

Bel, L.; Crocombe, A. Ch.; Gersabeck, M.; Pearce, A.; Majewski, M.; Szumlak, T.

2017-10-01

The LHCb Vertex Locator (VELO) is a silicon strip semiconductor detector operating at just 8mm distance to the LHC beams. Its 172,000 strips are read at a frequency of 1.1 MHz and processed by off-detector FPGAs followed by a PC cluster that reduces the event rate to about 10 kHz. During the second run of the LHC, which lasts from 2015 until 2018, the detector performance will undergo continued change due to radiation damage effects. This necessitates a detailed monitoring of the data quality to avoid adverse effects on the physics analysis performance. The VELO monitoring infrastructure has been re-designed compared to the first run of the LHC when it was based on manual checks. The new system is based around an automatic analysis framework, which monitors the performance of new data as well as long-term trends and using dedicated algorithms flags issues whenever they arise. The new analysis framework then analyses the plots that are produced by these algorithms. One of its tasks is to perform custom comparisons between the newly processed data and that from reference runs. The most-likely scenario in which this analysis would identify an issue is the parameters of the readout electronics no longer being optimal and requiring retuning. The data of the monitoring plots can be reduced further, e.g. by evaluating averages, and these quantities are input to long-term trending. This is used to detect slow variation of quantities, which are not detectable by the comparison of two nearby runs. Such gradual change is what is expected due to radiation damage effects. It is essential to detect these changes early such that measures can be taken, e.g. adjustments of the operating voltage, to prevent any impact on the quality of high-level quantities and thus on physics analyses. The plots as well as the analysis results and trends are made available through graphical user interfaces (GUIs). These GUIs are dynamically configured by a single configuration that determines the choice and arrangement of plots and trends and ensures a common look and feel.

Phylodynamic Analysis Revealed That Epidemic of CRF07_BC Strain in Men Who Have Sex with Men Drove Its Second Spreading Wave in China.

PubMed

Zhang, Min; Jia, Dijing; Li, Hanping; Gui, Tao; Jia, Lei; Wang, Xiaolin; Li, Tianyi; Liu, Yongjian; Bao, Zuoyi; Liu, Siyang; Zhuang, Daomin; Li, Jingyun; Li, Lin

2017-10-01

CRF07_BC was originally formed in Yunnan province of China in 1980s and spread quickly in injecting drug users (IDUs). In recent years, it has been introduced into men who have sex with men (MSM) and become the most dominant strain in China. In this study, we performed a comprehensively phylodynamic analysis of CRF07_BC sequences from China. All CRF07_BC sequences identified in China were retrieved from database. More sequences obtained in our laboratory were added to make the dataset more representative. A maximum-likelihood (ML) tree was constructed with PhyML3.0. Maximum clade credibility (MCC) tree and effective population size were predicted by using Markov Chains Monte Carlo sampling method with Beast software. A total of 610 CRF07_BC sequences coving 1,473 bp of the gag gene (from 817 to 2,289 according to HXB2 calculator) were included into the dataset. Three epidemic clusters were identified; two clusters comprised sequences from IDUs, while one cluster mainly contained sequences from MSMs. The time of the most recent common ancestor of clusters that composed of sequences from MSMs was estimated to be in 2000. Two rapid spreading waves of effective population size of CRF07_BC infections were identified in the skyline plot. The second wave coincided with the expanding of MSM cluster. The results indicated that the control of CRF07_BC infections in MSMs would help to decrease its epidemic in China.

A Typology of Interprofessional Teamwork in Acute Geriatric Care: A Study in 55 units in Belgium.

PubMed

Piers, Ruth D; Versluys, Karen J J; Devoghel, Johan; Lambrecht, Sophie; Vyt, André; Van Den Noortgate, Nele J

2017-09-01

To explore the quality of interprofessional teamwork in acute geriatric care and to build a model of team types. Cross-sectional multicenter study. Acute geriatric units in Belgium. Team members of different professional backgrounds. Perceptions of interprofessional teamwork among team members of 55 acute geriatric units in Belgium were measured using a survey covering collaborative practice and experience, managerial coaching and open team culture, shared reflection and decision-making, patient files facilitating teamwork, members' belief in the power of teamwork, and members' comfort in reporting incidents. Cluster analysis was used to determine types of interprofessional teamwork. Professions and clusters were compared using analysis of variance. The overall response rate was 60%. Of the 890 respondents, 71% were nursing professionals, 20% other allied health professionals, 5% physicians, and 4% logistic and administrative staff. More than 70% of respondents scored highly on interprofessional teamwork competencies, consultation, experiences, meetings, management, and results. Fewer than 55% scored highly on items about shared reflection and decision-making, reporting incidents from a colleague, and patient files facilitating interprofessional teamwork. Nurses in this study rated shared reflection and decision-making lower than physicians on the same acute geriatric units (P < .001). Using the mean score on each of the six areas, four clusters that differed significantly in all areas were identified using hierarchical cluster analysis and scree plot analysis (P < .001). Interprofessional teamwork in acute geriatric units is satisfactory, but shared reflection and decision-making needs improvement. Four types of interprofessional teamwork are identified and can be used to benchmark the teamwork of individual teams. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data

PubMed Central

Zeng, Beiyan; Chen, Yiping P.; Smith, Oscar H.

2003-01-01

Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r2 test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed. PMID:18629292

Assessing the hydraulic connection between fresh water aquifers and unconventional gas production using methane and stable isotopes

NASA Astrophysics Data System (ADS)

Iverach, Charlotte P.; Cendón, Dioni I.; Hankin, Stuart I.; Lowry, Dave; Fisher, Rebecca E.; France, James L.; Nisbet, Euan G.; Baker, Andy; Kelly, Bryce F. J.

2015-04-01

Unconventional gas developments pose a risk to groundwater quality and quantity in adjacent or overlying aquifers. To manage these risks there is a need to measure the background concentration of indicator groundwater chemicals and to map pathways of hydraulic connectivity between aquifers. This study presents methane (CH4) concentration and isotopic composition, dissolved organic carbon concentration ([DOC]) and tritium (3H) activity data from an area of expanding coal seam gas (CSG) exploration and production (Condamine Catchment, south-east Queensland, Australia). The target formation for gas production within the Condamine Catchment is the Walloon Coal Measures (WCM). This is a 700 m thick, low-rank CSG resource, which consists of numerous thin discontinuous lenses of coal separated by very fine-to medium-grained sandstone, siltstone, and mudstone, with minor calcareous sandstone, impure limestone and ironstone. The thickness of the coal makes up less than 10% of the total thickness of the unit. The WCM are overlain by sandstone formations, which form part of the Great Artesian Basin (GAB). The Condamine Alluvium fills a paleo-valley carved through the above formations. A combination of groundwater and degassing air samples were collected from irrigation bores and government groundwater monitoring boreholes. Degassing air samples were collected using an SKC 222-2301 air pump, which pumped the gas into 3 L Tedlar bags. The groundwater was analysed for 3H and [DOC]. A mobile CH4 survey was undertaken to continuously sample air in and around areas of agricultural and unconventional gas production. The isotopic signature of gas from the WCM was determined by sampling gas that was off-gassing from a co-produced water holding pond as it was the largest emission that could be directly linked to the WCM. This was used to determine the source signature of the CH4 from the WCM. We used Keeling plots to identify the source signature of the gas sampled. For the borehole samples these plots assume that there are only two sources of CH4, each with a unique isotopic signature. When the two sources mix in varying proportions they will plot along a straight line in the Keeling plot. Geometric mean displacement was used to fit a regression line and determine the intercept value. Within the Keeling plot, samples clustered according to their 3H and [DOC] values. One cluster is associated with near surface biological processes, while the other cluster can be attributed to gas sourced from the WCM. This indicates that in places there is hydraulic connectivity between the WCM and the overlying Condamine Alluvium. The results from this case study demonstrate that measuring 3H activity, [DOC] and CH4 concentrations in combination with CH4 isotopic analysis can provide an early indicator of hydraulic connectivity in areas of expanding unconventional gas development.

An accurate and computationally efficient algorithm for ground peak identification in large footprint waveform LiDAR data

NASA Astrophysics Data System (ADS)

Zhuang, Wei; Mountrakis, Giorgos

2014-09-01

Large footprint waveform LiDAR sensors have been widely used for numerous airborne studies. Ground peak identification in a large footprint waveform is a significant bottleneck in exploring full usage of the waveform datasets. In the current study, an accurate and computationally efficient algorithm was developed for ground peak identification, called Filtering and Clustering Algorithm (FICA). The method was evaluated on Land, Vegetation, and Ice Sensor (LVIS) waveform datasets acquired over Central NY. FICA incorporates a set of multi-scale second derivative filters and a k-means clustering algorithm in order to avoid detecting false ground peaks. FICA was tested in five different land cover types (deciduous trees, coniferous trees, shrub, grass and developed area) and showed more accurate results when compared to existing algorithms. More specifically, compared with Gaussian decomposition, the RMSE ground peak identification by FICA was 2.82 m (5.29 m for GD) in deciduous plots, 3.25 m (4.57 m for GD) in coniferous plots, 2.63 m (2.83 m for GD) in shrub plots, 0.82 m (0.93 m for GD) in grass plots, and 0.70 m (0.51 m for GD) in plots of developed areas. FICA performance was also relatively consistent under various slope and canopy coverage (CC) conditions. In addition, FICA showed better computational efficiency compared to existing methods. FICA's major computational and accuracy advantage is a result of the adopted multi-scale signal processing procedures that concentrate on local portions of the signal as opposed to the Gaussian decomposition that uses a curve-fitting strategy applied in the entire signal. The FICA algorithm is a good candidate for large-scale implementation on future space-borne waveform LiDAR sensors.

On the rebound: soil organic carbon stocks can bounce back to near forest levels when agroforests replace agriculture in southern India

NASA Astrophysics Data System (ADS)

Hombegowda, H. C.; van Straaten, O.; Köhler, M.; Hölscher, D.

2015-08-01

Tropical agroforestry has an enormous potential to sequester carbon while simultaneously producing agricultural yields and tree products. The amount of soil organic carbon (SOC) sequestered is however influenced by the type of the agroforestry system established, the soil and climatic conditions and management. In this regional scale study, we utilized a chronosequence approach to investigate how SOC stocks changed when the original forests are converted to agriculture, and then subsequently to four different agroforestry systems (AFSs): homegarden, coffee, coconut and mango. In total we established 224 plots in 56 plot clusters across four climate zones in southern India. Each plot cluster consisted of four plots: a natural forest reference plot, an agriculture reference and two of the same AFS types of two ages (30-60 years and > 60 years). The conversion of forest to agriculture resulted in a large loss the original SOC stock (50-61 %) in the top meter of soil depending on the climate zone. The establishment of homegarden and coffee AFSs on agriculture land caused SOC stocks to rebound to near forest levels, while in mango and coconut AFSs the SOC stock increased only slightly above the agriculture stock. The most important variable regulating SOC stocks and its changes was tree basal area, possibly indicative of organic matter inputs. Furthermore, climatic variables such as temperature and precipitation, and soil variables such as clay fraction and soil pH were likewise all important regulators of SOC and SOC stock changes. Lastly, we found a strong correlation between tree species diversity in homegarden and coffee AFSs and SOC stocks, highlighting possibilities to increase carbon stocks by proper tree species assemblies.

The association between chromaticity, phenolics, carotenoids, and in vitro antioxidant activity of frozen fruit pulp in Brazil: an application of chemometrics.

PubMed

Zielinski, Acácio Antonio Ferreira; Ávila, Suelen; Ito, Vivian; Nogueira, Alessandro; Wosiacki, Gilvan; Haminiuk, Charles Windson Isidoro

2014-04-01

A total of 19 Brazilian frozen pulps from the following fruits: açai (Euterpe oleracea), blackberry (Rubus sp.), cajá (Spondias mombin), cashew (Anacardium occidentale), cocoa (Theobroma cacao), coconut (Cocos nucifera), grape (Vitis sp.), graviola (Annona muricata), guava (Psidium guajava), papaya (Carica papaya), peach (Prunus persica), pineapple (Ananas comosus), pineapple and mint (A. comosus and Mentha spicata), red fruits (Rubus sp. and Fragaria sp.), seriguela (Spondias purpurea), strawberry (Fragaria sp.), tamarind (Tamarindus indica), umbu (Spondias tuberosa), and yellow passion fruit (Passiflora edulis) were analyzed in terms of chromaticity, phenolic compounds, carotenoids, and in vitro antioxidant activity using ferric reducing antioxidant power (FRAP) and 1,1-diphenyl-2-picrylhydrazyl (DPPH) assays. Data were processed using principal component analysis (PCA) and hierarchical cluster analysis (HCA). Antioxidant capacity was measured by DPPH and FRAP assays, which showed significant (P < 0.01) correlation with total phenolic compounds (r = 0.88 and 0.70, respectively), total flavonoids (r = 0.63 and 0.81, respectively), and total monomeric anthocyanins (r = 0.59 and 0.73, respectively). PCA explained 74.82% of total variance of data, and the separation into 3 groups in a scatter plot was verified. Three clusters also suggested by HCA, corroborated with PCA, in which cluster 3 was formed by strawberry, red fruits, blackberry, açaí, and grape pulps. This cluster showed the highest contents of total phenolic compounds, total flavonoids, and antioxidant activity. © 2014 Institute of Food Technologists®

Impact of Regulation on Spectral Clustering

DTIC Science & Technology

2014-07-22

the eigenvector values. The regularization parameter was taken to be n. The shaded blue and pink regions corresponds to the nodes belonging to the two...values. As before, the shaded blue and pink regions corresponds to the nodes belonging to the two strong clusters. For plots (a) & (b) the blue line... pink regions corresponds to the nodes belonging to the liberal and conservative blogs respectively. insensitive for large τ . In this case 70% of the

Multilevel models for cost-effectiveness analyses that use cluster randomised trial data: An approach to model choice.

PubMed

Ng, Edmond S-W; Diaz-Ordaz, Karla; Grieve, Richard; Nixon, Richard M; Thompson, Simon G; Carpenter, James R

2016-10-01

Multilevel models provide a flexible modelling framework for cost-effectiveness analyses that use cluster randomised trial data. However, there is a lack of guidance on how to choose the most appropriate multilevel models. This paper illustrates an approach for deciding what level of model complexity is warranted; in particular how best to accommodate complex variance-covariance structures, right-skewed costs and missing data. Our proposed models differ according to whether or not they allow individual-level variances and correlations to differ across treatment arms or clusters and by the assumed cost distribution (Normal, Gamma, Inverse Gaussian). The models are fitted by Markov chain Monte Carlo methods. Our approach to model choice is based on four main criteria: the characteristics of the data, model pre-specification informed by the previous literature, diagnostic plots and assessment of model appropriateness. This is illustrated by re-analysing a previous cost-effectiveness analysis that uses data from a cluster randomised trial. We find that the most useful criterion for model choice was the deviance information criterion, which distinguishes amongst models with alternative variance-covariance structures, as well as between those with different cost distributions. This strategy for model choice can help cost-effectiveness analyses provide reliable inferences for policy-making when using cluster trials, including those with missing data. © The Author(s) 2013.

Assessment of self-organizing maps to analyze sole-carbon source utilization profiles.

PubMed

Leflaive, Joséphine; Céréghino, Régis; Danger, Michaël; Lacroix, Gérard; Ten-Hage, Loïc

2005-07-01

The use of community-level physiological profiles obtained with Biolog microplates is widely employed to consider the functional diversity of bacterial communities. Biolog produces a great amount of data which analysis has been the subject of many studies. In most cases, after some transformations, these data were investigated with classical multivariate analyses. Here we provided an alternative to this method, that is the use of an artificial intelligence technique, the Self-Organizing Maps (SOM, unsupervised neural network). We used data from a microcosm study of algae-associated bacterial communities placed in various nutritive conditions. Analyses were carried out on the net absorbances at two incubation times for each substrates and on the chemical guild categorization of the total bacterial activity. Compared to Principal Components Analysis and cluster analysis, SOM appeared as a valuable tool for community classification, and to establish clear relationships between clusters of bacterial communities and sole-carbon sources utilization. Specifically, SOM offered a clear bidimensional projection of a relatively large volume of data and were easier to interpret than plots commonly obtained with multivariate analyses. They would be recommended to pattern the temporal evolution of communities' functional diversity.

The Phasor Approach to Fluorescence Lifetime Imaging Analysis

PubMed Central

Digman, Michelle A.; Caiolfa, Valeria R.; Zamai, Moreno; Gratton, Enrico

2008-01-01

Changing the data representation from the classical time delay histogram to the phasor representation provides a global view of the fluorescence decay at each pixel of an image. In the phasor representation we can easily recognize the presence of different molecular species in a pixel or the occurrence of fluorescence resonance energy transfer. The analysis of the fluorescence lifetime imaging microscopy (FLIM) data in the phasor space is done observing clustering of pixels values in specific regions of the phasor plot rather than by fitting the fluorescence decay using exponentials. The analysis is instantaneous since is not based on calculations or nonlinear fitting. The phasor approach has the potential to simplify the way data are analyzed in FLIM, paving the way for the analysis of large data sets and, in general, making the FLIM technique accessible to the nonexpert in spectroscopy and data analysis. PMID:17981902

PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

PubMed

Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

2018-05-22

Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques.

PubMed

Tahir, Haroon Elrasheid; Xiaobo, Zou; Xiaowei, Huang; Jiyong, Shi; Mariod, Abdalbasit Adam

2016-09-01

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography-mass spectrometry (GC-MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of codon usage bias of envelope glycoprotein genes in nuclear polyhedrosis virus (NPV) and its relation to evolution.

PubMed

Zhao, Yongchao; Zheng, Hao; Xu, Anying; Yan, Donghua; Jiang, Zijian; Qi, Qi; Sun, Jingchen

2016-08-24

Analysis of codon usage bias is an extremely versatile method using in furthering understanding of the genetic and evolutionary paths of species. Codon usage bias of envelope glycoprotein genes in nuclear polyhedrosis virus (NPV) has remained largely unexplored at present. Hence, the codon usage bias of NPV envelope glycoprotein was analyzed here to reveal the genetic and evolutionary relationships between different viral species in baculovirus genus. A total of 9236 codons from 18 different species of NPV of the baculovirus genera were used to perform this analysis. Glycoprotein of NPV exhibits weaker codon usage bias. Neutrality plot analysis and correlation analysis of effective number of codons (ENC) values indicate that natural selection is the main factor influencing codon usage bias, and that the impact of mutation pressure is relatively smaller. Another cluster analysis shows that the kinship or evolutionary relationships of these viral species can be divided into two broad categories despite all of these 18 species are from the same baculovirus genus. There are many elements that can affect codon bias, such as the composition of amino acids, mutation pressure, natural selection, gene expression level, and etc. In the meantime, cluster analysis also illustrates that codon usage bias of virus envelope glycoprotein can serve as an effective means of evolutionary classification in baculovirus genus.

Effects of logging and recruitment on community phylogenetic structure in 32 permanent forest plots of Kampong Thom, Cambodia

PubMed Central

Toyama, Hironori; Kajisa, Tsuyoshi; Tagane, Shuichiro; Mase, Keiko; Chhang, Phourin; Samreth, Vanna; Ma, Vuthy; Sokh, Heng; Ichihashi, Ryuji; Onoda, Yusuke; Mizoue, Nobuya; Yahara, Tetsukazu

2015-01-01

Ecological communities including tropical rainforest are rapidly changing under various disturbances caused by increasing human activities. Recently in Cambodia, illegal logging and clear-felling for agriculture have been increasing. Here, we study the effects of logging, mortality and recruitment of plot trees on phylogenetic community structure in 32 plots in Kampong Thom, Cambodia. Each plot was 0.25 ha; 28 plots were established in primary evergreen forests and four were established in secondary dry deciduous forests. Measurements were made in 1998, 2000, 2004 and 2010, and logging, recruitment and mortality of each tree were recorded. We estimated phylogeny using rbcL and matK gene sequences and quantified phylogenetic α and β diversity. Within communities, logging decreased phylogenetic diversity, and increased overall phylogenetic clustering and terminal phylogenetic evenness. Between communities, logging increased phylogenetic similarity between evergreen and deciduous plots. On the other hand, recruitment had opposite effects both within and between communities. The observed patterns can be explained by environmental homogenization under logging. Logging is biased to particular species and larger diameter at breast height, and forest patrol has been effective in decreasing logging. PMID:25561669

Effects of logging and recruitment on community phylogenetic structure in 32 permanent forest plots of Kampong Thom, Cambodia.

PubMed

Toyama, Hironori; Kajisa, Tsuyoshi; Tagane, Shuichiro; Mase, Keiko; Chhang, Phourin; Samreth, Vanna; Ma, Vuthy; Sokh, Heng; Ichihashi, Ryuji; Onoda, Yusuke; Mizoue, Nobuya; Yahara, Tetsukazu

2015-02-19

Ecological communities including tropical rainforest are rapidly changing under various disturbances caused by increasing human activities. Recently in Cambodia, illegal logging and clear-felling for agriculture have been increasing. Here, we study the effects of logging, mortality and recruitment of plot trees on phylogenetic community structure in 32 plots in Kampong Thom, Cambodia. Each plot was 0.25 ha; 28 plots were established in primary evergreen forests and four were established in secondary dry deciduous forests. Measurements were made in 1998, 2000, 2004 and 2010, and logging, recruitment and mortality of each tree were recorded. We estimated phylogeny using rbcL and matK gene sequences and quantified phylogenetic α and β diversity. Within communities, logging decreased phylogenetic diversity, and increased overall phylogenetic clustering and terminal phylogenetic evenness. Between communities, logging increased phylogenetic similarity between evergreen and deciduous plots. On the other hand, recruitment had opposite effects both within and between communities. The observed patterns can be explained by environmental homogenization under logging. Logging is biased to particular species and larger diameter at breast height, and forest patrol has been effective in decreasing logging. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Performance analysis of deciduous morphology for detecting biological siblings.

PubMed

Paul, Kathleen S; Stojanowski, Christopher M

2015-08-01

Family-centered burial practices influence cemetery structure and can represent social group composition in both modern and ancient contexts. In ancient sites dental phenotypic data are often used as proxies for underlying genotypes to identify potential biological relatives. Here, we test the performance of deciduous dental morphological traits for differentiating sibling pairs from unrelated individuals from the same population. We collected 46 deciduous morphological traits for 69 sibling pairs from the Burlington Growth Centre's long term Family Study. Deciduous crown features were recorded following published standards. After variable winnowing, inter-individual Euclidean distances were generated using 20 morphological traits. To determine whether sibling pairs are more phenotypically similar than expected by chance we used bootstrap resampling of distances to generate P values. Multidimensional scaling (MDS) plots were used to evaluate the degree of clustering among sibling pairs. Results indicate an average distance between siblings of 0.252, which is significantly less than 9,999 replicated averages of 69 resampled pseudo-distances generated from: 1) a sample of non-relative pairs (P < 0.001), and 2) a sample of relative and non-relative pairs (P < 0.001). MDS plots indicate moderate to strong clustering among siblings; families occupied 3.83% of the multidimensional space on average (versus 63.10% for the total sample). Deciduous crown morphology performed well in identifying related sibling pairs. However, there was considerable variation in the extent to which different families exhibited similarly low levels of phenotypic divergence. © 2015 Wiley Periodicals, Inc.

Reservoir zonation based on statistical analyses: A case study of the Nubian sandstone, Gulf of Suez, Egypt

NASA Astrophysics Data System (ADS)

El Sharawy, Mohamed S.; Gaafar, Gamal R.

2016-12-01

Both reservoir engineers and petrophysicists have been concerned about dividing a reservoir into zones for engineering and petrophysics purposes. Through decades, several techniques and approaches were introduced. Out of them, statistical reservoir zonation, stratigraphic modified Lorenz (SML) plot and the principal component and clustering analyses techniques were chosen to apply on the Nubian sandstone reservoir of Palaeozoic - Lower Cretaceous age, Gulf of Suez, Egypt, by using five adjacent wells. The studied reservoir consists mainly of sandstone with some intercalation of shale layers with varying thickness from one well to another. The permeability ranged from less than 1 md to more than 1000 md. The statistical reservoir zonation technique, depending on core permeability, indicated that the cored interval of the studied reservoir can be divided into two zones. Using reservoir properties such as porosity, bulk density, acoustic impedance and interval transit time indicated also two zones with an obvious variation in separation depth and zones continuity. The stratigraphic modified Lorenz (SML) plot indicated the presence of more than 9 flow units in the cored interval as well as a high degree of microscopic heterogeneity. On the other hand, principal component and cluster analyses, depending on well logging data (gamma ray, sonic, density and neutron), indicated that the whole reservoir can be divided at least into four electrofacies having a noticeable variation in reservoir quality, as correlated with the measured permeability. Furthermore, continuity or discontinuity of the reservoir zones can be determined using this analysis.

Normal versus High Tension Glaucoma: A Comparison of Functional and Structural Defects

PubMed Central

Thonginnetra, Oraorn; Greenstein, Vivienne C.; Chu, David; Liebmann, Jeffrey M.; Ritch, Robert; Hood, Donald C.

2009-01-01

Purpose To compare visual field defects obtained with both multifocal visual evoked potential (mfVEP) and Humphrey visual field (HVF) techniques to topographic optic disc measurements in patients with normal tension glaucoma (NTG) and high tension glaucoma (HTG). Methods We studied 32 patients with NTG and 32 with HTG. All patients had reliable 24-2 HVFs with a mean deviation (MD) of −10 dB or better, a glaucomatous optic disc and an abnormal HVF in at least one eye. Multifocal VEPs were obtained from each eye and probability plots created. The mfVEP and HVF probability plots were divided into a central 10-degree (radius) and an outer arcuate subfield in both superior and inferior hemifields. Cluster analyses and counts of abnormal points were performed in each subfield. Optic disc images were obtained with the Heidelberg Retina Tomograph III (HRT III). Eleven stereometric parameters were calculated. Moorfields regression analysis (MRA) and the glaucoma probability score (GPS) were performed. Results There were no significant differences in MD and PSD values between NTG and HTG eyes. However, NTG eyes had a higher percentage of abnormal test points and clusters of abnormal points in the central subfields on both mfVEP and HVF than HTG eyes. For HRT III, there were no significant differences in the 11 stereometric parameters or in the MRA and GPS analyses of the optic disc images. Conclusions The visual field data suggest more localized and central defects for NTG than HTG. PMID:19223786

Photoelectron spectroscopy of color centers in negatively charged cesium iodide nanocrystals

NASA Astrophysics Data System (ADS)

Sarkas, Harry W.; Kidder, Linda H.; Bowen, Kit H.

1995-01-01

We present the photoelectron spectra of negatively charged cesium iodide nanocrystals recorded using 2.540 eV photons. The species examined were produced using an inert gas condensation cluster ion source, and they ranged in size from (CsI)-n=13 to nanocrystal anions comprised of 330 atoms. Nanocrystals showing two distinct types of photoemission behavior were observed. For (CsI)-n=13 and (CsI)-n=36-165, a plot of cluster anion photodetachment threshold energies vs n-1/3 gives a straight line extrapolating (at n-1/3=0, i.e., n=∞) to 2.2 eV, the photoelectric threshold energy for F centers in bulk cesium iodide. The linear extrapolation of the cluster anion data to the corresponding bulk property implies that the electron localization in these gas-phase nanocrystals is qualitatively similar to that of F centers in extended alkali halide crystals. These negatively charged cesium iodide nanocrystals are thus shown to support embryonic forms of F centers, which mature with increasing cluster size toward condensed phase impurity centers. Under an alternative set of source conditions, nanocrystals were produced which showed significantly lower photodetachment thresholds than the aforementioned F-center cluster anions. For these species, containing 83-131 atoms, a plot of their cluster anion photodetachment threshold energies versus n-1/3 gives a straight line which extrapolates to 1.4 eV. This value is in accord with the expected photoelectric threshold energy for F' centers in bulk cesium iodide, i.e., color centers with two excess electrons in a single defect site. These nanocrystals are interpreted to be the embryonic F'-center containing species, Cs(CsI)-n=41-65.

Heavy particle decay studies using different versions of nuclear potentials

NASA Astrophysics Data System (ADS)

Santhosh, K. P.; Sukumaran, Indu

2017-10-01

The heavy particle decay from 212-240Pa , 219-245Np , 228-246Pu , 230-249Am , and 232-252Cm leading to doubly magic 208Pb and its neighboring nuclei have been studied using fourteen versions of nuclear potentials. The study has shown that the barrier penetrability as well as the decay half-lives are found to vary with the nuclear potential used. The investigated decay events of the emission of the clusters 22Ne , 24Ne , 26Mg , 28Mg , 32Si and 33Si are not experimentally detected yet but may be detectable in the future. As most of the half-lives predicted are found to lie within the experimental upper limit, T 1/2 < 1030 s, our predictions will be a guide to future experimental design. The GN plots studied are linear for different cluster emissions from different parents with varying slopes and intercepts. Also, it is to be noted that the linearity of the GN plots is unaltered using different nuclear potentials. The universal curve studied ( log10 T 1/2 vs. -ln P for various clusters emitted from various parents shows a linear behavior with the same slope and intercept irrespective of the nuclear potential used.

A new computer code for discrete fracture network modelling

NASA Astrophysics Data System (ADS)

Xu, Chaoshui; Dowd, Peter

2010-03-01

The authors describe a comprehensive software package for two- and three-dimensional stochastic rock fracture simulation using marked point processes. Fracture locations can be modelled by a Poisson, a non-homogeneous, a cluster or a Cox point process; fracture geometries and properties are modelled by their respective probability distributions. Virtual sampling tools such as plane, window and scanline sampling are included in the software together with a comprehensive set of statistical tools including histogram analysis, probability plots, rose diagrams and hemispherical projections. The paper describes in detail the theoretical basis of the implementation and provides a case study in rock fracture modelling to demonstrate the application of the software.

Swarm v2: highly-scalable and high-resolution amplicon clustering.

PubMed

Mahé, Frédéric; Rognes, Torbjørn; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

2015-01-01

Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks.

Genetic diversity analysis of cyanogenic potential (CNp) of root among improved genotypes of cassava using simple sequence repeat markers.

PubMed

Moyib, O K; Mkumbira, J; Odunola, O A; Dixon, A G

2012-12-01

Cyanogenic potential (CNp) of cassava constitutes a serious problem for over 500 million people who rely on the crop as their main source of calories. Genetic diversity is a key to successful crop improvement for breeding new improved variability for target traits. Forty-three improved genotypes of cassava developed by International Institute of Tropical Agriculture (ITA), Ibadan, were characterized for CNp trait using 35 Simple Sequence.Repeat (SSR) markers. Essential colorimetry picric test was used for evaluation of CNp on a color scale of 1 to 14. The CNp scores obtained ranged from 3 to 9, with a mean score of 5.48 (+/- 0.09) based on Statistical Analysis System (SAS) package. TMS M98/ 0068 (4.0 +/- 0.25) was identified as the best genotype with low CNp while TMS M98/0028 (7.75 +/- 0.25) was the worst. The 43 genotypes were assigned into 7 phenotypic groups based on rank-sum analysis in SAS. Dissimilarity analysis representatives for windows generated a phylogenetic tree with 5 clusters which represented hybridizing groups. Each of the clusters (except 4) contained low CNp genotypes that could be used for improving the high CNp genotypes in the same or near cluster. The scatter plot of the genotypes showed that there was little or no demarcation for phenotypic CNp groupings in the molecular groupings. The result of this study demonstrated that SSR markers are powerful tools for the assessment of genetic variability, and proper identification and selection of parents for genetic improvement of low CNp trait among the IITA cassava collection.

Inelastic lepton-deuteron scattering: Possible coherent effects

NASA Astrophysics Data System (ADS)

Yen, G. D.; Vary, J. P.

1989-07-01

Electron-deuteron data exhibit some unusual secondary peaks in the plots of νW2 versus Bjorken x. It is our spectulation that these peaks are evidence of interference between three-quark and the six-quark cluster contributions to the inclusive data.

An Analysis of Rich Cluster Redshift Survey Data for Large Scale Structure Studies

NASA Astrophysics Data System (ADS)

Slinglend, K.; Batuski, D.; Haase, S.; Hill, J.

1994-12-01

The results from the COBE satellite show the existence of structure on scales on the order of 10% or more of the horizon scale of the universe. Rich clusters of galaxies from Abell's catalog show evidence of structure on scales of 100 Mpc and may hold the promise of confirming structure on the scale of the COBE result. However, many Abell clusters have zero or only one measured redshift, so present knowledge of their three dimensional distribution has quite large uncertainties. The shortage of measured redshifts for these clusters may also mask a problem of projection effects corrupting the membership counts for the clusters. Our approach in this effort has been to use the MX multifiber spectrometer on the Steward 2.3m to measure redshifts of at least ten galaxies in each of 80 Abell cluster fields with richness class R>= 1 and mag10 <= 16.8 (estimated z<= 0.12) and zero or one measured redshifts. This work will result in a deeper, more complete (and reliable) sample of positions of rich clusters. Our primary intent for the sample is for two-point correlation and other studies of the large scale structure traced by these clusters in an effort to constrain theoretical models for structure formation. We are also obtaining enough redshifts per cluster so that a much better sample of reliable cluster velocity dispersions will be available for other studies of cluster properties. To date, we have collected such data for 64 clusters, and for most of them, we have seven or more cluster members with redshifts, allowing for reliable velocity dispersion calculations. Velocity histograms and stripe density plots for several interesting cluster fields are presented, along with summary tables of cluster redshift results. Also, with 10 or more redshifts in most of our cluster fields (30({') } square, just about an `Abell diameter' at z ~ 0.1) we have investigated the extent of projection effects within the Abell catalog in an effort to quantify and understand how this may effect the Abell sample.

GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

PubMed

Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy

2011-08-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data*

PubMed Central

Rigbolt, Kristoffer T. G.; Vanselow, Jens T.; Blagoev, Blagoy

2011-01-01

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net. PMID:21602510

Spatiotemporal analysis of indigenous and imported dengue fever cases in Guangdong province, China.

PubMed

Li, Zhongjie; Yin, Wenwu; Clements, Archie; Williams, Gail; Lai, Shengjie; Zhou, Hang; Zhao, Dan; Guo, Yansha; Zhang, Yonghui; Wang, Jinfeng; Hu, Wenbiao; Yang, Weizhong

2012-06-12

Dengue fever has been a major public health concern in China since it re-emerged in Guangdong province in 1978. This study aimed to explore spatiotemporal characteristics of dengue fever cases for both indigenous and imported cases during recent years in Guangdong province, so as to identify high-risk areas of the province and thereby help plan resource allocation for dengue interventions. Notifiable cases of dengue fever were collected from all 123 counties of Guangdong province from 2005 to 2010. Descriptive temporal and spatial analysis were conducted, including plotting of seasonal distribution of cases, and creating choropleth maps of cumulative incidence by county. The space-time scan statistic was used to determine space-time clusters of dengue fever cases at the county level, and a geographical information system was used to visualize the location of the clusters. Analysis were stratified by imported and indigenous origin. 1658 dengue fever cases were recorded in Guangdong province during the study period, including 94 imported cases and 1564 indigenous cases. Both imported and indigenous cases occurred more frequently in autumn. The areas affected by the indigenous and imported cases presented a geographically expanding trend over the study period. The results showed that the most likely cluster of imported cases (relative risk = 7.52, p < 0.001) and indigenous cases (relative risk = 153.56, p < 0.001) occurred in the Pearl River Delta Area; while a secondary cluster of indigenous cases occurred in one district of the Chao Shan Area (relative risk = 471.25, p < 0.001). This study demonstrated that the geographic range of imported and indigenous dengue fever cases has expanded over recent years, and cases were significantly clustered in two heavily urbanised areas of Guangdong province. This provides the foundation for further investigation of risk factors and interventions in these high-risk areas.

Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries.

PubMed

Muntaner, Carles; Chung, Haejoo; Benach, Joan; Ng, Edwin

2012-04-18

An important contribution of the social determinants of health perspective has been to inquire about non-medical determinants of population health. Among these, labour market regulations are of vital significance. In this study, we investigate the labour market regulations among low- and middle-income countries (LMICs) and propose a labour market taxonomy to further understand population health in a global context. Using Gross National Product per capita, we classify 113 countries into either low-income (n = 71) or middle-income (n = 42) strata. Principal component analysis of three standardized indicators of labour market inequality and poverty is used to construct 2 factor scores. Factor score reliability is evaluated with Cronbach's alpha. Using these scores, we conduct a hierarchical cluster analysis to produce a labour market taxonomy, conduct zero-order correlations, and create box plots to test their associations with adult mortality, healthy life expectancy, infant mortality, maternal mortality, neonatal mortality, under-5 mortality, and years of life lost to communicable and non-communicable diseases. Labour market and health data are retrieved from the International Labour Organization's Key Indicators of Labour Markets and World Health Organization's Statistical Information System. Six labour market clusters emerged: Residual (n = 16), Emerging (n = 16), Informal (n = 10), Post-Communist (n = 18), Less Successful Informal (n = 22), and Insecure (n = 31). Primary findings indicate: (i) labour market poverty and population health is correlated in both LMICs; (ii) association between labour market inequality and health indicators is significant only in low-income countries; (iii) Emerging (e.g., East Asian and Eastern European countries) and Insecure (e.g., sub-Saharan African nations) clusters are the most advantaged and disadvantaged, respectively, with the remaining clusters experiencing levels of population health consistent with their labour market characteristics. The labour market regulations of LMICs appear to be important social determinant of population health. This study demonstrates the heuristic value of understanding the labour markets of LMICs and their health effects using exploratory taxonomy approaches.

Pilot study assessing differentiation of steatosis hepatis, hepatic iron overload, and combined disease using two-point dixon MRI at 3 T: in vitro and in vivo results of a 2D decomposition technique.

PubMed

Boll, Daniel T; Marin, Daniele; Redmon, Grace M; Zink, Stephen I; Merkle, Elmar M

2010-04-01

The purpose of our study was to evaluate whether two-point Dixon MRI using a 2D decomposition technique facilitates metabolite differentiation between lipids and iron in standardized in vitro liver phantoms with in vivo patient validation and allows semiquantitative in vitro assessment of metabolites associated with steatosis, iron overload, and combined disease. The acrylamide-based phantoms were made to reproduce the T1- and T2-weighted MRI appearances of physiologic hepatic parenchyma and hepatic steatosis-iron overload by the admixture of triglycerides and ferumoxides. Combined disease was simulated using joint admixtures of triglycerides and ferumoxides at various concentrations. For phantom validation, 30 patients were included, of whom 10 had steatosis, 10 had iron overload, and 10 had no liver disease. For MRI an in-phase/opposed-phase T1-weighted sequence with TR/TE(opposed-phase)/TE(in-phase) of 4.19/1.25/2.46 was used. Fat/water series were obtained by Dixon-based algorithms. In-phase and opposed-phase and fat/water ratios were calculated. Statistical cluster analysis assessed ratio pairs of physiologic liver, steatosis, iron overload, and combined disease in 2D metabolite discrimination plots. Statistical assessment proved that metabolite decomposition in phantoms simulating steatosis (1.77|0.22; in-phase/opposed-phase|fat/water ratios), iron overload (0.75|0.21), and healthy control subjects (1.09|0.05) formed three clusters with distinct ratio pairs. Patient validation for hepatic steatosis (3.29|0.51), iron overload (0.56|0.41), and normal control subjects (0.99|0.05) confirmed this clustering (p < 0.001). One-dimensional analysis assessing in vitro combined disease only with in-phase/opposed-phase ratios would have failed to characterize metabolites. The 2D analysis plotting in-phase/opposed-phase and fat/water ratios (2.16|0.59) provided accurate semiquantitative metabolite decomposition (p < 0.001). MR Dixon imaging facilitates metabolite decomposition of intrahepatic lipids and iron using in vitro phantoms with in vivo patient validation. The proposed decomposition technique identified distinct in-phase/opposed-phase and fat/water ratios for in vitro steatosis, iron overload, and combined disease.

Method of Continuous Variations: Applications of Job Plots to the Study of Molecular Associations in Organometallic Chemistry[**

PubMed Central

Renny, Joseph S.; Tomasevich, Laura L.; Tallmadge, Evan H.; Collum, David B.

2014-01-01

Applications of the method of continuous variations—MCV or the Method of Job—to problems of interest to organometallic chemists are described. MCV provides qualitative and quantitative insights into the stoichiometries underlying association of m molecules of A and n molecules of B to form AmBn. Applications to complex ensembles probe associations that form metal clusters and aggregates. Job plots in which reaction rates are monitored provide relative stoichiometries in rate-limiting transition structures. In a specialized variant, ligand- or solvent-dependent reaction rates are dissected into contributions in both the ground states and transition states, which affords insights into the full reaction coordinate from a single Job plot. Gaps in the literature are identified and critiqued. PMID:24166797

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2016-12-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Functionally relevant protein motions: Extracting basin-specific collective coordinates from molecular dynamics trajectories

NASA Astrophysics Data System (ADS)

Pan, Patricia Wang; Dickson, Russell J.; Gordon, Heather L.; Rothstein, Stuart M.; Tanaka, Shigenori

2005-01-01

Functionally relevant motion of proteins has been associated with a number of atoms moving in a concerted fashion along so-called "collective coordinates." We present an approach to extract collective coordinates from conformations obtained from molecular dynamics simulations. The power of this technique for differentiating local structural fuctuations between classes of conformers obtained by clustering is illustrated by analyzing nanosecond-long trajectories for the response regulator protein Spo0F of Bacillus subtilis, generated both in vacuo and using an implicit-solvent representation. Conformational clustering is performed using automated histogram filtering of the inter-Cα distances. Orthogonal (varimax) rotation of the vectors obtained by principal component analysis of these interresidue distances for the members of individual clusters is key to the interpretation of collective coordinates dominating each conformational class. The rotated loadings plots isolate significant variation in interresidue distances, and these are associated with entire mobile secondary structure elements. From this we infer concerted motions of these structural elements. For the Spo0F simulations employing an implicit-solvent representation, collective coordinates obtained in this fashion are consistent with the location of the protein's known active sites and experimentally determined mobile regions.

Screening molecular associations with lipid membranes using natural abundance 13C cross-polarization magic-angle spinning NMR and principal component analysis.

PubMed

Middleton, David A; Hughes, Eleri; Madine, Jillian

2004-08-11

We describe an NMR approach for detecting the interactions between phospholipid membranes and proteins, peptides, or small molecules. First, 1H-13C dipolar coupling profiles are obtained from hydrated lipid samples at natural isotope abundance using cross-polarization magic-angle spinning NMR methods. Principal component analysis of dipolar coupling profiles for synthetic lipid membranes in the presence of a range of biologically active additives reveals clusters that relate to different modes of interaction of the additives with the lipid bilayer. Finally, by representing profiles from multiple samples in the form of contour plots, it is possible to reveal statistically significant changes in dipolar couplings, which reflect perturbations in the lipid molecules at the membrane surface or within the hydrophobic interior.

User Guide for the Plotting Software for the Los Alamos National Laboratory Nuclear Weapons Analysis Tools Version 2.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cleland, Timothy James

The Los Alamos National Laboratory Plotting Software for the Nuclear Weapons Analysis Tools is a Java™ application based upon the open source library JFreeChart. The software provides a capability for plotting data on graphs with a rich variety of display options while allowing the viewer interaction via graph manipulation and scaling to best view the data. The graph types include XY plots, Date XY plots, Bar plots and Histogram plots.

Quantifying innovation in surgery.

PubMed

Hughes-Hallett, Archie; Mayer, Erik K; Marcus, Hani J; Cundy, Thomas P; Pratt, Philip J; Parston, Greg; Vale, Justin A; Darzi, Ara W

2014-08-01

The objectives of this study were to assess the applicability of patents and publications as metrics of surgical technology and innovation; evaluate the historical relationship between patents and publications; develop a methodology that can be used to determine the rate of innovation growth in any given health care technology. The study of health care innovation represents an emerging academic field, yet it is limited by a lack of valid scientific methods for quantitative analysis. This article explores and cross-validates 2 innovation metrics using surgical technology as an exemplar. Electronic patenting databases and the MEDLINE database were searched between 1980 and 2010 for "surgeon" OR "surgical" OR "surgery." Resulting patent codes were grouped into technology clusters. Growth curves were plotted for these technology clusters to establish the rate and characteristics of growth. The initial search retrieved 52,046 patents and 1,801,075 publications. The top performing technology cluster of the last 30 years was minimally invasive surgery. Robotic surgery, surgical staplers, and image guidance were the most emergent technology clusters. When examining the growth curves for these clusters they were found to follow an S-shaped pattern of growth, with the emergent technologies lying on the exponential phases of their respective growth curves. In addition, publication and patent counts were closely correlated in areas of technology expansion. This article demonstrates the utility of publically available patent and publication data to quantify innovations within surgical technology and proposes a novel methodology for assessing and forecasting areas of technological innovation.

Identifying Changes of Complex Flood Dynamics with Recurrence Analysis

NASA Astrophysics Data System (ADS)

Wendi, D.; Merz, B.; Marwan, N.

2016-12-01

Temporal changes in flood hazard system are known to be difficult to detect and attribute due to multiple drivers that include complex processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defense, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. Moreover hydrological time series (i.e. discharge) are often subject to measurement errors, such as rating curve error especially in the case of extremes where observation are actually derived through extrapolation. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. Sensitivity of the common measurement errors and noise on recurrence analysis will also be analyzed and evaluated against conventional methods. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic to certain flood events.

Multi-Spacecraft Analysis with Generic Visualization Tools

NASA Astrophysics Data System (ADS)

Mukherjee, J.; Vela, L.; Gonzalez, C.; Jeffers, S.

2010-12-01

To handle the needs of scientists today and in the future, software tools are going to have to take better advantage of the currently available hardware. Specifically, computing power, memory, and disk space have become cheaper, while bandwidth has become more expensive due to the explosion of online applications. To overcome these limitations, we have enhanced our Southwest Data Display and Analysis System (SDDAS) to take better advantage of the hardware by utilizing threads and data caching. Furthermore, the system was enhanced to support a framework for adding data formats and data visualization methods without costly rewrites. Visualization tools can speed analysis of many common scientific tasks and we will present a suite of tools that encompass the entire process of retrieving data from multiple data stores to common visualizations of the data. The goals for the end user are ease of use and interactivity with the data and the resulting plots. The data can be simultaneously plotted in a variety of formats and/or time and spatial resolutions. The software will allow one to slice and separate data to achieve other visualizations. Furthermore, one can interact with the data using the GUI or through an embedded language based on the Lua scripting language. The data presented will be primarily from the Cluster and Mars Express missions; however, the tools are data type agnostic and can be used for virtually any type of data.

Thermal helium clusters at 3.2 Kelvin in classical and semiclassical simulations

NASA Astrophysics Data System (ADS)

Schulte, J.

1993-03-01

The thermodynamic stability of4He4-13 at 3.2 K is investigated with the classical Monte Carlo method, with the semiclassical path-integral Monte Carlo (PIMC) method, and with the semiclassical all-order many-body method. In the all-order many-body simulation the dipole-dipole approximation including short-range correction is used. The resulting stability plots are discussed and related to recent TOF experiments by Stephens and King. It is found that with classical Monte Carlo of course the characteristics of the measured mass spectrum cannot be resolved. With PIMC, switching on more and more quantum mechanics. by raising the number of virtual time steps results in more structure in the stability plot, but this did not lead to sufficient agreement with the TOF experiment. Only the all-order many-body method resolved the characteristic structures of the measured mass spectrum, including magic numbers. The result shows the influence of quantum statistics and quantum mechanics on the stability of small neutral helium clusters.

Seed: a user-friendly tool for exploring and visualizing microbial community data.

PubMed

Beck, Daniel; Dennis, Christopher; Foster, James A

2015-02-15

In this article we present Simple Exploration of Ecological Data (Seed), a data exploration tool for microbial communities. Seed is written in R using the Shiny library. This provides access to powerful R-based functions and libraries through a simple user interface. Seed allows users to explore ecological datasets using principal coordinate analyses, scatter plots, bar plots, hierarchal clustering and heatmaps. Seed is open source and available at https://github.com/danlbek/Seed. danlbek@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

BRepertoire: a user-friendly web server for analysing antibody repertoire data.

PubMed

Margreitter, Christian; Lu, Hui-Chun; Townsend, Catherine; Stewart, Alexander; Dunn-Walters, Deborah K; Fraternali, Franca

2018-04-14

Antibody repertoire analysis by high throughput sequencing is now widely used, but a persisting challenge is enabling immunologists to explore their data to discover discriminating repertoire features for their own particular investigations. Computational methods are necessary for large-scale evaluation of antibody properties. We have developed BRepertoire, a suite of user-friendly web-based software tools for large-scale statistical analyses of repertoire data. The software is able to use data preprocessed by IMGT, and performs statistical and comparative analyses with versatile plotting options. BRepertoire has been designed to operate in various modes, for example analysing sequence-specific V(D)J gene usage, discerning physico-chemical properties of the CDR regions and clustering of clonotypes. Those analyses are performed on the fly by a number of R packages and are deployed by a shiny web platform. The user can download the analysed data in different table formats and save the generated plots as image files ready for publication. We believe BRepertoire to be a versatile analytical tool that complements experimental studies of immune repertoires. To illustrate the server's functionality, we show use cases including differential gene usage in a vaccination dataset and analysis of CDR3H properties in old and young individuals. The server is accessible under http://mabra.biomed.kcl.ac.uk/BRepertoire.

Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

NASA Astrophysics Data System (ADS)

Elangasinghe, M. A.; Singhal, N.; Dirks, K. N.; Salmond, J. A.; Samarasinghe, S.

2014-09-01

This paper uses artificial neural networks (ANN), combined with k-means clustering, to understand the complex time series of PM10 and PM2.5 concentrations at a coastal location of New Zealand based on data from a single site. Out of available meteorological parameters from the network (wind speed, wind direction, solar radiation, temperature, relative humidity), key factors governing the pattern of the time series concentrations were identified through input sensitivity analysis performed on the trained neural network model. The transport pathways of particulate matter under these key meteorological parameters were further analysed through bivariate concentration polar plots and k-means clustering techniques. The analysis shows that the external sources such as marine aerosols and local sources such as traffic and biomass burning contribute equally to the particulate matter concentrations at the study site. These results are in agreement with the results of receptor modelling by the Auckland Council based on Positive Matrix Factorization (PMF). Our findings also show that contrasting concentration-wind speed relationships exist between marine aerosols and local traffic sources resulting in very noisy and seemingly large random PM10 concentrations. The inclusion of cluster rankings as an input parameter to the ANN model showed a statistically significant (p < 0.005) improvement in the performance of the ANN time series model and also showed better performance in picking up high concentrations. For the presented case study, the correlation coefficient between observed and predicted concentrations improved from 0.77 to 0.79 for PM2.5 and from 0.63 to 0.69 for PM10 and reduced the root mean squared error (RMSE) from 5.00 to 4.74 for PM2.5 and from 6.77 to 6.34 for PM10. The techniques presented here enable the user to obtain an understanding of potential sources and their transport characteristics prior to the implementation of costly chemical analysis techniques or advanced air dispersion models.

Negative ion photoelectron spectroscopy of solvated electron cluster anions, (H2O){/n -} and (NH3){/n -}

NASA Astrophysics Data System (ADS)

Lee, G. H.; Arnold, S. T.; Eaton, J. G.; Sarkas, H. W.; Bowen, K. H.; Ludewigt, C.; Haberland, H.

1991-03-01

The photodetachment spectra of (H2O){/n =2-69/-} and (NH3){/n =41-1100/-} have been recorded, and vertical detachment energies (VDEs) were obtained from the spectra. For both systems, the cluster anion VDEs increase smoothly with increasing sizes and most species plot linearly with n -1/3, extrapolating to a VDE ( n=∞) value which is very close to the photoelectric threshold energy for the corresponding condensed phase solvated electron system. The linear extrapolation of this data to the analogous condensed phase property suggests that these cluster anions are gas phase counterparts to solvated electrons, i.e. they are embryonic forms of hydrated and ammoniated electrons which mature with increasing cluster size toward condensed phase solvated electrons.

Analysis of β-Subgroup Proteobacterial Ammonia Oxidizer Populations in Soil by Denaturing Gradient Gel Electrophoresis Analysis and Hierarchical Phylogenetic Probing

PubMed Central

Stephen, John R.; Kowalchuk, George A.; Bruns, Mary-Ann V.; McCaig, Allison E.; Phillips, Carol J.; Embley, T. Martin; Prosser, James I.

1998-01-01

A combination of denaturing gradient gel electrophoresis (DGGE) and oligonucleotide probing was used to investigate the influence of soil pH on the compositions of natural populations of autotrophic β-subgroup proteobacterial ammonia oxidizers. PCR primers specific to this group were used to amplify 16S ribosomal DNA (rDNA) from soils maintained for 36 years at a range of pH values, and PCR products were analyzed by DGGE. Genus- and cluster-specific probes were designed to bind to sequences within the region amplified by these primers. A sequence specific to all β-subgroup ammonia oxidizers could not be identified, but probes specific for Nitrosospira clusters 1 to 4 and Nitrosomonas clusters 6 and 7 (J. R. Stephen, A. E. McCaig, Z. Smith, J. I. Prosser, and T. M. Embley, Appl. Environ. Microbiol. 62:4147–4154, 1996) were designed. Elution profiles of probes against target sequences and closely related nontarget sequences indicated a requirement for high-stringency hybridization conditions to distinguish between different clusters. DGGE banding patterns suggested the presence of Nitrosomonas cluster 6a and Nitrosospira clusters 2, 3, and 4 in all soil plots, but results were ambiguous because of overlapping banding patterns. Unambiguous band identification of the same clusters was achieved by combined DGGE and probing of blots with the cluster-specific radiolabelled probes. The relative intensities of hybridization signals provided information on the apparent selection of different Nitrosospira genotypes in samples of soil of different pHs. The signal from the Nitrosospira cluster 3 probe decreased significantly, relative to an internal control probe, with decreasing soil pH in the range of 6.6 to 3.9, while Nitrosospira cluster 2 hybridization signals increased with increasing soil acidity. Signals from Nitrosospira cluster 4 were greatest at pH 5.5, decreasing at lower and higher values, while Nitrosomonas cluster 6a signals did not vary significantly with pH. These findings are in agreement with a previous molecular study (J. R. Stephen, A. E. McCaig, Z. Smith, J. I. Prosser, and T. M. Embley, Appl. Environ. Microbiol 62:4147–4154, 1996) of the same sites, which demonstrated the presence of the same four clusters of ammonia oxidizers and indicated that selection might be occurring for clusters 2 and 3 at acid and neutral pHs, respectively. The two studies used different sets of PCR primers for amplification of 16S rDNA sequences from soil, and the similar findings suggest that PCR bias was unlikely to be a significant factor. The present study demonstrates the value of DGGE and probing for rapid analysis of natural soil communities of β-subgroup proteobacterial ammonia oxidizers, indicates significant pH-associated differences in Nitrosospira populations, and suggests that Nitrosospira cluster 2 may be of significance for ammonia-oxidizing activity in acid soils. PMID:9687457

Microsatellite diversity among the primitive tribes of India

PubMed Central

Mukherjee, Malay B.; Tripathy, V.; Colah, R. B.; Solanki, P. K.; Ghosh, K.; Reddy, B. M.; Mohanty, D.

2009-01-01

The present study was undertaken to determine the extent of diversity at 12 microsatellite short tandem repeat (STR) loci in seven primitive tribal populations of India with diverse linguistic and geographic backgrounds. DNA samples of 160 unrelated individuals were analyzed for 12 STR loci by multiplex polymerase chain reaction (PCR). Gene diversity analysis suggested that the average heterozygosity was uniformly high ( >0.7) in these groups and varied from 0.705 to 0.794. The Hardy-Weinberg equilibrium analysis revealed that these populations were in genetic equilibrium at almost all the loci. The overall GST value was high (GST = 0.051; range between 0.026 and 0.098 among the loci), reflecting the degree of differentiation/heterogeneity of seven populations studied for these loci. The cluster analysis and multidimensional scaling of genetic distances reveal two broad clusters of populations, besides Moolu Kurumba maintaining their distinct genetic identity vis-à-vis other populations. The genetic affinity for the three tribes of the Indo-European family could be explained based on geography and Language but not for the four Dravidian tribes as reflected by the NJT and MDS plots. For the overall data, the insignificant MANTEL correlations between genetic, linguistic and geographic distances suggest that the genetic variation among these tribes is not patterned along geographic and/or linguistic lines. PMID:21088716

[Difference evaluation of three kinds of root of Aconitum carmichaelii in Sichuan based on UPLC analysis of six alkaloids and chemometrics].

PubMed

Qian, Chang-Min; Song, Zhao-Hui; Zhang, Lan-Lan; Zhou, Shui-Ping; Feng, Feng

2013-09-01

An ultra performance liquid chromatography (UPLC) method was established and validated to simultaneously determine the contents of six aconitum alkaloids in mother, daughter and fibrous roots of 19 batches of Aconitum carmichaelii from Sichuan province. The separation of the six alkaloids was achieved on a ACQUITY UPLC BEH C18 (2.1 mm x 100 mm, 1.7 microm) column at 40 degrees C with a mobile phase consisting of acetonitrile in 30 mmol x L(-1) ammonium acetate buffer solution (adjusted to pH 10.0 with aqueous ammonia) in gradient mode. The data and plots showed that the six aconitum alkaloids have different distributions. Four aconitum alkaloids were almost same in mother and daughter root except benzoylmesaconine and mesaconitine, while the fibrous root differed from the other two roots. The comparisons of significant differences of six aconitum alkaloids between the mother and daughter roots definitely demonstrated that benzoylmesaconine and mesaconitine were the representative components. The 38 detecting samples were classified as two clusters by hierarchical clustering analysis (HCA) and principle component analysis (PCA), the results indicated that the mother root was different from the daughter root on chemical material basis. The study might contribute to the reasonable clinical application of A. carmichaelii.

Structural, evolutionary and genetic analysis of the histidine biosynthetic "core" in the genus Burkholderia.

PubMed

Papaleo, Maria Cristiana; Russo, Edda; Fondi, Marco; Emiliani, Giovanni; Frandi, Antonio; Brilli, Matteo; Pastorelli, Roberta; Fani, Renato

2009-12-01

In this work a detailed analysis of the structure, the expression and the organization of his genes belonging to the core of histidine biosynthesis (hisBHAF) in 40 newly determined and 13 available sequences of Burkholderia strains was carried out. Data obtained revealed a strong conservation of the structure and organization of these genes through the entire genus. The phylogenetic analysis showed the monophyletic origin of this gene cluster and indicated that it did not undergo horizontal gene transfer events. The analysis of the intergenic regions, based on the substitution rate, entropy plot and bendability suggested the existence of a putative transcription promoter upstream of hisB, that was supported by the genetic analysis that showed that this cluster was able to complement Escherichia colihisA, hisB, and hisF mutations. Moreover, a preliminary transcriptional analysis and the analysis of microarray data revealed that the expression of the his core was constitutive. These findings are in agreement with the fact that the entire Burkholderiahis operon is heterogeneous, in that it contains "alien" genes apparently not involved in histidine biosynthesis. Besides, they also support the idea that the proteobacterial his operon was piece-wisely assembled, i.e. through accretion of smaller units containing only some of the genes (eventually together with their own promoters) involved in this biosynthetic route. The correlation existing between the structure, organization and regulation of his "core" genes and the function(s) they perform in cellular metabolism is discussed.

A first look at measurement error on FIA plots using blind plots in the Pacific Northwest

Treesearch

Susanna Melson; David Azuma; Jeremy S. Fried

2002-01-01

Measurement error in the Forest Inventory and Analysis work of the Pacific Northwest Station was estimated with a recently implemented blind plot measurement protocol. A small subset of plots was revisited by a crew having limited knowledge of the first crew's measurements. This preliminary analysis of the first 18 months' blind plot data indicates that...

A density management diagram for even-aged ponderosa pine stands

Treesearch

James N. Long; John D. Shaw

2005-01-01

We developed a density management diagram (DMD) for ponderosa pine using Forest Inventory and Analysis (FIA) data. Analysis plots were drawn from all FIA plots in the western United States on which ponderosa pine occurred. A total of 766 plots met the criteria for analysis. Selection criteria were for purity, defined as ponderosa pine basal area 80% of plot basal area...

Start codon targeted (SCoT) and target region amplification polymorphism (TRAP) for evaluating the genetic relationship of Dendrobium species.

PubMed

Feng, Shangguo; He, Refeng; Yang, Sai; Chen, Zhe; Jiang, Mengying; Lu, Jiangjie; Wang, Huizhong

2015-08-10

Two molecular marker systems, start codon targeted (SCoT) and target region amplification polymorphism (TRAP), were used for genetic relationship analysis of 36 Dendrobium species collected from China. Twenty-two selected SCoT primers produced 337 loci, of which 324 (96%) were polymorphic, whereas 13 TRAP primer combinations produced a total of 510 loci, with 500 (97.8%) of them being polymorphic. An average polymorphism information content of 0.953 and 0.983 was detected using the SCoT and TRAP primers, respectively, showing that a high degree of genetic diversity exists among Chinese Dendrobium species. The partition of clusters in the unweighted pair group method with arithmetic mean dendrogram and principal coordinate analysis plot based on the SCoT and TRAP markers was similar and clustered the 36 Dendrobium species into four main groups. Our results will provide useful information for resource protection and will also be useful to improve the current Dendrobium breeding programs. Our results also demonstrate that SCoT and TRAP markers are informative and can be used to evaluate genetic relationships between Dendrobium species. Copyright © 2015 Elsevier B.V. All rights reserved.

Monte Carlo Shower Counter Studies

NASA Technical Reports Server (NTRS)

Snyder, H. David

1991-01-01

Activities and accomplishments related to the Monte Carlo shower counter studies are summarized. A tape of the VMS version of the GEANT software was obtained and installed on the central computer at Gallaudet University. Due to difficulties encountered in updating this VMS version, a decision was made to switch to the UNIX version of the package. This version was installed and used to generate the set of data files currently accessed by various analysis programs. The GEANT software was used to write files of data for positron and proton showers. Showers were simulated for a detector consisting of 50 alternating layers of lead and scintillator. Each file consisted of 1000 events at each of the following energies: 0.1, 0.5, 2.0, 10, 44, and 200 GeV. Data analysis activities related to clustering, chi square, and likelihood analyses are summarized. Source code for the GEANT user subprograms and data analysis programs are provided along with example data plots.

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Hyun Jung; McDonnell, Kevin T.; Zelenyuk, Alla

2014-03-01

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly inmore » high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.« less

PET kinetic analysis --pitfalls and a solution for the Logan plot.

PubMed

Kimura, Yuichi; Naganawa, Mika; Shidahara, Miho; Ikoma, Yoko; Watabe, Hiroshi

2007-01-01

The Logan plot is a widely used algorithm for the quantitative analysis of neuroreceptors using PET because it is easy to use and simple to implement. The Logan plot is also suitable for receptor imaging because its algorithm is fast. However, use of the Logan plot, and interpretation of the formed receptor images should be regarded with caution, because noise in PET data causes bias in the Logan plot estimates. In this paper, we describe the basic concept of the Logan plot in detail and introduce three algorithms for the Logan plot. By comparing these algorithms, we demonstrate the pitfalls of the Logan plot and discuss the solution.

Genetic Variability among Lucerne Cultivars Based on Biochemical (SDS-PAGE) and Morphological Markers

NASA Astrophysics Data System (ADS)

Farshadfar, M.; Farshadfar, E.

The present research was conducted to determine the genetic variability of 18 Lucerne cultivars, based on morphological and biochemical markers. The traits studied were plant height, tiller number, biomass, dry yield, dry yield/biomass, dry leaf/dry yield, macro and micro elements, crude protein, dry matter, crude fiber and ash percentage and SDS- PAGE in seed and leaf samples. Field experiments included 18 plots of two meter rows. Data based on morphological, chemical and SDS-PAGE markers were analyzed using SPSSWIN soft ware and the multivariate statistical procedures: cluster analysis (UPGMA), principal component. Analysis of analysis of variance and mean comparison for morphological traits reflected significant differences among genotypes. Genotype 13 and 15 had the greatest values for most traits. The Genotypic Coefficient of Variation (GCV), Phenotypic Coefficient of Variation (PCV) and Heritability (Hb) parameters for different characters raged from 12.49 to 26.58% for PCV, hence the GCV ranged from 6.84 to 18.84%. The greatest value of Hb was 0.94 for stem number. Lucerne genotypes could be classified, based on morphological traits, into four clusters and 94% of the variance among the genotypes was explained by two PCAs: Based on chemical traits they were classified into five groups and 73.492% of variance was explained by four principal components: Dry matter, protein, fiber, P, K, Na, Mg and Zn had higher variance. Genotypes based on the SDS-PAGE patterns all genotypes were classified into three clusters. The greatest genetic distance was between cultivar 10 and others, therefore they would be suitable parent in a breeding program.

Quantitative Analysis of Technological Innovation in Knee Arthroplasty: Using Patent and Publication Metrics to Identify Developments and Trends.

PubMed

Dalton, David M; Burke, Thomas P; Kelly, Enda G; Curtin, Paul D

2016-06-01

Surgery is in a constant continuum of innovation with refinement of technique and instrumentation. Arthroplasty surgery potentially represents an area with highly innovative process. This study highlights key area of innovation in knee arthroplasty over the past 35 years using patent and publication metrics. Growth rates and patterns are analyzed. Patents are correlated to publications as a measure of scientific support. Electronic patent and publication databases were searched over the interval 1980-2014 for "knee arthroplasty" OR "knee replacement." The resulting patent codes were allocated into technology clusters. Citation analysis was performed to identify any important developments missed on initial analysis. The technology clusters identified were further analyzed, individual repeat searches performed, and growth curves plotted. The initial search revealed 3574 patents and 16,552 publications. The largest technology clusters identified were Unicompartmental, Patient-Specific Instrumentation (PSI), Navigation, and Robotic knee arthroplasties. The growth in patent activity correlated strongly with publication activity (Pearson correlation value 0.892, P < .01), but was growing at a faster rate suggesting a decline in vigilance. PSI, objectively the fastest growing technology in the last 5 years, is currently in a period of exponential growth that began a decade ago. Established technologies in the study have double s-shaped patent curves. Identifying trends in emerging technologies is possible using patent metrics and is useful information for training and regulatory bodies. The decline in ratio of publications to patents and the uninterrupted growth of PSI are developments that may warrant further investigation. Copyright © 2015 Elsevier Inc. All rights reserved.

A heptadecanuclear Mn(III)9Dy(III)8 cluster derived from triethanolamine with two edge sharing supertetrahedra as the core and displaying SMM behaviour.

PubMed

Langley, Stuart K; Moubarakia, Boujemaa; Murray, Keith S

2010-06-07

A heterometallic, heptadecanuclear cluster of formula [Mn(III)9Dy(III)8O8(OH)8(tea)2(teaH)2(teaH2)4(Ac)4(NO3)2(H2O)4](NO3)7·8H2O (1) is reported. The core of 1 displays two edge sharing Mn(III)5Dy(III)5 supertetrahedra and represents one of the largest Mn/4f cluster compound so far reported. Magnetic studies show that 1 displays probable SMM behaviour as observed via non-zero values in the χM''vs T plot.

Patterns of mortality in a montane mixed-conifer forest in San Diego County, California.

PubMed

Freeman, Mary Pyott; Stow, Douglas A; An, Li

2017-10-01

We examine spatial patterns of conifer tree mortality and their changes over time for the montane mixed-conifer forests of San Diego County. These forest areas have recently experienced extensive tree mortality due to multiple factors. A spatial contextual image processing approach was utilized with high spatial resolution digital airborne imagery to map dead trees for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan, and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Mean mortality remained static from 1997 to 2002 (4, 2.2, and 4.2 trees/ha for Palomar, Volcan, and Laguna) and then increased by 2005 to 10.3, 9.7, and 5.2 trees/ha, respectively. The increase in mortality between 2002 and 2005 represents the temporal pattern of a discrete disturbance event, attributable to the 2002-2003 drought. Dead trees are significantly clustered for all dates, based on spatial cluster analysis, indicating that they form distinct groups, as opposed to spatially random single dead trees. Other tests indicate no directional shift or spread of mortality over time, but rather an increase in density. While general temporal and spatial mortality processes are uniform across all study areas, the plot-based species and quantity distribution of mortality, and diameter distributions of dead vs. living trees, vary by study area. The results of this study improve our understanding of stand- to landscape-level forest structure and dynamics, particularly by examining them from the multiple perspectives of field and remotely sensed data. © 2017 by the Ecological Society of America.

ND 2 AV: N-dimensional data analysis and visualization analysis for the National Ignition Campaign

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bremer, Peer -Timo; Maljovec, Dan; Saha, Avishek

Here, one of the biggest challenges in high-energy physics is to analyze a complex mix of experimental and simulation data to gain new insights into the underlying physics. Currently, this analysis relies primarily on the intuition of trained experts often using nothing more sophisticated than default scatter plots. Many advanced analysis techniques are not easily accessible to scientists and not flexible enough to explore the potentially interesting hypotheses in an intuitive manner. Furthermore, results from individual techniques are often difficult to integrate, leading to a confusing patchwork of analysis snippets too cumbersome for data exploration. This paper presents a case study on how a combination of techniques from statistics, machine learning, topology, and visualization can have a significant impact in the field of inertial confinement fusion. We present themore » $$\\mathrm{ND}^2\\mathrm{AV}$$: N-dimensional data analysis and visualization framework, a user-friendly tool aimed at exploiting the intuition and current workflow of the target users. The system integrates traditional analysis approaches such as dimension reduction and clustering with state-of-the-art techniques such as neighborhood graphs and topological analysis, and custom capabilities such as defining combined metrics on the fly. All components are linked into an interactive environment that enables an intuitive exploration of a wide variety of hypotheses while relating the results to concepts familiar to the users, such as scatter plots. $$\\mathrm{ND}^2\\mathrm{AV}$$ uses a modular design providing easy extensibility and customization for different applications. $$\\mathrm{ND}^2\\mathrm{AV}$$ is being actively used in the National Ignition Campaign and has already led to a number of unexpected discoveries.« less

ND 2 AV: N-dimensional data analysis and visualization analysis for the National Ignition Campaign

DOE PAGES

Bremer, Peer -Timo; Maljovec, Dan; Saha, Avishek; ...

2015-07-01

Here, one of the biggest challenges in high-energy physics is to analyze a complex mix of experimental and simulation data to gain new insights into the underlying physics. Currently, this analysis relies primarily on the intuition of trained experts often using nothing more sophisticated than default scatter plots. Many advanced analysis techniques are not easily accessible to scientists and not flexible enough to explore the potentially interesting hypotheses in an intuitive manner. Furthermore, results from individual techniques are often difficult to integrate, leading to a confusing patchwork of analysis snippets too cumbersome for data exploration. This paper presents a case study on how a combination of techniques from statistics, machine learning, topology, and visualization can have a significant impact in the field of inertial confinement fusion. We present themore » $$\\mathrm{ND}^2\\mathrm{AV}$$: N-dimensional data analysis and visualization framework, a user-friendly tool aimed at exploiting the intuition and current workflow of the target users. The system integrates traditional analysis approaches such as dimension reduction and clustering with state-of-the-art techniques such as neighborhood graphs and topological analysis, and custom capabilities such as defining combined metrics on the fly. All components are linked into an interactive environment that enables an intuitive exploration of a wide variety of hypotheses while relating the results to concepts familiar to the users, such as scatter plots. $$\\mathrm{ND}^2\\mathrm{AV}$$ uses a modular design providing easy extensibility and customization for different applications. $$\\mathrm{ND}^2\\mathrm{AV}$$ is being actively used in the National Ignition Campaign and has already led to a number of unexpected discoveries.« less

Swarm v2: highly-scalable and high-resolution amplicon clustering

PubMed Central

Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah

2015-01-01

Previously we presented Swarm v1, a novel and open source amplicon clustering program that produced fine-scale molecular operational taxonomic units (OTUs), free of arbitrary global clustering thresholds and input-order dependency. Swarm v1 worked with an initial phase that used iterative single-linkage with a local clustering threshold (d), followed by a phase that used the internal abundance structures of clusters to break chained OTUs. Here we present Swarm v2, which has two important novel features: (1) a new algorithm for d = 1 that allows the computation time of the program to scale linearly with increasing amounts of data; and (2) the new fastidious option that reduces under-grouping by grafting low abundant OTUs (e.g., singletons and doubletons) onto larger ones. Swarm v2 also directly integrates the clustering and breaking phases, dereplicates sequencing reads with d = 0, outputs OTU representatives in fasta format, and plots individual OTUs as two-dimensional networks. PMID:26713226

Study of II Galactic quadrant of Milky Way Galaxy using open clusters

NASA Astrophysics Data System (ADS)

Bisht, Devendra; Ganesh, Shashikiran; Baliyan, Kiran Singh; Yadav, Ramakant Singh; Durgapal, Alok

2018-04-01

We have made UBV I CCD observations for the open clusters Teutsch 1, Riddle 4 and Czernik 6 using 1.04-m Sampurnanand telescope located at the ARIES observatory (Manora peak, Nainital, India). We have used 2MASS JHKS data for the clusters Teutsch 126, Teutsch 54 and Czernik 3. For the estimation of fundamental parameters, we have plotted radial density profiles, colour-magnitude and colour-colour diagrams. Using these inputs, we have studied the structure of Milky Way Galaxy in the second Galactic quadrant. We have considered the open clusters that are younger than 1 Gyrs and lay in the longitude range from 90 to 180 deg. Our study shows that up to 3.5 Kpc, the Galactic disc bends towards the southern hemisphere while after 3.5 Kpc it bends towards the northern hemisphere. The distribution of reddening with longitude and age shows a decreasing trend with the longitude and age of the clusters. Our study also indicates that younger clusters have more reddening than older ones.

A SURVEY OF CN AND CH VARIATIONS IN GALACTIC GLOBULAR CLUSTERS FROM SLOAN DIGITAL SKY SURVEY SPECTROSCOPY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smolinski, Jason P.; Beers, Timothy C.; Lee, Young Sun

We present a homogeneous survey of the CN and CH band strengths in eight Galactic globular clusters observed during the course of the Sloan Extension for Galactic Understanding and Exploration sub-survey of the Sloan Digital Sky Survey. We confirm the existence of a bimodal CN distribution among red giant branch (RGB) stars in all of the clusters with metallicity greater than [Fe/H] = -1.7; the lowest metallicity cluster with an observed CN bimodality is M53, with [Fe/H] {approx_equal} -2.1. There is also some evidence for individual CN groups on the subgiant branches of M92, M2, and M13, and on themore » RGBs of M92 and NGC 5053. Finally, we quantify the correlation between overall cluster metallicity and the slope of the CN band strength-luminosity plot as a means of further demonstrating the level of CN enrichment in cluster giants. Our results agree well with previous studies reported in the literature.« less

Spike detection, characterization, and discrimination using feature analysis software written in LabVIEW.

PubMed

Stewart, C M; Newlands, S D; Perachio, A A

2004-12-01

Rapid and accurate discrimination of single units from extracellular recordings is a fundamental process for the analysis and interpretation of electrophysiological recordings. We present an algorithm that performs detection, characterization, discrimination, and analysis of action potentials from extracellular recording sessions. The program was entirely written in LabVIEW (National Instruments), and requires no external hardware devices or a priori information about action potential shapes. Waveform events are detected by scanning the digital record for voltages that exceed a user-adjustable trigger. Detected events are characterized to determine nine different time and voltage levels for each event. Various algebraic combinations of these waveform features are used as axis choices for 2-D Cartesian plots of events. The user selects axis choices that generate distinct clusters. Multiple clusters may be defined as action potentials by manually generating boundaries of arbitrary shape. Events defined as action potentials are validated by visual inspection of overlain waveforms. Stimulus-response relationships may be identified by selecting any recorded channel for comparison to continuous and average cycle histograms of binned unit data. The algorithm includes novel aspects of feature analysis and acquisition, including higher acquisition rates for electrophysiological data compared to other channels. The program confirms that electrophysiological data may be discriminated with high-speed and efficiency using algebraic combinations of waveform features derived from high-speed digital records.

Assessing genetic divergence in interspecific hybrids of Aechmea gomosepala and A. recurvata var. recurvata using inflorescence characteristics and sequence-related amplified polymorphism markers.

PubMed

Zhang, F; Ge, Y Y; Wang, W Y; Shen, X L; Yu, X Y

2012-12-03

Conventional hybridization and selection techniques have aided the development of new ornamental crop cultivars. However, little information is available on the genetic divergence of bromeliad hybrids. In the present study, we investigated the genetic variability in interspecific hybrids of Aechmea gomosepala and A. recurvata var. recurvata using inflorescence characteristics and sequence-related amplified polymorphism (SRAP) markers. The morphological analysis showed that the putative hybrids were intermediate between both parental species with respect to inflorescence characteristics. The 16 SRAP primer combinations yield 265 bands, among which 154 (57.72%) were polymorphic. The genetic similarity was an average of 0.59 and ranged from 0.21 to 0.87, indicating moderate genetic divergence among the hybrids. The unweighted pair group method with arithmetic average (UPGMA)-based cluster analysis distinguished the hybrids from their parents with a genetic distance coefficient of 0.54. The cophenetic correlation was 0.93, indicating a good fit between the dendrogram and the original distance matrix. The two-dimensional plot from the principal coordinate analysis showed that the hybrids were intermediately dispersed between both parents, corresponding to the results of the UPGMA cluster and the morphological analysis. These results suggest that SRAP markers could help to identify breeders, characterize F(1) hybrids of bromeliads at an early stage, and expedite genetic improvement of bromeliad cultivars.

Deriving spatial patterns from a novel database of volcanic rock geochemistry in the Virunga Volcanic Province, East African Rift

NASA Astrophysics Data System (ADS)

Poppe, Sam; Barette, Florian; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu

2016-04-01

The Virunga Volcanic Province (VVP) is situated within the western branch of the East-African Rift. The geochemistry and petrology of its' volcanic products has been studied extensively in a fragmented manner. They represent a unique collection of silica-undersaturated, ultra-alkaline and ultra-potassic compositions, displaying marked geochemical variations over the area occupied by the VVP. We present a novel spatially-explicit database of existing whole-rock geochemical analyses of the VVP volcanics, compiled from international publications, (post-)colonial scientific reports and PhD theses. In the database, a total of 703 geochemical analyses of whole-rock samples collected from the 1950s until recently have been characterised with a geographical location, eruption source location, analytical results and uncertainty estimates for each of these categories. Comparative box plots and Kruskal-Wallis H tests on subsets of analyses with contrasting ages or analytical methods suggest that the overall database accuracy is consistent. We demonstrate how statistical techniques such as Principal Component Analysis (PCA) and subsequent cluster analysis allow the identification of clusters of samples with similar major-element compositions. The spatial patterns represented by the contrasting clusters show that both the historically active volcanoes represent compositional clusters which can be identified based on their contrasted silica and alkali contents. Furthermore, two sample clusters are interpreted to represent the most primitive, deep magma source within the VVP, different from the shallow magma reservoirs that feed the eight dominant large volcanoes. The samples from these two clusters systematically originate from locations which 1. are distal compared to the eight large volcanoes and 2. mostly coincide with the surface expressions of rift faults or NE-SW-oriented inherited Precambrian structures which were reactivated during rifting. The lava from the Mugogo eruption of 1957 belongs to these primitive clusters and is the only known to have erupted outside the current rift valley in historical times. We thus infer there is a distributed hazard of vent opening susceptibility additional to the susceptibility associated with the main Virunga edifices. This study suggests that the statistical analysis of such geochemical database may help to understand complex volcanic plumbing systems and the spatial distribution of volcanic hazards in active and poorly known volcanic areas such as the Virunga Volcanic Province.

On the rebound: soil organic carbon stocks can bounce back to near forest levels when agroforests replace agriculture in southern India

NASA Astrophysics Data System (ADS)

Hombegowda, H. C.; van Straaten, O.; Köhler, M.; Hölscher, D.

2016-01-01

Tropical agroforestry has an enormous potential to sequester carbon while simultaneously producing agricultural yields and tree products. The amount of soil organic carbon (SOC) sequestered is influenced by the type of the agroforestry system established, the soil and climatic conditions, and management. In this regional-scale study, we utilized a chronosequence approach to investigate how SOC stocks changed when the original forests are converted to agriculture, and then subsequently to four different agroforestry systems (AFSs): home garden, coffee, coconut and mango. In total we established 224 plots in 56 plot clusters across 4 climate zones in southern India. Each plot cluster consisted of four plots: a natural forest reference, an agriculture reference and two of the same AFS types of two ages (30-60 years and > 60 years). The conversion of forest to agriculture resulted in a large loss the original SOC stock (50-61 %) in the top meter of soil depending on the climate zone. The establishment of home garden and coffee AFSs on agriculture land caused SOC stocks to rebound to near forest levels, while in mango and coconut AFSs the SOC stock increased only slightly above the agriculture SOC stock. The most important variable regulating SOC stocks and its changes was tree basal area, possibly indicative of organic matter inputs. Furthermore, climatic variables such as temperature and precipitation, and soil variables such as clay fraction and soil pH were likewise all important regulators of SOC and SOC stock changes. Lastly, we found a strong correlation between tree species diversity in home garden and coffee AFSs and SOC stocks, highlighting possibilities to increase carbon stocks by proper tree species assemblies.

A Novel Approach to Detect Accelerated Aged and Surface-Mediated Degradation in Explosives by UPLC-ESI-MS.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beppler, Christina L

2015-12-01

A new approach was created for studying energetic material degradation. This approach involved detecting and tentatively identifying non-volatile chemical species by liquid chromatography-mass spectrometry (LC-MS) with multivariate statistical data analysis that form as the CL-20 energetic material thermally degraded. Multivariate data analysis showed clear separation and clustering of samples based on sample group: either pristine or aged material. Further analysis showed counter-clockwise trends in the principal components analysis (PCA), a type of multivariate data analysis, Scores plots. These trends may indicate that there was a discrete shift in the chemical markers as the went from pristine to aged material, andmore » then again when the aged CL-20 mixed with a potentially incompatible material was thermally aged for 4, 6, or 9 months. This new approach to studying energetic material degradation should provide greater knowledge of potential degradation markers in these materials.« less

Rapid quality assessment of Radix Aconiti Preparata using direct analysis in real time mass spectrometry.

PubMed

Zhu, Hongbin; Wang, Chunyan; Qi, Yao; Song, Fengrui; Liu, Zhiqiang; Liu, Shuying

2012-11-08

This study presents a novel and rapid method to identify chemical markers for the quality control of Radix Aconiti Preparata, a world widely used traditional herbal medicine. In the method, the samples with a fast extraction procedure were analyzed using direct analysis in real time mass spectrometry (DART MS) combined with multivariate data analysis. At present, the quality assessment approach of Radix Aconiti Preparata was based on the two processing methods recorded in Chinese Pharmacopoeia for the purpose of reducing the toxicity of Radix Aconiti and ensuring its clinical therapeutic efficacy. In order to ensure the safety and effectivity in clinical use, the processing degree of Radix Aconiti should be well controlled and assessed. In the paper, hierarchical cluster analysis and principal component analysis were performed to evaluate the DART MS data of Radix Aconiti Preparata samples in different processing times. The results showed that the well processed Radix Aconiti Preparata, unqualified processed and the raw Radix Aconiti could be clustered reasonably corresponding to their constituents. The loading plot shows that the main chemical markers having the most influence on the discrimination amongst the qualified and unqualified samples were mainly some monoester diterpenoid aconitines and diester diterpenoid aconitines, i.e. benzoylmesaconine, hypaconitine, mesaconitine, neoline, benzoylhypaconine, benzoylaconine, fuziline, aconitine and 10-OH-mesaconitine. The established DART MS approach in combination with multivariate data analysis provides a very flexible and reliable method for quality assessment of toxic herbal medicine. Copyright © 2012 Elsevier B.V. All rights reserved.

Combining Mixture Components for Clustering*

PubMed Central

Baudry, Jean-Patrick; Raftery, Adrian E.; Celeux, Gilles; Lo, Kenneth; Gottardo, Raphaël

2010-01-01

Model-based clustering consists of fitting a mixture model to data and identifying each cluster with one of its components. Multivariate normal distributions are typically used. The number of clusters is usually determined from the data, often using BIC. In practice, however, individual clusters can be poorly fitted by Gaussian distributions, and in that case model-based clustering tends to represent one non-Gaussian cluster by a mixture of two or more Gaussian distributions. If the number of mixture components is interpreted as the number of clusters, this can lead to overestimation of the number of clusters. This is because BIC selects the number of mixture components needed to provide a good approximation to the density, rather than the number of clusters as such. We propose first selecting the total number of Gaussian mixture components, K, using BIC and then combining them hierarchically according to an entropy criterion. This yields a unique soft clustering for each number of clusters less than or equal to K. These clusterings can be compared on substantive grounds, and we also describe an automatic way of selecting the number of clusters via a piecewise linear regression fit to the rescaled entropy plot. We illustrate the method with simulated data and a flow cytometry dataset. Supplemental Materials are available on the journal Web site and described at the end of the paper. PMID:20953302

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

PubMed Central

Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

2009-01-01

Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors. PMID:19698124

Ecological risks of Aluminum production and contaminated area by red mud in Western Hungary (Ajka)

NASA Astrophysics Data System (ADS)

Rasulov, Oqil; Horváth, Adrienn; Bidló, András; Winkler, Dániel

2016-04-01

In October 2010, Hungary experienced one of the most severe environmental disasters: the dam wall of a red mud depository of an alumina plant in collapsed and more than 1 million m3 of toxic sludge flooded the surrounding area. Red mud is a strongly alkaline (pH of 9-12.5) by-product due to the high NaOH content. Apart from residual minerals and oxides, its components also include heavy metals such as Cu, Zn, Cd, Hg, Pb, Ni, Co. As it has already been assessed, red mud had considerable effect on soil properties and thus on soil biodiversity. The aim of our study was to determine the aftereffects of red mud pollution on the soil mesofauna (Collembola). Study plots were selected in the area affected by the toxic flood, in agricultural and grassland habitats, at different distances (0.3 to 12.5 km) from the contamination source. Control plots of each habitat types were selected for comparative analyses. Soil samples were taken during the summer of 2015, five years after the red mud disaster. From each of the selected plots, 5 soil cores of 100 cm3 volume (3.6 cm in diameter and 10 cm in depth) were sampled from which springtails were extracted within 14 days using a modified Tullgren apparatus. Simultaneously with the Collembola sampling, we collected soil samples on each plots in order to determine soil properties (pH, CaCO3, particle size distribution) and the degree of heavy metal pollution. 25 heavy metals were measured (including total Hg) following the method of total (cc. HNO3 + H2O2-soluble) and bioavailable (NH4-acetate + EDTA-soluble) element content using ICP-OES and AMA 254. The studied habitats presented neutral to moderately alkaline soils (pH 7.2-8.1). Total metal content was higher in the plots formerly affected by red mud flood. The Hg concentration ranged from 0.023 to 1.167 mg.kg-1, exceeding the threshold concentration (0.5 mg.kg-1) defined by Hungarian legislation for toxic trace metals in soil. The collected 1442 Collembola specimens belong to 32 species. Species richness and diversity were the highest in the uncontaminated grassland plots. Abundance was the lowest in the polluted and intensively managed agricultural plots (1167±433 ind./m2), while the most abundant community was found the control grassland plots reaching 10233±1567 ind./m2. Community structure comparison was estimated using cluster analysis based on the Bray-Curtis index, which well emphasises the difference between the habitat types, as well as the separation of the polluted and control sites. CCA analysis revealed that the most sensitive species to the red mud pollution and thus to the increased heavy metal concentration were Mesaphorura macrochaeta and Sminthurinus elegans, while Brachystomella parvula and most Protaphorura spp. appeared to be more tolerant to the changed soil conditions.

Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

PubMed

Batchelder, Kendra A; Tanenbaum, Aaron B; Albert, Seth; Guimond, Lyne; Kestener, Pierre; Arneodo, Alain; Khalil, Andre

2014-01-01

The 2D Wavelet-Transform Modulus Maxima (WTMM) method was used to detect microcalcifications (MC) in human breast tissue seen in mammograms and to characterize the fractal geometry of benign and malignant MC clusters. This was done in the context of a preliminary analysis of a small dataset, via a novel way to partition the wavelet-transform space-scale skeleton. For the first time, the estimated 3D fractal structure of a breast lesion was inferred by pairing the information from two separate 2D projected mammographic views of the same breast, i.e. the cranial-caudal (CC) and mediolateral-oblique (MLO) views. As a novelty, we define the "CC-MLO fractal dimension plot", where a "fractal zone" and "Euclidean zones" (non-fractal) are defined. 118 images (59 cases, 25 malignant and 34 benign) obtained from a digital databank of mammograms with known radiologist diagnostics were analyzed to determine which cases would be plotted in the fractal zone and which cases would fall in the Euclidean zones. 92% of malignant breast lesions studied (23 out of 25 cases) were in the fractal zone while 88% of the benign lesions were in the Euclidean zones (30 out of 34 cases). Furthermore, a Bayesian statistical analysis shows that, with 95% credibility, the probability that fractal breast lesions are malignant is between 74% and 98%. Alternatively, with 95% credibility, the probability that Euclidean breast lesions are benign is between 76% and 96%. These results support the notion that the fractal structure of malignant tumors is more likely to be associated with an invasive behavior into the surrounding tissue compared to the less invasive, Euclidean structure of benign tumors. Finally, based on indirect 3D reconstructions from the 2D views, we conjecture that all breast tumors considered in this study, benign and malignant, fractal or Euclidean, restrict their growth to 2-dimensional manifolds within the breast tissue.

[Heart rate variability study based on a novel RdR RR Intervals Scatter Plot].

PubMed

Lu, Hongwei; Lu, Xiuyun; Wang, Chunfang; Hua, Youyuan; Tian, Jiajia; Liu, Shihai

2014-08-01

On the basis of Poincare scatter plot and first order difference scatter plot, a novel heart rate variability (HRV) analysis method based on scatter plots of RR intervals and first order difference of RR intervals (namely, RdR) was proposed. The abscissa of the RdR scatter plot, the x-axis, is RR intervals and the ordinate, y-axis, is the difference between successive RR intervals. The RdR scatter plot includes the information of RR intervals and the difference between successive RR intervals, which captures more HRV information. By RdR scatter plot analysis of some records of MIT-BIH arrhythmias database, we found that the scatter plot of uncoupled premature ventricular contraction (PVC), coupled ventricular bigeminy and ventricular trigeminy PVC had specific graphic characteristics. The RdR scatter plot method has higher detecting performance than the Poincare scatter plot method, and simpler and more intuitive than the first order difference method.

Accumulating pollutants in conifer needles on an Atlantic island - a case study with Pinus canariensis on Tenerife, Canary Islands.

PubMed

Tausz, Michael; Trummer, Walter; Goessler, Walter; Wonisch, Astrid; Grill, Dieter; Naumann, Simone; Jiménez, Maria Soledad; Morales, Domingo

2005-08-01

Concentrations of potential pollutant elements Na, Cl, and S were investigated in needles of Pinus canariensis grown at 55 field plots in Tenerife. Microelement concentrations (including heavy metals) were measured at a subset of 18 plots. Na and Cl concentrations were high at low elevations (up to 8 mg g(-1) Cl and 5.5 mg g(-1) Na). Na/Cl ratio close to standard seawater indicated sea spray influence up to 1200 m a.s.l. Only at few plots, sulphur concentrations indicated possible pollutant impact. Cluster and correlation analyses identified a related group of V, As, Cr, Fe, Mo, Ni, Cu, Pb, and Al, possibly related to traffic exhaust aggregated with soil particles. Mainly north-eastern, lower elevated plots were exposed to those immissions, but metal concentrations were generally low compared to data from other studies. In conclusion, seawater and soil particles explained most of the element distribution pattern in pine needles in Tenerife, but strong indications for some effect of local sources of air pollutants were detected.

True versus perturbed forest inventory plot locations for modeling: a simulation study

Treesearch

John W. Coulston; Kurt H. Riitters; Ronald E. McRoberts; William D. Smith

2006-01-01

USDA Forest Service Forest Inventory and Analysis plot information is widely used for timber inventories, forest health assessments, and environmental risk analyses. With few exceptions, true plot locations are not revealed; the plot coordinates are manipulated to obscure the location of field plots and thereby preserve plot integrity. The influence of perturbed plot...

Quantitative Analysis of Technological Innovation in Urology.

PubMed

Bhatt, Nikita R; Davis, Niall F; Dalton, David M; McDermott, Ted; Flynn, Robert J; Thomas, Arun Z; Manecksha, Rustom P

2018-01-01

To assess major areas of technological innovation in urology in the last 20 years using patent and publication data. Patent and MEDLINE databases were searched between 1980 and 2012 electronically using the terms urology OR urological OR urologist AND "surgeon" OR "surgical" OR "surgery". The patent codes obtained were grouped in technology clusters, further analyzed with individual searches, and growth curves were plotted. Growth rates and patterns were analyzed, and patents were correlated with publications as a measure of scientific support and of clinical adoption. The initial search revealed 417 patents and 20,314 publications. The top 5 technology clusters in descending order were surgical instruments including urinary catheters, minimally invasive surgery (MIS), lasers, robotic surgery, and image guidance. MIS and robotic surgery were the most emergent clusters in the last 5 years. Publication and patent growth rates were closely correlated (Pearson coefficient 0.78, P <.01), but publication growth rate remained constantly higher than patent growth, suggesting validated scientific support for urologic innovation and adoption into clinical practice. Patent metrics identify emergent technological innovations and such trends are valuable to understand progress in the field of urology. New surgical technologies like robotic surgery and MIS showed exponential growth in the last decade with good scientific vigilance. Copyright © 2017 Elsevier Inc. All rights reserved.

Distant Cluster Hunting. II; A Comparison of X-Ray and Optical Cluster Detection Techniques and Catalogs from the ROSAT Optical X-Ray Survey

NASA Technical Reports Server (NTRS)

Donahue, Megan; Scharf, Caleb A.; Mack, Jennifer; Lee, Y. Paul; Postman, Marc; Rosait, Piero; Dickinson, Mark; Voit, G. Mark; Stocke, John T.

2002-01-01

We present and analyze the optical and X-ray catalogs of moderate-redshift cluster candidates from the ROSA TOptical X-Ray Survey, or ROXS. The survey covers the sky area contained in the fields of view of 23 deep archival ROSA T PSPC pointings, 4.8 square degrees. The cross-correlated cluster catalogs were con- structed by comparing two independent catalogs extracted from the optical and X-ray bandpasses, using a matched-filter technique for the optical data and a wavelet technique for the X-ray data. We cross-identified cluster candidates in each catalog. As reported in Paper 1, the matched-filter technique found optical counter- parts for at least 60% (26 out of 43) of the X-ray cluster candidates; the estimated redshifts from the matched filter algorithm agree with at least 7 of 1 1 spectroscopic confirmations (Az 5 0.10). The matched filter technique. with an imaging sensitivity of ml N 23, identified approximately 3 times the number of candidates (155 candidates, 142 with a detection confidence >3 u) found in the X-ray survey of nearly the same area. There are 57 X-ray candidates, 43 of which are unobscured by scattered light or bright stars in the optical images. Twenty-six of these have fairly secure optical counterparts. We find that the matched filter algorithm, when applied to images with galaxy flux sensitivities of mI N 23, is fairly well-matched to discovering z 5 1 clusters detected by wavelets in ROSAT PSPC exposures of 8000-60,000 s. The difference in the spurious fractions between the optical and X-ray (30%) and IO%, respectively) cannot account for the difference in source number. In Paper I, we compared the optical and X-ray cluster luminosity functions and we found that the luminosity functions are consistent if the relationship between X-ray and optical luminosities is steep (Lx o( L&f). Here, in Paper 11, we present the cluster catalogs and a numerical simulation of the ROXS. We also present color-magnitude plots for several of the cluster candidates, and examine the prominence of the red sequence in each. We find that the X-ray clusters in our survey do not all have a prominent red sequence. We conclude that while the red sequence may be a distinct feature in the color-magnitude plots for virialized massive clusters, it may be less distinct in lower mass clusters of galaxies at even moderate redshifts. Multiple, complementary methods of selecting and defining clusters may be essential, particularly at high redshift where all methods start to run into completeness limits, incomplete understanding of physical evolution, and projection effects.

Recurrence quantification analysis of electrically evoked surface EMG signal.

PubMed

Liu, Chunling; Wang, Xu

2005-01-01

Recurrence Plot is a quite useful tool used in time-series analysis, in particular for measuring unstable periodic orbits embedded in a chaotic dynamical system. This paper introduced the structures of the Recurrence Plot and the ways of the plot coming into being. Then the way of the quantification of the Recurrence Plot is defined. In this paper, one of the possible applications of Recurrence Quantification Analysis (RQA) strategy to the analysis of electrical stimulation evoked surface EMG. The result shows the percent determination is increased along with stimulation intensity.

Characterizing Oscillatory Bursts in Single-Trial EEG Data

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Shah, A. S.; Lakatos, P.; Schroeder, C. E.

2004-01-01

Oscillatory bursts in numerous bands ranging from low (theta) to high frequencies (e.g., gamma) undoubtedly play an important role in cortical dynamics. Largely because of the inadequacy of existing analytic techniques. however, oscillatory bursts and their role in cortical processing remains poorly understood. To study oscillatory bursts effectively one must be able to isolate them and characterize them in the single trial. We describe a series of straightforward analysis techniques that produce useful indices of burst characteristics. First, stimulus-evoked responses are estimated using Differentially Variable Component Analysis (dVCA), and are subtracted from the single-trial. The single-trial characteristics of the evoked responses are stored to identify possible correlations with burst activity. Time-frequency (T-F), or wavelet, analyses are then applied to the single trial residuals. While T-F plots have been used in recent studies to identify and isolate bursts, we go further by fitting each burst in the T-F plot with a two-dimensional Gaussian. This provides a set of burst characteristics, such as, center time. burst duration, center frequency. frequency dispersion. and amplitude, all of which contribute to the accurate characterization of the individual burst. The burst phase can also be estimated. Burst characteristics can be quantified with several standard techniques (e.g.. histogramming and clustering), as well as Bayesian techniques (e.g., blocking) to allow a more parametric description analysis of the characteristics of oscillatory bursts, and the relationships of specific parameters to cortical excitability and stimulus integration.

Master plot analysis of microcracking in graphite/epoxy and graphite/PEEK laminates

NASA Technical Reports Server (NTRS)

Nairn, John A.; Hu, Shoufeng; Bark, Jong Song

1993-01-01

We used a variational stress analysis and an energy release rate failure criterion to construct a master plot analysis of matrix microcracking. In the master plot, the results for all laminates of a single material are predicted to fall on a single line whose slope gives the microcracking toughness of the material. Experimental results from 18 different layups of AS4/3501-6 laminates show that the master plot analysis can explain all observations. In particular, it can explain the differences between microcracking of central 90 deg plies and of free-surface 90 deg plies. Experimental results from two different AS4/PEEK laminates tested at different temperatures can be explained by a modified master plot that accounts for changes in the residual thermal stresses. Finally, we constructed similar master plot analyses for previous literature microcracking models. All microcracking theories that ignore the thickness dependence of the stresses gave poor results.

Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries

PubMed Central

2012-01-01

Background An important contribution of the social determinants of health perspective has been to inquire about non-medical determinants of population health. Among these, labour market regulations are of vital significance. In this study, we investigate the labour market regulations among low- and middle-income countries (LMICs) and propose a labour market taxonomy to further understand population health in a global context. Methods Using Gross National Product per capita, we classify 113 countries into either low-income (n = 71) or middle-income (n = 42) strata. Principal component analysis of three standardized indicators of labour market inequality and poverty is used to construct 2 factor scores. Factor score reliability is evaluated with Cronbach's alpha. Using these scores, we conduct a hierarchical cluster analysis to produce a labour market taxonomy, conduct zero-order correlations, and create box plots to test their associations with adult mortality, healthy life expectancy, infant mortality, maternal mortality, neonatal mortality, under-5 mortality, and years of life lost to communicable and non-communicable diseases. Labour market and health data are retrieved from the International Labour Organization's Key Indicators of Labour Markets and World Health Organization's Statistical Information System. Results Six labour market clusters emerged: Residual (n = 16), Emerging (n = 16), Informal (n = 10), Post-Communist (n = 18), Less Successful Informal (n = 22), and Insecure (n = 31). Primary findings indicate: (i) labour market poverty and population health is correlated in both LMICs; (ii) association between labour market inequality and health indicators is significant only in low-income countries; (iii) Emerging (e.g., East Asian and Eastern European countries) and Insecure (e.g., sub-Saharan African nations) clusters are the most advantaged and disadvantaged, respectively, with the remaining clusters experiencing levels of population health consistent with their labour market characteristics. Conclusions The labour market regulations of LMICs appear to be important social determinant of population health. This study demonstrates the heuristic value of understanding the labour markets of LMICs and their health effects using exploratory taxonomy approaches. PMID:22512892

Hyperspectral remote sensing of paddy crop using insitu measurement and clustering technique

NASA Astrophysics Data System (ADS)

Moharana, S.; Dutta, S.

2014-11-01

Rice Agriculture, mainly cultivated in South Asia regions, is being monitored for extracting crop parameter, crop area, crop growth profile, crop yield using both optical and microwave remote sensing. Hyperspectral data provide more detailed information of rice agriculture. The present study was carried out at the experimental station of the Regional Rainfed Low land Rice Research Station, Assam, India (26.1400° N, 91.7700° E) and the overall climate of the study area comes under Lower Brahmaputra Valley (LBV) Agro Climatic Zones. The hyperspectral measurements were made in the year 2009 from 72 plots that include eight rice varieties along with three different level of nitrogen treatments (50, 100, 150 kg/ha) covering rice transplanting to the crop harvesting period. With an emphasis to varieties, hyperspectral measurements were taken in the year 2014 from 24 plots having 24 rice genotypes with different crop developmental ages. All the measurements were performed using a spectroradiometer with a spectral range of 350-1050 nm under direct sunlight of a cloud free sky and stable condition of the atmosphere covering more than 95 % canopy. In this study, reflectance collected from canopy of rice were expressed in terms of waveforms. Furthermore, generated waveforms were analysed for all combinations of nitrogen applications and varieties. A hierarchical clustering technique was employed to classify these waveforms into different groups. By help of agglomerative clustering algorithm a few number of clusters were finalized for different rice varieties along with nitrogen treatments. By this clustering approach, observational error in spectroradiometer reflectance was also nullified. From this hierarchical clustering, appropriate spectral signature for rice canopy were identified and will help to create rice crop classification accurately and therefore have a prospect to make improved information on rice agriculture at both local and regional scales. From this hierarchical clustering, spectral signature library for rice canopy were identified which will help to create rice crop classification maps and critical wave bands like green (519,559 nm), red (649 nm), red edge (729 nm) and NIR region (779,819 nm) were marked sensitive to nitrogen which will further help in nitrogen mapping of paddy agriculture over therefore have the prospect to make improved informed decisions.

Predicting cotton yield of small field plots in a cotton breeding program using UAV imagery data

NASA Astrophysics Data System (ADS)

Maja, Joe Mari J.; Campbell, Todd; Camargo Neto, Joao; Astillo, Philip

2016-05-01

One of the major criteria used for advancing experimental lines in a breeding program is yield performance. Obtaining yield performance data requires machine picking each plot with a cotton picker, modified to weigh individual plots. Harvesting thousands of small field plots requires a great deal of time and resources. The efficiency of cotton breeding could be increased significantly while the cost could be decreased with the availability of accurate methods to predict yield performance. This work is investigating the feasibility of using an image processing technique using a commercial off-the-shelf (COTS) camera mounted on a small Unmanned Aerial Vehicle (sUAV) to collect normal RGB images in predicting cotton yield on small plot. An orthonormal image was generated from multiple images and used to process multiple, segmented plots. A Gaussian blur was used to eliminate the high frequency component of the images, which corresponds to the cotton pixels, and used image subtraction technique to generate high frequency pixel images. The cotton pixels were then separated using k-means cluster with 5 classes. Based on the current work, the calculated percentage cotton area was computed using the generated high frequency image (cotton pixels) divided by the total area of the plot. Preliminary results showed (five flights, 3 altitudes) that cotton cover on multiple pre-selected 227 sq. m. plots produce an average of 8% which translate to approximately 22.3 kgs. of cotton. The yield prediction equation generated from the test site was then use on a separate validation site and produced a prediction error of less than 10%. In summary, the results indicate that a COTS camera with an appropriate image processing technique can produce results that are comparable to expensive sensors.

Discrimination of Picea chihuahuana Martinez populations on the basis of climatic, edaphic, dendrometric, genetic and population traits

PubMed Central

Dominguez-Guerrero, Iliana Karina; del Rocío Mariscal-Lucero, Samantha; Hernández-Díaz, José Ciro; Heinze, Berthold; Prieto-Ruiz, José Ángel

2017-01-01

Background Picea chihuahuana, which is endemic to Mexico, is currently listed as “Endangered” on the Red List. Chihuahua spruce is only found in the Sierra Madre Occidental (SMO), Mexico. About 42,600 individuals are distributed in forty populations. These populations are fragmented and can be classified into three geographically distinct clusters in the SMO. The total area covered by P. chihuahuana populations is less than 300 ha. A recent study suggested assisted migration as an alternative to the ex situ conservation of P. chihuahuana, taking into consideration the genetic structure and diversity of the populations and the predictions regarding the future climate of the habitat. However, detailed background information is required to enable development of plans for protecting and conserving species and for successful assisted migration. Thus, it is important to identify differences between populations in relation to environmental conditions. The genetic diversity of populations, which affect vigor, evolution and adaptability of the species, must also be considered. In this study, we examined 14 populations of P. chihuahuana, with the overall aim of discriminating the populations and form clusters of this species. Methods Each population was represented by one 50 × 50 m plot established in the center of its respective location. Climate, soil, dasometric, density variables and genetic and species diversities were assessed in these plots for further analyses. The putatively neutral and adaptive AFLP markers were used to calculate genetic diversity. Affinity Propagation (AP) clustering technique and k-means clustering algorithm were used to classify the populations in the optimal number of clusters. Later stepwise binomial logistic regression was applied to test for significant differences in variables of the southern and northern P. chihuahuana populations. Spearman’s correlation test was used to analyze the relationships among all variables studied. Results The binomial logistic regression analysis revealed that seven climate variables, the geographical longitude and sand proportion in the soil separated the southern from northern populations. The northern populations grow in more arid and continental conditions and on soils with lower sand proportion. The mean genetic diversity using all AFLP studied of P. chihuahuana was significantly correlated with the mean temperature in the warmest month, where warmer temperatures are associated to larger genetic diversity. Genetic diversity of P. chihuahuana calculated with putatively adaptive AFLP was not statistically significantly correlated with any environmental factor. Discussion Future reforestation programs should take into account that at least two different groups (the northern and southern cluster) of P. chihuahuana exist, as local adaptation takes place because of different environmental conditions. PMID:28626616

Analytical and experimental investigation of a 1/8-scale dynamic model of the shuttle orbiter. Volume 3B: Supporting data

NASA Technical Reports Server (NTRS)

Mason, P. W.; Harris, H. G.; Zalesak, J.; Bernstein, M.

1974-01-01

The NASA Structural Analysis System (NASTRAN) Model 1 finite element idealization, input data, and detailed analytical results are presented. The data presented include: substructuring analysis for normal modes, plots of member data, plots of symmetric free-free modes, plots of antisymmetric free-free modes, analysis of the wing, analysis of the cargo doors, analysis of the payload, and analysis of the orbiter.

Genetic variability of Brazilian isolates of Alternaria alternata detected by AFLP and RAPD techniques

PubMed Central

Dini-Andreote, Francisco; Pietrobon, Vivian Cristina; Andreote, Fernando Dini; Romão, Aline Silva; Spósito, Marcel Bellato; Araújo, Welington Luiz

2009-01-01

The Alternaria brown spot (ABS) is a disease caused in tangerine plants and its hybrids by the fungus Alternaria alternata f. sp. citri which has been found in Brazil since 2001. Due to the recent occurrence in Brazilian orchards, the epidemiology and genetic variability of this pathogen is still an issue to be addressed. Here it is presented a survey about the genetic variability of this fungus by the characterization of twenty four pathogenic isolates of A. alternata f. sp. citri from citrus plants and four endophytic isolates from mango (one Alternaria tenuissima and three Alternaria arborescens). The application of two molecular markers Random Amplified Polymorphic DNA (RAPD) and Amplified Fragment Length Polymorphism (AFLP) had revealed the isolates clustering in distinct groups when fingerprintings were analyzed by Principal Components Analysis (PCA). Despite the better assessment of the genetic variability through the AFLP, significant modifications in clusters components were not observed, and only slight shifts in the positioning of isolates LRS 39/3 and 25M were observed in PCA plots. Furthermore, in both analyses, only the isolates from lemon plants revealed to be clustered, differently from the absence of clustering for other hosts or plant tissues. Summarizing, both RAPD and AFLP analyses were both efficient to detect the genetic variability within the population of the pathogenic fungus Alternaria spp., supplying information on the genetic variability of this species as a basis for further studies aiming the disease control. PMID:24031413

Characterization of diesel fuel by chemical separation combined with capillary gas chromatography (GC) isotope ratio mass spectrometry (IRMS).

PubMed

Harvey, Scott D; Jarman, Kristin H; Moran, James J; Sorensen, Christina M; Wright, Bob W

2012-09-15

The purpose of this study was to perform a preliminary investigation of compound-specific isotope analysis (CSIA) of diesel fuels to evaluate whether the technique could distinguish diesel samples from different sources/locations. The ability to differentiate or correlate diesel samples could be valuable for discovering fuel tax evasion schemes or for environmental forensic studies. Two urea adduction-based techniques were used to isolate the n-alkanes from the fuel. Both carbon isotope ratio (δ(13)C) and hydrogen isotope ratio (δD) values for the n-alkanes were then determined by CSIA in each sample. The samples investigated had δ(13)C values that ranged from -30.1‰ to -26.8‰, whereas δD values ranged from -83‰ to -156‰. Plots of δD versus δ(13)C with sample n-alkane points connected in order of increasing carbon number gave well-separated clusters with characteristic shapes for each sample. Principal components analysis (PCA) with δ(13)C, δD, or combined δ(13)C and δD data was applied to extract the maximum information content. PCA scores plots could clearly differentiate the samples, thereby demonstrating the potential of this approach for distinguishing (e.g., fingerprinting) fuel samples using δ(13)C and δD values. Copyright © 2012 Elsevier B.V. All rights reserved.

Metabolite profiling and fingerprinting of Suillus species (Basidiomycetes) by electrospray mass spectrometry.

PubMed

Heinke, Ramona; Schöne, Pia; Arnold, Norbert; Wessjohann, Ludger; Schmidt, Jürgen; Schmidt, Jürgen

2014-01-01

The genus Suillus is known for the occurrence of a series of prenylated phenols and boviquinones. The extracts of four different Suillus species [S. bovinus, S. granulatus, S. tridentinus and S.variegatus) were investigated by using rapid ultra-performance Liquid chromatography/electrospray ionization mass spectrometry (UPLC/ESI-MS) and direct infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS). While direct infusion ESI-FT-ICR mass spectra give a fast overview concerning the elemental compositions of the compounds and, therefore, hints to the main metabolites, UPLC/ESI-tandem mass spectrometry is shown to be a useful tool for their identification. A principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on the UPLC/ESI-MS clearly showed that the metabolite profiles can be used not only for the identification and classification of such fungi but also as a sophisticated and powerful tool for the chemotaxonomy of fungi. Furthermore, a clear discrimination of various types of biological samples (fruiting bodies versus mycelial cultures) is also possible. The orthogonal partial least squares (OPLS) two-class models of both UPLC/ESI-MS and ESI-FT-ICR-MS possess a clear differentiation of two compared Suillus species representing the between class variation and the within class variation. Based on generated S-plots and Loading plots, statistically significant metabolites could be identified as potential biomarker for one species.

The FLIGHT Drosophila RNAi database

PubMed Central

Bursteinas, Borisas; Jain, Ekta; Gao, Qiong; Baum, Buzz; Zvelebil, Marketa

2010-01-01

FLIGHT (http://flight.icr.ac.uk/) is an online resource compiling data from high-throughput Drosophila in vivo and in vitro RNAi screens. FLIGHT includes details of RNAi reagents and their predicted off-target effects, alongside RNAi screen hits, scores and phenotypes, including images from high-content screens. The latest release of FLIGHT is designed to enable users to upload, analyze, integrate and share their own RNAi screens. Users can perform multiple normalizations, view quality control plots, detect and assign screen hits and compare hits from multiple screens using a variety of methods including hierarchical clustering. FLIGHT integrates RNAi screen data with microarray gene expression as well as genomic annotations and genetic/physical interaction datasets to provide a single interface for RNAi screen analysis and datamining in Drosophila. PMID:20855970

Exploring the patterns of alpine vegetation of Eastern Bhutan: a case study from the Merak Himalaya.

PubMed

Jamtsho, Karma; Sridith, Kitichate

2015-01-01

A survey was conducted from March to September 2012 along the altitudinal gradient of the Jomokungkhar trail in the Merak Himalaya of Sakteng Wildlife Sanctuary to study the floristic compositions and the patterns of alpine vegetation of Eastern Bhutan. The vegetation of the sampled plots is classified into five types of communities based on the hierarchical cluster analysis at similarity index 63% viz., (1) Riverine Community; (2) Abies-Rhododendron Woodland Community; (3) Juniperus Scrub Community; (4) Rhododendron Krummholz and (5) Alpine Meadow, based on the floristic compositions. In addition, it was noticed that the fragile alpine environment of the Merak Himalaya has high plant diversity and important plants that are susceptible to the anthropogenic pressures.

Toward a hyperspectral optical signature of extra virgin olive oil

NASA Astrophysics Data System (ADS)

Mignani, A. G.; Ciaccheri, L.; Thienpont, H.; Ottevaere, H.; Attilio, C.; Cimato, A.

2007-05-01

Italian extra virgin olive oils bearing labels of certified area of origin were considered. Their multispectral digital signature was measured by means of absorption spectroscopy in the 200-1700 nm spectral range. The instrumentation was a fiber optic-based, cheap, and compact device. The spectral data were processed by means of multivariate analysis and plotted on a 2D classification map. The map showed sharp clusters according to the geographical origin of the oils, thus demonstrating the potentials of UV-VIS-NIR spectroscopy for optical fingerprinting. Then, the spectral data were correlated to the content of the most important fatty acids. The good fitting achieved demonstrated that the optical fingerprinting can be used also for predicting nutritional and chemical parameters.

Rocky Mountain spotted fever in Georgia, 1961-75: analysis of social and environmental factors affecting occurrence.

PubMed Central

Newhouse, V F; Choi, K; Holman, R C; Thacker, S B; D'Angelo, L J; Smith, J D

1986-01-01

For the period of 1961 through 1975, 10 geographic and sociologic variables in each of the 159 counties of Georgia were analyzed to determine how they were correlated with the occurrence of Rocky Mountain spotted fever (RMSF). Combinations of variables were transformed into a smaller number of factors using principal-component analysis. Based upon the relative values of these factors, geographic areas of similarity were delineated by cluster analysis. It was found by use of these analyses that the counties of the State formed four similarity clusters, which we called south, central, lower north and upper north. When the incidence of RMSF was subsequently calculated for each of these regions of similarity, the regions had differing RMSF incidence; low in the south and upper north, moderate in the central, and high in the lower north. The four similarity clusters agreed closely with the incidence of RMSF when both were plotted on a map. Thus, when analyzed simultaneously, the 10 variables selected could be used to predict the occurrence of RMSF. The most important variables were those of climate and geography. Of secondary, but still major importance, were the changes over the 15-year period in variables associated with humans and their environmental alterations. Detailed examination of these factors has permitted quantitative evaluation of the simultaneous impacts of the geographic and sociologic variables on the occurrence of RMSF in Georgia. These analyses could be updated to reflect changes in the relevant variables and tested as a means of identifying new high risk areas for RMSF in the State. More generally, this method might be adapted to clarify our understanding of the relative importance of individual variables in the ecology of other diseases or environmental health problems. PMID:3090609

Bayesian Nonparametric Ordination for the Analysis of Microbial Communities.

PubMed

Ren, Boyu; Bacallado, Sergio; Favaro, Stefano; Holmes, Susan; Trippa, Lorenzo

2017-01-01

Human microbiome studies use sequencing technologies to measure the abundance of bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material. Typically the data are organized in contingency tables with OTU counts across heterogeneous biological samples. In the microbial ecology community, ordination methods are frequently used to investigate latent factors or clusters that capture and describe variations of OTU counts across biological samples. It remains important to evaluate how uncertainty in estimates of each biological sample's microbial distribution propagates to ordination analyses, including visualization of clusters and projections of biological samples on low dimensional spaces. We propose a Bayesian analysis for dependent distributions to endow frequently used ordinations with estimates of uncertainty. A Bayesian nonparametric prior for dependent normalized random measures is constructed, which is marginally equivalent to the normalized generalized Gamma process, a well-known prior for nonparametric analyses. In our prior, the dependence and similarity between microbial distributions is represented by latent factors that concentrate in a low dimensional space. We use a shrinkage prior to tune the dimensionality of the latent factors. The resulting posterior samples of model parameters can be used to evaluate uncertainty in analyses routinely applied in microbiome studies. Specifically, by combining them with multivariate data analysis techniques we can visualize credible regions in ecological ordination plots. The characteristics of the proposed model are illustrated through a simulation study and applications in two microbiome datasets.

Visual evaluation of kinetic characteristics of PET probe for neuroreceptors using a two-phase graphic plot analysis.

PubMed

Ito, Hiroshi; Ikoma, Yoko; Seki, Chie; Kimura, Yasuyuki; Kawaguchi, Hiroshi; Takuwa, Hiroyuki; Ichise, Masanori; Suhara, Tetsuya; Kanno, Iwao

2017-05-01

Objectives In PET studies for neuroreceptors, tracer kinetics are described by the two-tissue compartment model (2-TCM), and binding parameters, including the total distribution volume (V T ), non-displaceable distribution volume (V ND ), and binding potential (BP ND ), can be determined from model parameters estimated by kinetic analysis. The stability of binding parameter estimates depends on the kinetic characteristics of radioligands. To describe these kinetic characteristics, we previously developed a two-phase graphic plot analysis in which V ND and V T can be estimated from the x-intercept of regression lines for early and delayed phases, respectively. In this study, we applied this graphic plot analysis to visual evaluation of the kinetic characteristics of radioligands for neuroreceptors, and investigated a relationship between the shape of these graphic plots and the stability of binding parameters estimated by the kinetic analysis with 2-TCM in simulated brain tissue time-activity curves (TACs) with various binding parameters. Methods 90-min TACs were generated with the arterial input function and assumed kinetic parameters according to 2-TCM. Graphic plot analysis was applied to these simulated TACs, and the curvature of the plot for each TAC was evaluated visually. TACs with several noise levels were also generated with various kinetic parameters, and the bias and variation of binding parameters estimated by kinetic analysis were calculated in each TAC. These bias and variation were compared with the shape of graphic plots. Results The graphic plots showed larger curvature for TACs with higher specific binding and slower dissociation of specific binding. The quartile deviations of V ND and BP ND determined by kinetic analysis were smaller for radioligands with slow dissociation. Conclusions The larger curvature of graphic plots for radioligands with slow dissociation might indicate a stable determination of V ND and BP ND by kinetic analysis. For investigation of the kinetics of radioligands, such kinetic characteristics should be considered.

The Chern-Simons Current in Systems of DNA-RNA Transcriptions

NASA Astrophysics Data System (ADS)

Capozziello, Salvatore; Pincak, Richard; Kanjamapornkul, Kabin; Saridakis, Emmanuel N.

2018-04-01

A Chern-Simons current, coming from ghost and anti-ghost fields of supersymmetry theory, can be used to define a spectrum of gene expression in new time series data where a spinor field, as alternative representation of a gene, is adopted instead of using the standard alphabet sequence of bases $A, T, C, G, U$. After a general discussion on the use of supersymmetry in biological systems, we give examples of the use of supersymmetry for living organism, discuss the codon and anti-codon ghost fields and develop an algebraic construction for the trash DNA, the DNA area which does not seem active in biological systems. As a general result, all hidden states of codon can be computed by Chern-Simons 3 forms. Finally, we plot a time series of genetic variations of viral glycoprotein gene and host T-cell receptor gene by using a gene tensor correlation network related to the Chern-Simons current. An empirical analysis of genetic shift, in host cell receptor genes with separated cluster of gene and genetic drift in viral gene, is obtained by using a tensor correlation plot over time series data derived as the empirical mode decomposition of Chern-Simons current.

Stereophysicochemical variability plots highlight conserved antigenic areas in Flaviviruses

PubMed Central

Schein, Catherine H; Zhou, Bin; Braun, Werner

2005-01-01

Background Flaviviruses, which include Dengue (DV) and West Nile (WN), mutate in response to immune system pressure. Identifying escape mutants, variant progeny that replicate in the presence of neutralizing antibodies, is a common way to identify functionally important residues of viral proteins. However, the mutations typically occur at variable positions on the viral surface that are not essential for viral replication. Methods are needed to determine the true targets of the neutralizing antibodies. Results Stereophysicochemical variability plots (SVPs), 3-D images of protein structures colored according to variability, as determined by our PCPMer program, were used to visualize residues conserved in their physical chemical properties (PCPs) near escape mutant positions. The analysis showed 1) that escape mutations in the flavivirus envelope protein are variable residues by our criteria and 2) two escape mutants found at the same position in many flaviviruses sit above clusters of conserved residues from different regions of the linear sequence. Conservation patterns in T-cell epitopes in the NS3- protease suggest a similar mechanism of immune system evasion. Conclusion The SVPs add another dimension to structurally defining the binding sites of neutralizing antibodies. They provide a useful aid for determining antigenically important regions and designing vaccines. PMID:15845145

Food-induced changes of lipids in rat neuronal tissue visualized by ToF-SIMS imaging.

PubMed

Dowlatshahi Pour, Masoumeh; Jennische, Eva; Lange, Stefan; Ewing, Andrew G; Malmberg, Per

2016-09-06

Time of flight secondary ion mass spectrometry (ToF-SIMS) was used to image the lipid localization in brain tissue sections from rats fed specially processed cereals (SPC). An IonTof 5 instrument equipped with a Bi cluster ion gun was used to analyze the tissue sections. Data from 15 brain samples from control and cereal-fed rats were recorded and exported to principal components analysis (PCA). The data clearly show changes of certain lipids in the brain following cereal feeding. PCA score plots show a good separation in lipid distribution between the control and the SPC-fed group. The loadings plot reveal that the groups separated mainly due to changes in cholesterol, vitamin E and c18:2, c16:0 fatty acid distribution as well as some short chain monocarboxylic fatty acid compositions. These insights relate to the working mechanism of SPC as a dietary supplement. SPC is thought to activate antisecretory factor (AF), an endogenous protein with regulatory function for inflammation and fluid secretion. These data provide insights into lipid content in brain following SPC feeding and suggest a relation to activating AF.

H-alpha Variability in the Young Open Cluster Cygnus OB2

NASA Astrophysics Data System (ADS)

Clarke, Seth; Hintz, Eric G.; Joner, Michael D.

2018-01-01

Observations of Cygnus OB2 were obtained in the filters detailed in Joner & Hintz (2015). For the last five years a block of data was secured using the BYU West Mountain 0.9-m telescope. Magnitudes were then determined using DAOPHOT in order to examine as many stars as possible on each frame. These magnitudes were then combined to generate the indexes from Joner & Hintz (2015). We will examine the overall cluster by using a color-color-magnitude plot. We will also present short term and long term time series measurements of a sample of variable objects in the field.

Revisiting the Aqueous Solutions of Dimethyl Sulfoxide by Spectroscopy in the Mid- and Near-Infrared: Experiments and Car-Parrinello Simulations.

PubMed

Wallace, Victoria M; Dhumal, Nilesh R; Zehentbauer, Florian M; Kim, Hyung J; Kiefer, Johannes

2015-11-19

The infrared and near-infrared spectra of the aqueous solutions of dimethyl sulfoxide are revisited. Experimental and computational vibrational spectra are analyzed and compared. The latter are determined as the Fourier transformation of the velocity autocorrelation function of data obtained from Car-Parrinello molecular dynamics simulations. The experimental absorption spectra are deconvolved, and the excess spectra are determined. The two-dimensional excess contour plot provides a means of visualizing and identifying spectral regions and concentration ranges exhibiting nonideal behavior. In the binary mixtures, the analysis of the SO stretching band provides a semiquantitative picture of the formation and dissociation of hydrogen-bonded DMSO-water complexes. A maximum concentration of these clusters is found in the equimolar mixture. At high DMSO concentration, the formation of rather stable 3DMSO:1water complexes is suggested. The formation of 1DMSO:2water clusters, in which the water oxygen atoms interact with the sulfoxide methyl groups, is proposed as a possible reason for the marked depression of the freezing temperature at the eutectic point.

Screening and clustering of sparse regressions with finite non-Gaussian mixtures.

PubMed

Zhang, Jian

2017-06-01

This article proposes a method to address the problem that can arise when covariates in a regression setting are not Gaussian, which may give rise to approximately mixture-distributed errors, or when a true mixture of regressions produced the data. The method begins with non-Gaussian mixture-based marginal variable screening, followed by fitting a full but relatively smaller mixture regression model to the selected data with help of a new penalization scheme. Under certain regularity conditions, the new screening procedure is shown to possess a sure screening property even when the population is heterogeneous. We further prove that there exists an elbow point in the associated scree plot which results in a consistent estimator of the set of active covariates in the model. By simulations, we demonstrate that the new procedure can substantially improve the performance of the existing procedures in the content of variable screening and data clustering. By applying the proposed procedure to motif data analysis in molecular biology, we demonstrate that the new method holds promise in practice. © 2016, The International Biometric Society.

GRAFLAB 2.3 for UNIX - A MATLAB database, plotting, and analysis tool: User`s guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunn, W.N.

1998-03-01

This report is a user`s manual for GRAFLAB, which is a new database, analysis, and plotting package that has been written entirely in the MATLAB programming language. GRAFLAB is currently used for data reduction, analysis, and archival. GRAFLAB was written to replace GRAFAID, which is a FORTRAN database, analysis, and plotting package that runs on VAX/VMS.

Plotting equation for gaussian percentiles and a spreadsheet program for generating probability plots

USGS Publications Warehouse

Balsillie, J.H.; Donoghue, J.F.; Butler, K.M.; Koch, J.L.

2002-01-01

Two-dimensional plotting tools can be of invaluable assistance in analytical scientific pursuits, and have been widely used in the analysis and interpretation of sedimentologic data. We consider, in this work, the use of arithmetic probability paper (APP). Most statistical computer applications do not allow for the generation of APP plots, because of apparent intractable nonlinearity of the percentile (or probability) axis of the plot. We have solved this problem by identifying an equation(s) for determining plotting positions of Gaussian percentiles (or probabilities), so that APP plots can easily be computer generated. An EXCEL example is presented, and a programmed, simple-to-use EXCEL application template is hereby made publicly available, whereby a complete granulometric analysis including data listing, moment measure calculations, and frequency and cumulative APP plots, is automatically produced.

Grid Computing Environment using a Beowulf Cluster

NASA Astrophysics Data System (ADS)

Alanis, Fransisco; Mahmood, Akhtar

2003-10-01

Custom-made Beowulf clusters using PCs are currently replacing expensive supercomputers to carry out complex scientific computations. At the University of Texas - Pan American, we built a 8 Gflops Beowulf Cluster for doing HEP research using RedHat Linux 7.3 and the LAM-MPI middleware. We will describe how we built and configured our Cluster, which we have named the Sphinx Beowulf Cluster. We will describe the results of our cluster benchmark studies and the run-time plots of several parallel application codes that were compiled in C on the cluster using the LAM-XMPI graphics user environment. We will demonstrate a "simple" prototype grid environment, where we will submit and run parallel jobs remotely across multiple cluster nodes over the internet from the presentation room at Texas Tech. University. The Sphinx Beowulf Cluster will be used for monte-carlo grid test-bed studies for the LHC-ATLAS high energy physics experiment. Grid is a new IT concept for the next generation of the "Super Internet" for high-performance computing. The Grid will allow scientist worldwide to view and analyze huge amounts of data flowing from the large-scale experiments in High Energy Physics. The Grid is expected to bring together geographically and organizationally dispersed computational resources, such as CPUs, storage systems, communication systems, and data sources.

Diversity of the small subunit ribosomal RNA gene of the arbuscular mycorrhizal fungi colonizing Clintonia borealis from a mixed-wood boreal forest.

PubMed

DeBellis, Tonia; Widden, Paul

2006-11-01

Arbuscular mycorrhizal fungi (AMF) communities in Clintonia borealis roots from a boreal mixed forests in northwestern Québec were investigated. Roots were sampled from 100 m2 plots whose overstory was dominated by either trembling aspen (Populus tremuloides Michx.), white birch (Betula papyrifera Marsh.), or mixed white spruce (Picea glauca (Moench) Voss) and balsam fir (Abies balsamea (L.) Mill.). Part of the 18S ribosomal gene of the AMF was amplified and the resulting PCR products were cloned. Restriction analysis of the 576 resulting clones yielded 92 different restriction patterns which were then sequenced. Fifty-two sequences closely matched other Glomus sequences from Genbank. Phylogenetic analysis revealed 10 different AMF sequence types, most of which clustered with other uncultured AM sequences from plant roots from various field sites. Compared with other AMF communities from comparable studies, richness and diversity were higher than observed in an arable field, but lower than seen in a tropical forest and a temperate wetland. The AMF communities from Clintonia roots under the different canopy types did not differ significantly and the dominant sequence type, which clustered with AM sequences from a variety of environments and hosts at distant geographical locations, represented 66.9% of all the clones analyzed.

Development of a method for the determination of Fusarium fungi on corn using mid-infrared spectroscopy with attenuated total reflection and chemometrics.

PubMed

Kos, Gregor; Lohninger, Hans; Krska, Rudolf

2003-03-01

A novel method, which enables the determination of fungal infection with Fusarium graminearum on corn within minutes, is presented. The ground sample was sieved and the particle size fraction between >250 and 100 microm was used for mid-infrared/attenuated total reflection (ATR) measurements. The sample was pressed onto the ATR crystal, and reproducible pressure was applied. After the spectra were recorded, they were subjected to principle component analysis (PCA) and classified using cluster analysis. Observed changes in the spectra reflected changes in protein, carbohydrate, and lipid contents. Ergosterol (for the total fungal biomass) and the toxin deoxynivalenol (DON; a secondary metabolite) of Fusarium fungi served as reference parameters, because of their relevance for the examination of corn based food and feed. The repeatability was highly improved by sieving prior to recording the spectra, resulting in a better clustering in PCA score/score plots. The developed method enabled the separation of samples with a toxin content of as low as 310 microg/kg from noncontaminated (blank) samples. Investigated concentration ranges were 880-3600 microg/kg for ergosterol and 310-2596 microg/kg for DON. The percentage of correctly classified samples was up to 100% for individual samples compared with a number of blank samples.

Altered expression of four miRNA (miR-1238-3p, miR-202-3p, miR-630 and miR-766-3p) and their potential targets in peripheral blood from vitiligo patients.

PubMed

Shang, Zhiwei; Li, Hongwen

2017-10-01

Vitiligo is an acquired skin disease with pigmentary disorder. Autoimmune destruction of melanocytes is thought to be major factor in the etiology of vitiligo. miRNA-based regulators of gene expression have been reported to play crucial roles in autoimmune disease. Therefore, we attempt to profile the miRNA expressions and predict their potential targets, assessing the biological functions of differentially expressed miRNA. Total RNA was extracted from peripheral blood of vitiligo (experimental group, n = 5) and non-vitiligo (control group, n = 5) age-matched patients. Samples were hybridized to a miRNA array. Box, scatter and principal component analysis plots were performed, followed by unsupervised hierarchical clustering analysis to classify the samples. Quantitative reverse transcription polymerase chain reaction (RT-PCR) was conducted for validation of microarray data. Three different databases, TargetScan, PITA and microRNA.org, were used to predict the potential target genes. Gene ontology (GO) annotation and pathway analysis were performed to assess the potential functions of predicted genes of identified miRNA. A total of 100 (29 upregulated and 71 downregulated) miRNA were filtered by volcano plot analysis. Four miRNA were validated by quantitative RT-PCR as significantly downregulated in the vitiligo group. The functions of predicted target genes associated with differentially expressed miRNA were assessed by GO analysis, showing that the GO term with most significantly enriched target genes was axon guidance, and that the axon guidance pathway was most significantly correlated with these miRNA. In conclusion, we identified four downregulated miRNA in vitiligo and assessed the potential functions of target genes related to these differentially expressed miRNA. © 2017 Japanese Dermatological Association.

The Cluster Science Archive: from Time Period to Physics Based Search

NASA Astrophysics Data System (ADS)

Masson, A.; Escoubet, C. P.; Laakso, H. E.; Perry, C. H.

2015-12-01

Since 2000, the Cluster spacecraft relay the most detailed information on how the solar wind affects our geospace in three dimensions. Science output from Cluster is a leap forward in our knowledge of space plasma physics: the science behind space weather. It has been key in improving the modeling of the magnetosphere and understanding its various physical processes. Cluster data have enabled the publication of more than 2000 refereed papers and counting. This substantial scientific return is often attributed to the online availability of the Cluster data archive, now called the Cluster Science Archive (CSA). It is being developed by the ESAC Science Data Center (ESDC) team and maintained alongside other science ESA archives at ESAC (ESA Space Astronomy Center, Madrid, Spain). CSA is a public archive, which contains the entire set of Cluster high-resolution data, and other related products in a standard format and with a complete set of metadata. Since May 2015, it also contains data from the CNSA/ESA Double Star mission (2003-2008), a mission operated in conjunction with Cluster. The total amount of data format now exceeds 100 TB. Accessing CSA requires to be registered to enable user profiles and CSA accounts more than 1,500 users. CSA provides unique tools for visualizing its data including - on-demand particle distribution functions visualization - fast data browsing with more than 15TB of pre-generated plots - inventory plots It also offers command line capabilities (e.g. data access via Matlab or IDL softwares, data streaming). Despite its reliability, users can only request data for a specific time period while scientists often focus on specific regions or data signatures. For these reasons, a data-mining tool is being developed to do just that. It offers an interface to select data based not only on a time period but on various criteria including: key physical parameters, regions of space and spacecraft constellation geometry. The output of this tool is a list of time periods that fits the criteria imposed by the user. Such a list enables to download any bunch of datasets for all these time periods in one go. We propose to present the state of development of this tool and interact with the scientific community to better fit its needs.

Advancements in LiDAR-based registration of FIA field plots

Treesearch

Demetrios Gatziolis

2012-01-01

Meaningful integration of National Forest Inventory field plot information with spectral imagery acquired from satellite or airborne platforms requires precise plot registration. Global positioning system-based plot registration procedures, such as the one employed by the Forest Inventory and Analysis (FIA) Program, yield plot coordinates that, although adequate for...

Anorthosite belts, continental drift, and the anorthosite event

USGS Publications Warehouse

Herz, N.

1969-01-01

Most anorthosites lie in two principal belts when plotted on a predrift continental reconstruction. Anorthosite ages in the belts cluster around 1300 ?? 200 million years and range from 1100 to 1700 million years. This suggests that anorthosites are the product of a unique cataclysmic event or a thermal event that was normal only during the earth's early history.

Anorthosite belts, continental drift, and the anorthosite event.

PubMed

Herz, N

1969-05-23

Most anorthosites lie in two principal belts when plotted on a predrift continental reconstruction. Anorthosite ages in the belts cluster around 1300 +/- 200 million years and range from 1100 to 1700 million years. This suggests that anorthosites are the product of a unique cataclysmic event or a thermal event that was normal only during the earth's early history.

Evaluating a model to predict timber harvesting in Austria

Treesearch

Hubert Sterba; Michael Golser; Klemens Schadauer

2000-01-01

Between 1981 and 1985, the Austrian National Forest Inventory (ANF) established a set of 5,500 clusters, each with four permanent plots, covering all Austrian forests. After the first remeasurement between 1986 and 1990, models were developed to predict tree growth, mortality, and the behavior of forest owners in harvesting timber. A set of logistic equations describes...

How To ... Guide

Treesearch

Duncan C. Lutes; Robert E. Keane; John F. Caratti; Carl H. Key; Nathan C. Benson

2006-01-01

This is probably the most critical phase of FIREMON sampling because this plot ID must be unique across all plots that will be entered in the FIREMON database. The plot identifier is made up of three parts: Registration Code, Project Code, and Plot Number.The FIREMON Analysis Tools program will allow summarization and comparison of plots only if...

[Penis growth and development in children and adolescents: a study based on GAMLSS].

PubMed

Yi, Qing-Jie; Zeng, Yan; Zeng, Qing; Wang, Yi-Nan; Xiong, Feng

2017-08-01

To investigate penis development in children and adolescents aged 0-16 years, and to plot the percentile curve for penis development in different age groups. A total of 3 024 normal male neonates, children, and adolescents aged 0-16 years in Chongqing, China were selected by simple random sampling and stratified cluster sampling. The length and diameter of the penis were measured for all subjects. A descriptive statistical analysis was used to investigate the data characteristics of the penis, and the GAMLSS fitting model was used to plot the percentile curves of P 3 , P 10 , P 25 , P 50 , P 75 , P 90 , and P97 and obtain percentile reference values. The length and diameter of the penis grew rapidly before the age of 1 year, grew relatively slowly from 1 to 11 years old, and entered a rapid growth period from 11 years old. The length of the penis was positively correlated with its diameter (r=0.961, P<0.01). The percentile reference values of penis length and diameter were obtained and the percentile curve was plotted. The growth and development of penis length is consistent with that of penis diameter in male children and adolescents in Chongqing, and 0-1 year and 11-16 years are rapid growth periods of penis length and diameter. The percentile curve of penis length and diameter in children and adolescents aged 0-16 years in Chongqing which has been established will provide a reference for further studies on sexual development in children and adolescents.

Evaluation of multifocal visual evoked potentials in patients with Graves' orbitopathy and subclinical optic nerve involvement.

PubMed

Pérez-Rico, Consuelo; Rodríguez-González, Natividad; Arévalo-Serrano, Juan; Blanco, Román

2012-08-01

Dysthyroid optic neuropathy is the most serious, although infrequent (8-10 %) complication in Graves' orbitopathy (GO). It is known that early stages of compressive optic neuropathy may produce reversible visual field defects, suggesting axoplasmic stasis rather than ganglion cell death. This observational, cross-sectional, case-control study assessed 34 consecutive patients (65 eyes) with Graves' hyperthyroidism and longstanding GO and 31 age-matched control subjects. The patients' multifocal visual evoked potentials (mfVEP) were compared to their clinical and psychophysical (standard automated perimetry [SAP]) and structural (optic coherence tomography [OCT]) diagnostic test data. Abnormal cluster defects were found in 12.3 % and 3.1 % of eyes on the interocular and monocular amplitude analysis mfVEP probability plots, respectively. As well, mfVEP latencies delays were found in 13.8 and 20 % of eyes on the interocular and monocular analysis probability plots, respectively. Interestingly, 19 % of patients with GO had ocular hypertension, and a strong correlation between intraocular pressure measured at upgaze and mfVEP latency was found. MfVEP amplitudes and visual acuity were significantly related to each other (P < 0.05), but not with the latencies delays. However, relationships between the interocular or monocular mfVEP amplitudes and latencies analysis and SAP indices or OCT data were not statistically significant. One-third of our patients with GO showed changes in the mfVEP, indicating significant subclinical optic nerve dysfunction. In this sense, the mfVEP may be a useful diagnostic tool in the clinic for early diagnosis and monitoring of optic nerve function abnormalities in patients with GO.

Considerations in Forest Growth Estimation Between Two Measurements of Mapped Forest Inventory Plots

Treesearch

Michael T. Thompson

2006-01-01

Several aspects of the enhanced Forest Inventory and Analysis (FIA) program?s national plot design complicate change estimation. The design incorporates up to three separate plot sizes (microplot, subplot, and macroplot) to sample trees of different sizes. Because multiple plot sizes are involved, change estimators designed for polyareal plot sampling, such as those...

Extended utility of molten-salt chemistry: unprecedented synthesis of a water-soluble salt-inclusion solid comprised of high-nuclearity vanadium oxide clusters.

PubMed

Queen, Wendy L; West, J Palmer; Hudson, Joan; Hwu, Shiou-Jyh

2011-11-07

Polyoxometallates (POMs) are desirable in materials applications ranging from uses as catalysts in selective oxidation reactions to molecular-like building blocks for the preparation of new extended solids. With the use of an unprecedented approach involving high temperature, molten salt methods, a fascinating series of salt-inclusion solids (SISs) that contain high nuclearity POMs has been isolated for the first time. Cs(11)Na(3)(V(15)O(36))Cl(6) (1) was synthesized using the eutectic NaCl/CsCl flux (mp 493 °C) which serves as a reactive solvent in crystal growth and allows for the SIS formation. Its framework can be viewed as an "ionic" lattice composed of alternately packed counterions of Cl-centered [V(15)O(36)Cl](9-) clusters (V15; S = 11/2) and multinuclear [Cs(9)Na(3)Cl(5)](7+) cations. In light of the structural analysis, 1 was proven to be soluble in water giving rise to a dark green solution that is similar in color to single crystals of the title compound. Infrared spectroscopy of the solid formed from fast evaporation of the solution supports the presence of dissolved V15 clusters. Also noteworthy is the magnetization of 1 at 2 K, which reveals an s-shaped plot resembling that of superparamagnetic materials. © 2011 American Chemical Society

Derringer desirability and kinetic plot LC-column comparison approach for MS-compatible lipopeptide analysis.

PubMed

D'Hondt, Matthias; Verbeke, Frederick; Stalmans, Sofie; Gevaert, Bert; Wynendaele, Evelien; De Spiegeleer, Bart

2014-06-01

Lipopeptides are currently re-emerging as an interesting subgroup in the peptide research field, having historical applications as antibacterial and antifungal agents and new potential applications as antiviral, antitumor, immune-modulating and cell-penetrating compounds. However, due to their specific structure, chromatographic analysis often requires special buffer systems or the use of trifluoroacetic acid, limiting mass spectrometry detection. Therefore, we used a traditional aqueous/acetonitrile based gradient system, containing 0.1% (m/v) formic acid, to separate four pharmaceutically relevant lipopeptides (polymyxin B 1 , caspofungin, daptomycin and gramicidin A 1 ), which were selected based upon hierarchical cluster analysis (HCA) and principal component analysis (PCA). In total, the performance of four different C18 columns, including one UPLC column, were evaluated using two parallel approaches. First, a Derringer desirability function was used, whereby six single and multiple chromatographic response values were rescaled into one overall D -value per column. Using this approach, the YMC Pack Pro C18 column was ranked as the best column for general MS-compatible lipopeptide separation. Secondly, the kinetic plot approach was used to compare the different columns at different flow rate ranges. As the optimal kinetic column performance is obtained at its maximal pressure, the length elongation factor λ ( P max / P exp ) was used to transform the obtained experimental data (retention times and peak capacities) and construct kinetic performance limit (KPL) curves, allowing a direct visual and unbiased comparison of the selected columns, whereby the YMC Triart C18 UPLC and ACE C18 columns performed as best. Finally, differences in column performance and the (dis)advantages of both approaches are discussed.

[Use of multiple locus variable number tandem repeats analysis for the Brucella systematization].

PubMed

Kulakov, Iu K; Kovalev, D A; Misetova, E N; Golovneva, S I; Liapustina, L V; Zheludkov, M M

2012-01-01

The methods of molecular-genetic differentiation to strain level acquire increasing significance in the current system of struggle with brucellosis. MLVA (multiple locus variable number tandem repeats analysis) was selected for molecular-genetic differentiation to strain level and simultaneous establishment of the genetic relationship of investigated Brucella strains. The goal of this work was MLVA typing of three pathogenic Brucella species strains with the analysis of stability of chosen loci, discrimination power and concordance to conventional phenotypic methods of the Brucella differentiation for use in systematization of brucellosis causing agents. Twenty six Brucella strains representing reference (n = 15), vaccine (n = 2) and field strains of three pathogenic Brucella species were tested: B. melitensis (n = 3), B. abortus (n = 2), B. suis (n = 2), and isolates (n = 2) with unidentified taxonomic position using MLVA with 9 pairs primers on known variable loci of Brucella genome. The analysis of the stability of chosen loci, discrimination power on Hunter-Gaston discrimination index (HGDI) and consistency to phenotypic methods of identification was performed. MLVA was confirmed for the results of phenotypic methods of identification, stability of the chosen loci in majority reference, and vaccine strains with a high index of variability HGDI 0.9969 for all loci. A dendrogram was plotted on the basis of MLVA data on distributed Brucella strains in related clusters according to its taxonomic species and biovar positions and construction of 25 genotypes. B. melitensis strains formed cluster related to the reference strain of B. melitensis 63/9 biovar 2. Australian isolates of Brucella 83-4 and Brucella 83-6 isolated from rodents formed a cluster distant from other strains of Brucella. MLVA is a promising method for differentiation of Brucella strains with known and unresolved taxonomic status for their systematization and creation of MLVA genotype catalogue that will promote qualitative improvement of brucellosis surveillance system in Russia.

Comprehensive analysis of Polygoni Multiflori Radix of different geographical origins using ultra-high-performance liquid chromatography fingerprints and multivariate chemometric methods.

PubMed

Sun, Li-Li; Wang, Meng; Zhang, Hui-Jie; Liu, Ya-Nan; Ren, Xiao-Liang; Deng, Yan-Ru; Qi, Ai-Di

2018-01-01

Polygoni Multiflori Radix (PMR) is increasingly being used not just as a traditional herbal medicine but also as a popular functional food. In this study, multivariate chemometric methods and mass spectrometry were combined to analyze the ultra-high-performance liquid chromatograph (UPLC) fingerprints of PMR from six different geographical origins. A chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and three classification methods is proposed to analyze the UPLC fingerprints obtained. Common chromatographic problems, including the background contribution, baseline contribution, and peak overlap, were handled by the established MCR-ALS model. A total of 22 components were resolved. Moreover, relative species concentrations were obtained from the MCR-ALS model, which was used for multivariate classification analysis. Principal component analysis (PCA) and Ward's method have been applied to classify 72 PMR samples from six different geographical regions. The PCA score plot showed that the PMR samples fell into four clusters, which related to the geographical location and climate of the source areas. The results were then corroborated by Ward's method. In addition, according to the variance-weighted distance between cluster centers obtained from Ward's method, five components were identified as the most significant variables (chemical markers) for cluster discrimination. A counter-propagation artificial neural network has been applied to confirm and predict the effects of chemical markers on different samples. Finally, the five chemical markers were identified by UPLC-quadrupole time-of-flight mass spectrometer. Components 3, 12, 16, 18, and 19 were identified as 2,3,5,4'-tetrahydroxy-stilbene-2-O-β-d-glucoside, emodin-8-O-β-d-glucopyranoside, emodin-8-O-(6'-O-acetyl)-β-d-glucopyranoside, emodin, and physcion, respectively. In conclusion, the proposed method can be applied for the comprehensive analysis of natural samples. Copyright © 2016. Published by Elsevier B.V.

Characterisation of volatile profiles in 50 native Peruvian chili pepper using solid phase microextraction-gas chromatography mass spectrometry (SPME-GCMS).

PubMed

Patel, Kirti; Ruiz, Candy; Calderon, Rosa; Marcelo, Mavel; Rojas, Rosario

2016-11-01

The volatiles were characterised by headspace solid phase micro extraction (HS-SPME), gas chromatography mass spectrometry (GC-FID/MS). A total of 127 compounds were identified with terpenes (including mono terpenes and sesquiterpenes - a total of 45 compounds), esters (31 compounds) and hydrocarbons (20 compounds) were the predominant volatile compounds. Principal component analysis (PCA) of the volatile compounds yielded 2 significant PC's, which together accounted for 90.3% of the total variance in the data set and the scatter plot generated between PC1 and PC2 successfully segregated the 50 chili pepper samples into 7 groups. Clusters of hydrocarbons, esters, terpenes, aldehyde and ketones formed the major determinants of the difference. Copyright © 2016 Elsevier Ltd. All rights reserved.

ac impedance analysis of a Ni-Nb-Zr-H glassy alloy with femtofarad capacitance tunnels

NASA Astrophysics Data System (ADS)

Fukuhara, M.; Seto, M.; Inoue, A.

2010-01-01

A Nyquist diagram of a (Ni0.36Nb0.24Zr0.40)90H10 glassy alloy shows a semitrue circle, indicating that it is a conducting material with a total capacitance of 17.8 μF. The Bode plots showing the dependencies of its real and imaginary impedances, and phase on frequency suggest a simpler equivalent circuit having a resistor in parallel with a capacitor. Dividing the total capacitance (17.8 μF) by the capacitance of a single tunnel (0.9 fF), we deduced that this material has a high number of dielectric tunnels, which can be regarded as regular prisms separated from the electric-conducting distorted icosahedral Zr5Ni5Nb3 clusters by an average of 0.225 nm.

On-Line 1D and 2D PLOT/LC-ESI-MS Using 10 μm i.d. Poly(styrene–divinylbenzene) Porous Layer Open Tubular (PLOT) Columns For Ultrasensitive Proteomic Analysis

PubMed Central

Luo, Quanzhou; Yue, Guihua; Valaskovic, Gary A; Gu, Ye; Wu, Shiaw-Lin; Karger, Barry L.

2008-01-01

Following on our recent work, on-line one dimensional (1D) and two dimensional (2D) PLOT/LC-ESI-MS platforms using 3.2 m × 10 μm i.d. poly(styrenedivinylbenzene) (PS-DVB) porous layer open tubular (PLOT) columns have been developed to provide robust, high performance and ultrasensitive proteomic analysis. Using a PicoClear tee, the dead volume connection between a 50 μm i.d. PS-DVB monolithic microSPE column and the PLOT column was minimized. The microSPE/PLOT column assembly provided a separation performance similar to that obtained with direct injection onto the PLOT column at a mobile phase flow rate of 20 nL/min. The trace analysis potential of the platform was evaluated using an in-gel tryptic digest sample of a gel fraction (15 to 40 kDa) of a cervical cancer (SiHa) cell line. As an example of the sensitivity of the system, ∼2.5 ng of protein in 2 μL solution, an amount corresponding to 20 SiHa cells, was subjected to on-line microSPE-PLOT/LC-ESIMS/MS analysis using a linear ion trap MS. 237 peptides associated with 163 unique proteins were identified from a single analysis when using stringent criteria associated with a false positive rate less than 1% . The number of identified peptides and proteins increased to 638 and 343, respectively, as the injection amount was raised to ∼45 ng of protein, an amount corresponding to 350 SiHa cells. In comparison, only 338 peptides and 231 unique proteins were identified (false positive rate again less than 1%) from 750 ng of protein from the identical gel fraction, an amount corresponding to 6000 SiHa cells, using a typical 15 cm × 75 μm i.d. packed capillary column. The greater sensitivity, higher recovery, and higher resolving power of the PLOT column resulted in the increased number of identifications from only ∼5% of the injected sample amount. The resolving power of the microSPE/PLOT assembly was further extended by 2D chromatography via combination of the high-efficiency reversed phase PLOT column with strong cation exchange chromatography (SCX). As an example, 1071 peptides associated with 536 unique proteins were identified from 75 ng of protein from the same gel fraction, an amount corresponding to 600 cells, using 5 ion exchange fractions in online 2D SCX-PLOT/LC-MS. The 2D system, implemented in an automated format, led to simple and robust operation for proteomic analysis. These promising results demonstrate the potential of the PLOT column for ultratrace analysis. PMID:17625912

Transport in the Subtropical Lowermost Stratosphere during CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Pittman, Jasna V.; Weinstock, elliot M.; Oglesby, Robert J.; Sayres, David S.; Smith, Jessica B.; Anderson, James G.; Cooper, Owen R.; Wofsy, Steven C.; Xueref, Irene; Gerbig, Cristoph;

Transport in the Subtropical Lowermost Stratosphere during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment

NASA Technical Reports Server (NTRS)

Pittman, Jasna V.; Weinstock, Elliot M.; Oglesby, Robert J.; Sayres, David S.; Smith, Jessica B.; Anderson, James G.; Cooper, Owen R.; Wofsy, Steven C.; Xueref, Irene; Gerbig, Cristoph;

Cirripede Cypris Antennules: How Much Structural Variation Exists Among Balanomorphan Species from Hard-Bottom Habitats?

PubMed

Chan, Benny K K; Sari, Alireza; Høeg, Jens T

2017-10-01

Barnacle cypris antennules are important for substratum attachment during settlement and on through metamorphosis from the larval stage to sessile adult. Studies on the morphology of cirripede cyprids are mostly qualitative, based on descriptions from images obtained using a scanning electron microscope (SEM). To our knowledge, our study is the first to use scanning electron microscopy to quantify overall structural diversity in cypris antennules by measuring 26 morphological parameters, including the structure of sensory organs. We analyzed cyprids from seven species of balanomorphan barnacles inhabiting rocky shore communities; for comparison, we also included a sponge-inhabiting balanomorphan and a verrucomorphan species. Multivariate analysis of the structural parameters resulted in two distinct clusters of species. From nonmetric multidimensional scaling plots, the sponge-inhabiting Balanus spongicola and Verruca stroemia formed one cluster, while the other balanomorphan species, all from hard bottoms, grouped together in the other cluster. The shape of the attachment disk on segment 3 is the key parameter responsible for the separation into two clusters. The present results show that species from a coastal hard-bottom habitat may share a nearly identical antennular structure that is distinct from barnacles from other habitats, and this finding supports the fact that such species also have rather similar reactions to substratum cues during settlement. Any differences that may be found in settlement biology among such species must therefore be due either to differences in the properties of their adhesive mechanisms or to the way that sensory stimuli are detected by virtually identical setae and processed into settlement behavior by the cyprid.

A comparison of two sampling approaches for assessing the urban forest canopy cover from aerial photography.

Treesearch

Ucar Zennure; Pete Bettinger; Krista Merry; Jacek Siry; J.M. Bowker

2016-01-01

Two different sampling approaches for estimating urban tree canopy cover were applied to two medium-sized cities in the United States, in conjunction with two freely available remotely sensed imagery products. A random point-based sampling approach, which involved 1000 sample points, was compared against a plot/grid sampling (cluster sampling) approach that involved a...

An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data.

PubMed

Vu, Trung N; Valkenborg, Dirk; Smets, Koen; Verwaest, Kim A; Dommisse, Roger; Lemière, Filip; Verschoren, Alain; Goethals, Bart; Laukens, Kris

2011-10-20

Nuclear magnetic resonance spectroscopy (NMR) is a powerful technique to reveal and compare quantitative metabolic profiles of biological tissues. However, chemical and physical sample variations make the analysis of the data challenging, and typically require the application of a number of preprocessing steps prior to data interpretation. For example, noise reduction, normalization, baseline correction, peak picking, spectrum alignment and statistical analysis are indispensable components in any NMR analysis pipeline. We introduce a novel suite of informatics tools for the quantitative analysis of NMR metabolomic profile data. The core of the processing cascade is a novel peak alignment algorithm, called hierarchical Cluster-based Peak Alignment (CluPA). The algorithm aligns a target spectrum to the reference spectrum in a top-down fashion by building a hierarchical cluster tree from peak lists of reference and target spectra and then dividing the spectra into smaller segments based on the most distant clusters of the tree. To reduce the computational time to estimate the spectral misalignment, the method makes use of Fast Fourier Transformation (FFT) cross-correlation. Since the method returns a high-quality alignment, we can propose a simple methodology to study the variability of the NMR spectra. For each aligned NMR data point the ratio of the between-group and within-group sum of squares (BW-ratio) is calculated to quantify the difference in variability between and within predefined groups of NMR spectra. This differential analysis is related to the calculation of the F-statistic or a one-way ANOVA, but without distributional assumptions. Statistical inference based on the BW-ratio is achieved by bootstrapping the null distribution from the experimental data. The workflow performance was evaluated using a previously published dataset. Correlation maps, spectral and grey scale plots show clear improvements in comparison to other methods, and the down-to-earth quantitative analysis works well for the CluPA-aligned spectra. The whole workflow is embedded into a modular and statistically sound framework that is implemented as an R package called "speaq" ("spectrum alignment and quantitation"), which is freely available from http://code.google.com/p/speaq/.

Estimating the number of tree species in forest populations using current vegetation survey and forest inventory and analysis approximation plots and grid intensities

Treesearch

Hans T. Schreuder; Jin-Mann S. Lin; John Teply

2000-01-01

We estimate number of tree species in National Forest populations using the nonparametric estimator. Data from the Current Vegetation Survey (CVS) of Region 6 of the USDA Forest Service were used to estimate the number of tree species with a plot close in size to the Forest Inventory and Analysis (FIA) plot and the actual CVS plot for the 5.5 km FIA grid and the 2.7 km...

Visualization of Sources in the Universe

NASA Astrophysics Data System (ADS)

Kafatos, M.; Cebral, J. R.

1993-12-01

We have begun to develop a series of visualization tools of importance to the display of astronomical data and have applied these to the visualization of cosmological sources in the recently formed Institute for Computational Sciences and Informatics at GMU. One can use a three-dimensional perspective plot of the density surface for three dimensional data and in this case the iso-level contours are three- dimensional surfaces. Sophisticated rendering algorithms combined with multiple source lighting allow us to look carefully at such density contours and to see fine structure on the surface of the density contours. Stereoscopic and transparent rendering can give an even more sophisticated approach with multi-layered surfaces providing information at different levels. We have applied these methods to looking at density surfaces of 3-D data such as 100 clusters of galaxies and 2500 galaxies in the CfA redshift survey. Our plots presented are based on three variables, right ascension, declination and redshift. We have also obtained density structures in 2-D for the distribution of gamma-ray bursts (where distances are unknown) and the distribution of a variety of sources such as clusters of galaxies. Our techniques allow for correlations to be done visually.

Round versus rectangular: Does the plot shape matter?

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Bäthke, Lars; Ries, Johannes B.

2016-04-01

Field rainfall simulators are designed to study soil erosion processes and provide urgently needed data for various geomorphological, hydrological and pedological issues. Due to the different conditions and technologies applied, there are several methodological aspects under review of the scientific community, particularly concerning design, procedures and conditions of measurement for infiltration, runoff and soil erosion. Extensive discussions at the Rainfall Simulator Workshop 2011 in Trier and the Splinter Meeting at EGU 2013 "Rainfall simulation: Big steps forward!" lead to the opinion that the rectangular shape is the more suitable plot shape compared to the round plot. A horizontally edging Gerlach trough is installed for sample collection without forming unnatural necks as is found at round or triangle plots. Since most research groups did and currently do work with round plots at the point scale (<1m²), a precise analysis of the differences between the output of round and square plots are necessary. Our hypotheses are: - Round plot shapes disturb surface runoff, unnatural fluvial dynamics for the given plot size such as pool development especially directly at the plot's outlet occur. - A square plot shape prevent these problems. A first comparison between round and rectangular plots (Iserloh et al., 2015) indicates that the rectangular plot could indeed be the more suitable, but the rather ambiguous results make a more elaborate test setup necessary. The laboratory test setup includes the two plot shapes (round, square), a standardised silty substrate and three inclinations (2°, 6°, 12°). The analysis of the laboratory test provide results on the best performance concerning undisturbed surface runoff and soil/water sampling at the plot's outlet. The analysis of the plot shape concerning its influence on runoff and erosion shows that clear methodological standards are necessary in order to make rainfall simulation experiments comparable. Reference: Iserloh, T., Pegoraro, D., Schlösser, A., Thesing, H., Seeger, M., Ries, J.B. (2015): Rainfall simulation experiments: Influence of water temperature, water quality and plot design on soil erosion and runoff. Geophysical Research Abstracts, Vol. 17, EGU2015-5817.

SURF Model Calibration Strategy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Menikoff, Ralph

2017-03-10

SURF and SURFplus are high explosive reactive burn models for shock initiation and propagation of detonation waves. They are engineering models motivated by the ignition & growth concept of high spots and for SURFplus a second slow reaction for the energy release from carbon clustering. A key feature of the SURF model is that there is a partial decoupling between model parameters and detonation properties. This enables reduced sets of independent parameters to be calibrated sequentially for the initiation and propagation regimes. Here we focus on a methodology for tting the initiation parameters to Pop plot data based on 1-Dmore » simulations to compute a numerical Pop plot. In addition, the strategy for tting the remaining parameters for the propagation regime and failure diameter is discussed.« less

The poor man's Geographic Information System: plot expansion factors

Treesearch

Paul C. Van Deusen

2007-01-01

Plot expansion factors can serve as a crude Geographic Information System for users of Forest Inventory and Analysis (FIA) data. Each FIA plot has an associated expansion factor that is often interpreted as the number of forested acres that the plot represents. The derivation of expansion factors is discussed and it is shown that the mapped plot design requires a...

Maritime climate influence on chaparral composition and diversity in the coast range of central California.

PubMed

Vasey, Michael C; Parker, V Thomas; Holl, Karen D; Loik, Michael E; Hiatt, Seth

2014-09-01

We investigated the hypothesis that maritime climatic factors associated with summer fog and low cloud stratus (summer marine layer) help explain the compositional diversity of chaparral in the coast range of central California. We randomly sampled chaparral species composition in 0.1-hectare plots along a coast-to-interior gradient. For each plot, climatic variables were estimated and soil samples were analyzed. We used Cluster Analysis and Principle Components Analysis to objectively categorize plots into climate zone groups. Climate variables, vegetation composition and various diversity measures were compared across climate zone groups using ANOVA and nonmetric multidimensional scaling. Differences in climatic variables that relate to summer moisture availability and winter freeze events explained the majority of variance in measured conditions and coincided with three chaparral assemblages: maritime (lowland coast where the summer marine layer was strongest), transition (upland coast with mild summer marine layer influence and greater winter precipitation), and interior sites that generally lacked late summer water availability from either source. Species turnover (β-diversity) was higher among maritime and transition sites than interior sites. Coastal chaparral differs from interior chaparral in having a higher obligate seeder to facultative seeder (resprouter) ratio and by being dominated by various Arctostaphylos species as opposed to the interior dominant, Adenostoma fasciculatum. The maritime climate influence along the California central coast is associated with patterns of woody plant composition and β-diversity among sites. Summer fog in coastal lowlands and higher winter precipitation in coastal uplands combine to lower late dry season water deficit in coastal chaparral and contribute to longer fire return intervals that are associated with obligate seeders and more local endemism. Soil nutrients are comparatively less important in explaining plant community composition, but heterogeneous azonal soils contribute to local endemism and promote isolated chaparral patches within the dominant forest vegetation along the coast.

Use of density equalizing map projections (DEMP) in the analysis of childhood cancer in four California counties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merrill, D.W.; Selvin, S.; Close, E.R.

In studying geographic disease distributions, one normally compares rates of arbitrarily defined geographic subareas (e.g. census tracts), thereby sacrificing the geographic detail of the original data. The sparser the data, the larger the subareas must be in order to calculate stable rates. This dilemma is avoided with the technique of Density Equalizing Map Projections (DEMP). Boundaries of geographic subregions are adjusted to equalize population density over the entire study area. Case locations plotted on the transformed map should have a uniform distribution if the underlying disease-rates are constant. On the transformed map, the statistical analysis of the observed distribution ismore » greatly simplified. Even for sparse distributions, the statistical significance of a supposed disease cluster can be reliably calculated. The present report describes the first successful application of the DEMP technique to a sizeable ``real-world`` data set of epidemiologic interest. An improved DEMP algorithm [GUSE93, CLOS94] was applied to a data set previously analyzed with conventional techniques [SATA90, REYN91]. The results from the DEMP analysis and a conventional analysis are compared.« less

Analysis of perceived similarity between pairs of microcalcification clusters in mammograms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Juan; Jing, Hao; Wernick, Miles N.

2014-05-15

Purpose: Content-based image retrieval aims to assist radiologists by presenting example images with known pathology that are visually similar to the case being evaluated. In this work, the authors investigate several fundamental issues underlying the similarity ratings between pairs of microcalcification (MC) lesions on mammograms as judged by radiologists: the degree of variability in the similarity ratings, the impact of this variability on agreement between readers in retrieval of similar lesions, and the factors contributing to the readers’ similarity ratings. Methods: The authors conduct a reader study on a set of 1000 image pairs of MC lesions, in which amore » group of experienced breast radiologists rated the degree of similarity between each image pair. The image pairs are selected, from among possible pairings of 222 cases (110 malignant, 112 benign), based on quantitative image attributes (features) and the results of a preliminary reader study. Next, the authors apply analysis of variance (ANOVA) to quantify the level of variability in the readers’ similarity ratings, and study how the variability in individual reader ratings affects consistency between readers. The authors also measure the extent to which readers agree on images which are most similar to a given query, for which the Dice coefficient is used. To investigate how the similarity ratings potentially relate to the attributes underlying the cases, the authors study the fraction of perceptually similar images that also share the same benign or malignant pathology as the query image; moreover, the authors apply multidimensional scaling (MDS) to embed the cases according to their mutual perceptual similarity in a two-dimensional plot, which allows the authors to examine the manner in which similar lesions relate to one another in terms of benign or malignant pathology and clustered MCs. Results: The ANOVA results show that the coefficient of determination in the reader similarity ratings is 0.59. The variability level in the similarity ratings is proved to be a limiting factor, leading to only moderate correlation between the readers in their readings. The Dice coefficient, measuring agreement between readers in retrieval of similar images, can vary from 0.45 to 0.64 with different levels of similarity for individual readers, but is higher for average ratings from a group of readers (from 0.59 to 0.78). More importantly, the fraction of retrieved cases that match the benign or malignant pathology of the query image was found to increase with the degree of similarity among the retrieved images, reaching average value as high as 0.69 for the radiologists (p-value <10{sup −4} compared to random guessing). Moreover, MDS embedding of all the cases shows that cases having the same pathology tend to cluster together, and that neighboring cases in the plot tend to be similar in their clustered MCs. Conclusions: While individual readers exhibit substantial variability in their similarity ratings, similarity ratings averaged from a group of readers can achieve a high level of intergroup consistency and agreement in retrieval of similar images. More importantly, perceptually similar cases are also likely to be similar in their underlying benign or malignant pathology and image features of clustered MCs, which could be of diagnostic value in computer-aided diagnosis for lesions with clustered MCs.« less

Principal component analysis for the comparison of metabolic profiles from human rectal cancer biopsies and colorectal xenografts using high-resolution magic angle spinning 1H magnetic resonance spectroscopy

PubMed Central

Seierstad, Therese; Røe, Kathrine; Sitter, Beathe; Halgunset, Jostein; Flatmark, Kjersti; Ree, Anne H; Olsen, Dag Rune; Gribbestad, Ingrid S; Bathen, Tone F

2008-01-01

Background This study was conducted in order to elucidate metabolic differences between human rectal cancer biopsies and colorectal HT29, HCT116 and SW620 xenografts by using high-resolution magnetic angle spinning (MAS) magnetic resonance spectroscopy (MRS) and for determination of the most appropriate human rectal xenograft model for preclinical MR spectroscopy studies. A further aim was to investigate metabolic changes following irradiation of HT29 xenografts. Methods HR MAS MRS of tissue samples from xenografts and rectal biopsies were obtained with a Bruker Avance DRX600 spectrometer and analyzed using principal component analysis (PCA) and partial least square (PLS) regression analysis. Results and conclusion HR MAS MRS enabled assignment of 27 metabolites. Score plots from PCA of spin-echo and single-pulse spectra revealed separate clusters of the different xenografts and rectal biopsies, reflecting underlying differences in metabolite composition. The loading profile indicated that clustering was mainly based on differences in relative amounts of lipids, lactate and choline-containing compounds, with HT29 exhibiting the metabolic profile most similar to human rectal cancers tissue. Due to high necrotic fractions in the HT29 xenografts, radiation-induced changes were not detected when comparing spectra from untreated and irradiated HT29 xenografts. However, PLS calibration relating spectral data to the necrotic fraction revealed a significant correlation, indicating that necrotic fraction can be assessed from the MR spectra. PMID:18439252

Craniometric relationships among medieval Central European populations: implications for Croat migration and expansion.

PubMed

Slaus, Mario; Tomicić, Zeljko; Uglesić, Ante; Jurić, Radomir

2004-08-01

To determine the ethnic composition of the early medieval Croats, the location from which they migrated to the east coast of the Adriatic, and to separate early medieval Croats from Bijelo brdo culture members, using principal components analysis and discriminant function analysis of craniometric data from Central and South-East European medieval archaeological sites. Mean male values for 8 cranial measurements from 39 European and 5 Iranian sites were analyzed by principal components analysis. Raw data for 17 cranial measurements for 103 female and 112 male skulls were used to develop discriminant functions. The scatter-plot of the analyzed sites on the first 2 principal components showed a pattern of intergroup relationships consistent with geographical and archaeological information not included in the data set. The first 2 principal components separated the sites into 4 distinct clusters: Avaroslav sites west of the Danube, Avaroslav sites east of the Danube, Bijelo brdo sites, and Polish sites. All early medieval Croat sites were located in the cluster of Polish sites. Two discriminant functions successfully differentiated between early medieval Croats and Bijelo brdo members. Overall accuracies were high -- 89.3% for males, and 97.1% for females. Early medieval Croats seem to be of Slavic ancestry, and at one time shared a common homeland with medieval Poles. Application of unstandardized discriminant function coefficients to unclassified crania from 18 sites showed an expansion of early medieval Croats into continental Croatia during the 10th to 13th century.

Total coliforms, arsenic and cadmium exposure through drinking water in the Western Region of Ghana: application of multivariate statistical technique to groundwater quality.

PubMed

Affum, Andrews Obeng; Osae, Shiloh Dede; Nyarko, Benjamin Jabez Botwe; Afful, Samuel; Fianko, Joseph Richmond; Akiti, Tetteh Thomas; Adomako, Dickson; Acquaah, Samuel Osafo; Dorleku, Micheal; Antoh, Emmanuel; Barnes, Felix; Affum, Enoch Acheampong

2015-02-01

In recent times, surface water resource in the Western Region of Ghana has been found to be inadequate in supply and polluted by various anthropogenic activities. As a result of these problems, the demand for groundwater by the human populations in the peri-urban communities for domestic, municipal and irrigation purposes has increased without prior knowledge of its water quality. Water samples were collected from 14 public hand-dug wells during the rainy season in 2013 and investigated for total coliforms, Escherichia coli, mercury (Hg), arsenic (As), cadmium (Cd) and physicochemical parameters. Multivariate statistical analysis of the dataset and a linear stoichiometric plot of major ions were applied to group the water samples and to identify the main factors and sources of contamination. Hierarchal cluster analysis revealed four clusters from the hydrochemical variables (R-mode) and three clusters in the case of water samples (Q-mode) after z score standardization. Principal component analysis after a varimax rotation of the dataset indicated that the four factors extracted explained 93.3 % of the total variance, which highlighted salinity, toxic elements and hardness pollution as the dominant factors affecting groundwater quality. Cation exchange, mineral dissolution and silicate weathering influenced groundwater quality. The ranking order of major ions was Na(+) > Ca(2+) > K(+) > Mg(2+) and Cl(-) > SO4 (2-) > HCO3 (-). Based on piper plot and the hydrogeology of the study area, sodium chloride (86 %), sodium hydrogen carbonate and sodium carbonate (14 %) water types were identified. Although E. coli were absent in the water samples, 36 % of the wells contained total coliforms (Enterobacter species) which exceeded the WHO guidelines limit of zero colony-forming unit (CFU)/100 mL of drinking water. With the exception of Hg, the concentration of As and Cd in 79 and 43 % of the water samples exceeded the WHO guideline limits of 10 and 3 μg/L for drinking water, respectively. Reported values in some areas in Nigeria, Malaysia and USA indicated that the maximum concentration of Cd was low and As was high in this study. Health risk assessment of Cd, As and Hg based on average daily dose, hazard quotient and cancer risk was determined. In conclusion, multiple natural processes and anthropogenic activities from non-point sources contributed significantly to groundwater salinization, hardness, toxic element and microbiological contamination of the study area. The outcome of this study can be used as a baseline data to prioritize areas for future sustainable development of public wells.

Spatially Locating FIA Plots from Pixel Values

Treesearch

Greg C. Liknes; Geoffrey R. Holden; Mark D. Nelson; Ronald E. McRoberts

2005-01-01

The USDA Forest Service Forest Inventory and Analysis (FIA) program is required to ensure the confidentiality of the geographic locations of plots. To accommodate user requests for data without releasing actual plot coordinates, FIA creates overlays of plot locations on various geospatial data, including satellite imagery. Methods for reporting pixel values associated...

Melting of size-selected gallium clusters with 60-183 atoms.

PubMed

Pyfer, Katheryne L; Kafader, Jared O; Yalamanchali, Anirudh; Jarrold, Martin F

2014-07-10

Heat capacities have been measured as a function of temperature for size-selected gallium cluster cations with between 60 and 183 atoms. Almost all clusters studied show a single peak in the heat capacity that is attributed to a melting transition. The peaks can be fit by a two-state model incorporating only fully solid-like and fully liquid-like species, and hence no partially melted intermediates. The exceptions are Ga90(+), which does not show a peak, and Ga80(+) and Ga81(+), which show two peaks. For the clusters with two peaks, the lower temperature peak is attributed to a structural transition. The melting temperatures for clusters with less than 50 atoms have previously been shown to be hundreds of degrees above the bulk melting point. For clusters with more than 60 atoms the melting temperatures decrease, approaching the bulk value (303 K) at around 95 atoms, and then show several small upward excursions with increasing cluster size. A plot of the latent heat against the entropy change for melting reveals two groups of clusters: the latent heats and entropy changes for clusters with less than 94 atoms are distinct from those for clusters with more than 93 atoms. This observation suggests that a significant change in the nature of the bonding or the structure of the clusters occurs at 93-94 atoms. Even though the melting temperatures are close to the bulk value for the larger clusters studied here, the latent heats and entropies of melting are still far from the bulk values.

AFLP-based genetic diversity and its comparison with diversity based on SSR, SAMPL, and phenotypic traits in bread wheat.

PubMed

Roy, J K; Lakshmikumaran, M S; Balyan, H S; Gupta, P K

2004-02-01

Data on AFLP (eight primer pairs) and 14 phenotypic traits, collected on 55 elite and exotic bread wheat genotypes, were utilized for estimations of genetic diversity. We earlier used these 55 genotypes for a similar study using SSRs and SAMPL. As many as 615 scorable AFLP bands visualized included 287 (46.6%) polymorphic bands. The phenotypic traits included yield and its component traits, as well as physiomorphological traits like flag leaf area. Dendrograms were prepared using cluster analysis based on Jaccard's similarity coefficients in case of AFLP and on squared Euclidean distances in case of phenotypic traits. PCA was conducted using AFLP data and a PCA plot was prepared, which was compared with clustering patterns in two dendrograms, one each for AFLP and phenotypic traits. The results were also compared with published results that included studies conducted elsewhere using entirely different wheat germplasm and our own SSR and SAMPL studies based on the same 55 genotypes used in the present study. It was shown that molecular markers are superior to phenotypic traits and that AFLP and SAMPL are superior to other molecular markers for estimation of genetic diversity. On the basis of AFLP analysis and keeping in view the yield performance and stability, a pair of genotypes (E3876 and E677) was recommended for hybridization in order to develop superior cultivars.

Blunted autonomic response in cluster headache patients.

PubMed

Barloese, Mads; Brinth, Louise; Mehlsen, Jesper; Jennum, Poul; Lundberg, Helena Inez Sofia; Jensen, Rigmor

2015-12-01

Cluster headache (CH) is a disabling headache disorder with chronobiological features. The posterior hypothalamus is involved in CH pathophysiology and is a hub for autonomic control. We studied autonomic response to the head-up tilt table test (HUT) including heart rate variability (HRV) in CH patients and compared results to healthy controls. Twenty-seven episodic and chronic CH patients and an equal number of age-, sex- and BMI-matched controls were included. We analyzed responses to HUT in the time and frequency domain and by non-linear analysis. CH patients have normal cardiovascular responses compared to controls but increased blood pressure. In the frequency analysis CH patients had a smaller change in the normalized low- (LF) (2.89 vs. 13.38, p < 0.05) and high-frequency (HF) (-2.86 vs. -13.38, p < 0.05) components as well as the LF/HF ratio (0.81 vs. 2.62, p < 0.05) in response to tilt. In the Poincaré plot, the change in ratio between long- and short-term variation was lower in patients (SD1/SD2, -0.05 vs. -0.17, p < 0.05). CH patients show decreased autonomic response to HUT compared to healthy controls. This can be interpreted as dysregulation in the posterior hypothalamus and supports a theory of central autonomic mechanisms involvement in CH. © International Headache Society 2015.

A density management diagram for even-aged Sierra Nevada mixed-conifer stands

Treesearch

James N. Long; John D. Shaw

2012-01-01

We have developed a density management diagram (DMD) for even-aged mixed-conifer stands in the Sierra Nevada Mountains using forest inventory and analysis (FIA) data. Analysis plots were drawn from FIA plots in California, southern Oregon, and western Nevada which included those conifer species associated with the mixed-conifer forest type. A total of 204 plots met the...

The status of accurately locating forest inventory and analysis plots using the Global Positioning System

Treesearch

Michael Hoppus; Andrew Lister

2007-01-01

Historically, field crews used Global Positioning System (GPS) coordinates to establish and relocate plots, as well as document their general location. During the past 5 years, the increase in Geographic Information System (GIS) capabilities and in customer requests to use the spatial relationships between Forest Inventory and Analysis (FIA) plot data and other GIS...

A WISE Selection of MIR AGN in Different Environments

NASA Astrophysics Data System (ADS)

Cheeseboro, Belinda D.; Norman, Dara J.

2015-01-01

This study was undertaken to understand the role of large scale environment in the evolution of MIR-selected AGN. In this study we examine AGN candidates in two types of environments: 7 clusters and 6 blank fields. Two types of clusters were studied in this project: 3 virialized and 4 non-virialized. The redshift of the clusters ranged 0.22≤z≤0.28. We used the mid-infrared WISE All-Sky database to identify AGN, applying various methods to refine our AGN candidate selection. To ascertain if there is an excess or deficit of MIR AGN in galaxy clusters vs. blank fields, we compared the AGN candidate distributions in virialized vs. non-virialized clusters to the blank fields. After close examination and comparison of the results to X-ray selected AGN from the Gilmour et al. (2009) study, we concluded that we do not detect an excess or deficit of MIR AGN in our clusters whether the cluster was virialized or non-virialized. This contrasted the conclusion of the Gilmour et al. (2009) study where there was an excess of X-Ray selected AGN in clusters.We also note an interesting feature in our WISE color-color plots that might be used for further investigation.Cheeseboro was supported by the NOAO/KPNO ResearchExperiences for Undergraduates (REU) Program which is funded by theNational Science Foundation Research Experiences for UndergraduatesProgram (AST-1262829).

Advanced Treatment Monitoring for Olympic-Level Athletes Using Unsupervised Modeling Techniques

PubMed Central

Siedlik, Jacob A.; Bergeron, Charles; Cooper, Michael; Emmons, Russell; Moreau, William; Nabhan, Dustin; Gallagher, Philip; Vardiman, John P.

2016-01-01

Context Analysis of injury and illness data collected at large international competitions provides the US Olympic Committee and the national governing bodies for each sport with information to best prepare for future competitions. Research in which authors have evaluated medical contacts to provide the expected level of medical care and sports medicine services at international competitions is limited. Objective To analyze the medical-contact data for athletes, staff, and coaches who participated in the 2011 Pan American Games in Guadalajara, Mexico, using unsupervised modeling techniques to identify underlying treatment patterns. Design Descriptive epidemiology study. Setting Pan American Games. Patients or Other Participants A total of 618 US athletes (337 males, 281 females) participated in the 2011 Pan American Games. Main Outcome Measure(s) Medical data were recorded from the injury-evaluation and injury-treatment forms used by clinicians assigned to the central US Olympic Committee Sport Medicine Clinic and satellite locations during the operational 17-day period of the 2011 Pan American Games. We used principal components analysis and agglomerative clustering algorithms to identify and define grouped modalities. Lift statistics were calculated for within-cluster subgroups. Results Principal component analyses identified 3 components, accounting for 72.3% of the variability in datasets. Plots of the principal components showed that individual contacts focused on 4 treatment clusters: massage, paired manipulation and mobilization, soft tissue therapy, and general medical. Conclusions Unsupervised modeling techniques were useful for visualizing complex treatment data and provided insights for improved treatment modeling in athletes. Given its ability to detect clinically relevant treatment pairings in large datasets, unsupervised modeling should be considered a feasible option for future analyses of medical-contact data from international competitions. PMID:26794628

Genetic characterization of cassava (Manihot esculenta) landraces in Brazil assessed with simple sequence repeats

PubMed Central

2009-01-01

Based on nine microsatellite loci, the aim of this study was to appraise the genetic diversity of 42 cassava (Manihot esculenta) landraces from selected regions in Brazil, and examine how this variety is distributed according to origin in several municipalities in the states of Minas Gerais, São Paulo, Mato Grosso do Sul, Amazonas and Mato Grosso. High diversity values were found among the five above-mentioned regions, with 3.3 alleles per locus on an average, a high percentage of polymorphic loci varying from 88.8% to 100%, an average of 0.265 for observed heterozygosity and 0.570 for gene diversity. Most genetic diversity was concentrated within the regions themselves (HS = 0.52). Cluster analysis and principal component based scatter plotting showed greater similarity among landraces from São Paulo, Mato Grosso do Sul and Amazonas, whereas those from Minas Gerais were clustered into a sub-group within this group. The plants from Mato Grosso, mostly collected in the municipality of General Carneiro, provided the highest differentiation. The migration of human populations is one among the possible reasons for this closer resemblance or greater disparity among plants from the various regions. PMID:21637653

Computer routine adds plotting capabilities to existing programs

NASA Technical Reports Server (NTRS)

Harris, J. C.; Linnekin, J. S.

1966-01-01

PLOTAN, a generalized plot analysis routine written for the IBM 7094 computer, minimizes the difficulties in adding plot capabilities to large existing programs. PLOTAN is used in conjunction with a binary tape writing routine and has the ability to plot any variable on the intermediate binary tape as a function of any other.

NEMAR plotting computer program

NASA Technical Reports Server (NTRS)

Myler, T. R.

1981-01-01

A FORTRAN coded computer program which generates CalComp plots of trajectory parameters is examined. The trajectory parameters are calculated and placed on a data file by the Near Earth Mission Analysis Routine computer program. The plot program accesses the data file and generates the plots as defined by inputs to the plot program. Program theory, user instructions, output definitions, subroutine descriptions and detailed FORTRAN coding information are included. Although this plot program utilizes a random access data file, a data file of the same type and formatted in 102 numbers per record could be generated by any computer program and used by this plot program.

Mars Science Laboratory Launch-Arrival Space Study: A Pork Chop Plot Analysis

NASA Technical Reports Server (NTRS)

Cianciolo, Alicia Dwyer; Powell, Richard; Lockwood, Mary Kae

2006-01-01

Launch-Arrival, or "pork chop", plot analysis can provide mission designers with valuable information and insight into a specific launch and arrival space selected for a mission. The study begins with the array of entry states for each pair of selected Earth launch and Mars arrival dates, and nominal entry, descent and landing trajectories are simulated for each pair. Parameters of interest, such as maximum heat rate, are plotted in launch-arrival space. The plots help to quickly identify launch and arrival regions that are not feasible under current constraints or technology and also provide information as to what technologies may need to be developed to reach a desired region. This paper provides a discussion of the development, application, and results of a pork chop plot analysis to the Mars Science Laboratory mission. This technique is easily applicable to other missions at Mars and other destinations.

Using recurrence plot analysis for software execution interpretation and fault detection

NASA Astrophysics Data System (ADS)

Mosdorf, M.

2015-09-01

This paper shows a method targeted at software execution interpretation and fault detection using recurrence plot analysis. In in the proposed approach recurrence plot analysis is applied to software execution trace that contains executed assembly instructions. Results of this analysis are subject to further processing with PCA (Principal Component Analysis) method that simplifies number coefficients used for software execution classification. This method was used for the analysis of five algorithms: Bubble Sort, Quick Sort, Median Filter, FIR, SHA-1. Results show that some of the collected traces could be easily assigned to particular algorithms (logs from Bubble Sort and FIR algorithms) while others are more difficult to distinguish.

Relative equilibrium plot improves graphical analysis and allows bias correction of SUVR in quantitative [11C]PiB PET studies

PubMed Central

Zhou, Yun; Sojkova, Jitka; Resnick, Susan M.; Wong, Dean F.

2012-01-01

Both the standardized uptake value ratio (SUVR) and the Logan plot result in biased distribution volume ratios (DVR) in ligand-receptor dynamic PET studies. The objective of this study is to use a recently developed relative equilibrium-based graphical plot (RE plot) method to improve and simplify the two commonly used methods for quantification of [11C]PiB PET. Methods The overestimation of DVR in SUVR was analyzed theoretically using the Logan and the RE plots. A bias-corrected SUVR (bcSUVR) was derived from the RE plot. Seventy-eight [11C]PiB dynamic PET scans (66 from controls and 12 from mildly cognitively impaired participants (MCI) from the Baltimore Longitudinal Study of Aging (BLSA)) were acquired over 90 minutes. Regions of interest (ROIs) were defined on coregistered MRIs. Both the ROI and pixelwise time activity curves (TACs) were used to evaluate the estimates of DVR. DVRs obtained using the Logan plot applied to ROI TACs were used as a reference for comparison of DVR estimates. Results Results from the theoretical analysis were confirmed by human studies. ROI estimates from the RE plot and the bcSUVR were nearly identical to those from the Logan plot with ROI TACs. In contrast, ROI estimates from DVR images in frontal, temporal, parietal, cingulate regions, and the striatum were underestimated by the Logan plot (controls 4 – 12%; MCI 9 – 16%) and overestimated by the SUVR (controls 8 – 16%; MCI 16 – 24%). This bias was higher in the MCI group than in controls (p < 0.01) but was not present when data were analyzed using either the RE plot or the bcSUVR. Conclusion The RE plot improves pixel-wise quantification of [11C]PiB dynamic PET compared to the conventional Logan plot. The bcSUVR results in lower bias and higher consistency of DVR estimates compared to SUVR. The RE plot and the bcSUVR are practical quantitative approaches that improve the analysis of [11C]PiB studies. PMID:22414634

Recurrence plots and recurrence quantification analysis of human motion data

NASA Astrophysics Data System (ADS)

Josiński, Henryk; Michalczuk, Agnieszka; Świtoński, Adam; Szczesna, Agnieszka; Wojciechowski, Konrad

2016-06-01

The authors present exemplary application of recurrence plots, cross recurrence plots and recurrence quantification analysis for the purpose of exploration of experimental time series describing selected aspects of human motion. Time series were extracted from treadmill gait sequences which were recorded in the Human Motion Laboratory (HML) of the Polish-Japanese Academy of Information Technology in Bytom, Poland by means of the Vicon system. Analysis was focused on the time series representing movements of hip, knee, ankle and wrist joints in the sagittal plane.

Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob.

PubMed

Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven

2018-01-16

Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob). The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments. Copyright © 2017 Elsevier B.V. All rights reserved.

[Study on discrimination of varieties of fire resistive coating for steel structure based on near-infrared spectroscopy].

PubMed

Xue, Gang; Song, Wen-qi; Li, Shu-chao

2015-01-01

In order to achieve the rapid identification of fire resistive coating for steel structure of different brands in circulating, a new method for the fast discrimination of varieties of fire resistive coating for steel structure by means of near infrared spectroscopy was proposed. The raster scanning near infrared spectroscopy instrument and near infrared diffuse reflectance spectroscopy were applied to collect the spectral curve of different brands of fire resistive coating for steel structure and the spectral data were preprocessed with standard normal variate transformation(standard normal variate transformation, SNV) and Norris second derivative. The principal component analysis (principal component analysis, PCA)was used to near infrared spectra for cluster analysis. The analysis results showed that the cumulate reliabilities of PC1 to PC5 were 99. 791%. The 3-dimentional plot was drawn with the scores of PC1, PC2 and PC3 X 10, which appeared to provide the best clustering of the varieties of fire resistive coating for steel structure. A total of 150 fire resistive coating samples were divided into calibration set and validation set randomly, the calibration set had 125 samples with 25 samples of each variety, and the validation set had 25 samples with 5 samples of each variety. According to the principal component scores of unknown samples, Mahalanobis distance values between each variety and unknown samples were calculated to realize the discrimination of different varieties. The qualitative analysis model for external verification of unknown samples is a 10% recognition ration. The results demonstrated that this identification method can be used as a rapid, accurate method to identify the classification of fire resistive coating for steel structure and provide technical reference for market regulation.

A neural-network potential through charge equilibration for WS2: From clusters to sheets

NASA Astrophysics Data System (ADS)

Hafizi, Roohollah; Ghasemi, S. Alireza; Hashemifar, S. Javad; Akbarzadeh, Hadi

2017-12-01

In the present work, we use a machine learning method to construct a high-dimensional potential for tungsten disulfide using a charge equilibration neural-network technique. A training set of stoichiometric WS2 clusters is prepared in the framework of density functional theory. After training the neural-network potential, the reliability and transferability of the potential are verified by performing a crystal structure search on bulk phases of WS2 and by plotting energy-area curves of two different monolayers. Then, we use the potential to investigate various triangular nano-clusters and nanotubes of WS2. In the case of nano-structures, we argue that 2H atomic configurations with sulfur rich edges are thermodynamically more stable than the other investigated configurations. We also studied a number of WS2 nanotubes which revealed that 1T tubes with armchair chirality exhibit lower bending stiffness.

CO2 adsorption on gas-phase Cu4-xPtx (x = 0-4) clusters: a DFT study.

PubMed

Gálvez-González, Luis E; Juárez-Sánchez, J Octavio; Pacheco-Contreras, Rafael; Garzón, Ignacio L; Paz-Borbón, Lauro Oliver; Posada-Amarillas, Alvaro

2018-06-13

Transition and noble metal clusters have proven to be critical novel materials, potentially offering major advantages over conventional catalysts in a range of value-added catalytic processess such as carbon dioxide transformation to methanol. In this work, a systematic computational study of CO2 adsorption on gas-phase Cu4-xPtx (x = 0-4) clusters is performed. An exhaustive potential energy surface exploration is initially performed using our recent density functional theory basin-hopping global optimization implementation. Ground-state and low-lying energy isomers are identified for Cu4-xPtx clusters. Secondly, a CO2 molecule adsorption process is analyzed on the ground-state Cu4-xPtx configurations, as a function of cluster composition. Our results show that the gas-phase linear CO2 molecule is deformed upon adsorption, with its bend angle varying from about 132° to 139°. Cu4-xPtx cluster geometries remain unchanged after CO2 adsorption, with the exception of Cu3Pt1 and Pt4 clusters. For these particular cases, a structural conversion between the ground-state geometry and the corresponding first isomer configurations is found to be assisted by the CO2 adsorption. For all clusters, the energy barriers between the ground-state and first isomer structures are explored. Our calculated CO2 adsorption energies are found to be larger for Pt-rich clusters, exhibiting a volcano-type plot. The overall effect of a hybrid functional including dispersion forces is also discussed.

Multiple filters affect tree species assembly in mid-latitude forest communities.

PubMed

Kubota, Y; Kusumoto, B; Shiono, T; Ulrich, W

2018-05-01

Species assembly patterns of local communities are shaped by the balance between multiple abiotic/biotic filters and dispersal that both select individuals from species pools at the regional scale. Knowledge regarding functional assembly can provide insight into the relative importance of the deterministic and stochastic processes that shape species assembly. We evaluated the hierarchical roles of the α niche and β niches by analyzing the influence of environmental filtering relative to functional traits on geographical patterns of tree species assembly in mid-latitude forests. Using forest plot datasets, we examined the α niche traits (leaf and wood traits) and β niche properties (cold/drought tolerance) of tree species, and tested non-randomness (clustering/over-dispersion) of trait assembly based on null models that assumed two types of species pools related to biogeographical regions. For most plots, species assembly patterns fell within the range of random expectation. However, particularly for cold/drought tolerance-related β niche properties, deviation from randomness was frequently found; non-random clustering was predominant in higher latitudes with harsh climates. Our findings demonstrate that both randomness and non-randomness in trait assembly emerged as a result of the α and β niches, although we suggest the potential role of dispersal processes and/or species equalization through trait similarities in generating the prevalence of randomness. Clustering of β niche traits along latitudinal climatic gradients provides clear evidence of species sorting by filtering particular traits. Our results reveal that multiple filters through functional niches and stochastic processes jointly shape geographical patterns of species assembly across mid-latitude forests.

Integrating P3 Data Into P2 Analyses: What is the Added Value

Treesearch

James R. Steinman

2001-01-01

The Forest Inventory and Analysis and Forest Health Monitoring Programs of the USDA Forest Service are integrating field procedures for measuring their networks of plots throughout the United States. These plots are now referred to as Phase 2 (P2) and Phase 3 (P3) plots, respectively, and 1 out of every 16 P2 plots will also be a P3 plot. Mensurational methods will be...

Flyby Error Analysis Based on Contour Plots for the Cassini Tour

NASA Technical Reports Server (NTRS)

Stumpf, P. W.; Gist, E. M.; Goodson, T. D.; Hahn, Y.; Wagner, S. V.; Williams, P. N.

2008-01-01

The maneuver cancellation analysis consists of cost contour plots employed by the Cassini maneuver team. The plots are two-dimensional linear representations of a larger six-dimensional solution to a multi-maneuver, multi-encounter mission at Saturn. By using contours plotted with the dot product of vectors B and R and the dot product of vectors B and T components, it is possible to view the effects delta V on for various encounter positions in the B-plane. The plot is used in operations to help determine if the Approach Maneuver (ensuing encounter minus three days) and/or the Cleanup Maneuver (ensuing encounter plus three days) can be cancelled and also is a linear check of an integrated solution.

Eye-gaze control of the computer interface: Discrimination of zoom intent

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldberg, J.H.; Schryver, J.C.

1993-10-01

An analysis methodology and associated experiment were developed to assess whether definable and repeatable signatures of eye-gaze characteristics are evident, preceding a decision to zoom-in, zoom-out, or not to zoom at a computer interface. This user intent discrimination procedure can have broad application in disability aids and telerobotic control. Eye-gaze was collected from 10 subjects in a controlled experiment, requiring zoom decisions. The eye-gaze data were clustered, then fed into a multiple discriminant analysis (MDA) for optimal definition of heuristics separating the zoom-in, zoom-out, and no-zoom conditions. Confusion matrix analyses showed that a number of variable combinations classified at amore » statistically significant level, but practical significance was more difficult to establish. Composite contour plots demonstrated the regions in parameter space consistently assigned by the MDA to unique zoom conditions. Peak classification occurred at about 1200--1600 msec. Improvements in the methodology to achieve practical real-time zoom control are considered.« less

Application of chemometrics in quality control of Turmeric (Curcuma longa) based on Ultra-violet, Fourier transform-infrared and 1H NMR spectroscopy.

PubMed

Gad, Haidy A; Bouzabata, Amel

2017-12-15

Turmeric (Curcuma longa L.) belongs to the family Zingiberaceae that is widely used as a spice in food preparations in addition to its biological activities. UV, FT-IR, 1 H NMR in addition to HPLC were applied to construct a metabolic fingerprint for Turmeric in an attempt to assess its quality. 30 samples were analyzed, and then principal component analysis (PCA) and hierarchical clustering analysis (HCA) were utilized to assess the differences and similarities between collected samples. PCA score plot based on both HPLC and UV spectroscopy showed the same discriminatory pattern, where the samples were segregated into four main groups depending on their total curcuminoids content. The results revealed that UV could be utilized as a simple and rapid alternative for HPLC. However, FT-IR failed to discriminate between the same species. By applying 1 H NMR, the metabolic variability between samples was more evident in the essential oils/fatty acid region. Copyright © 2017 Elsevier Ltd. All rights reserved.

A long-term evaluation of applied nucleation as a strategy to facilitate forest restoration.

PubMed

Corbin, Jeffrey D; Robinson, George R; Hafkemeyer, Lauren M; Handel, Steven N

2016-01-01

Applied nucleation is a restoration technique that seeks to facilitate woody-plant establishment by attracting birds or other animals that may introduce seeds of dispersal-limited species. In 1991, an experimental test of applied nucleation was initiated in an abandoned landfill in New Jersey, USA. Trees and shrubs were planted into 16 10 x 10 m plots, covering < 3% of the 6-ha site. In 2010-2011, we sampled the plant community to test the impact of the treatments on forest cover and plant biodiversity. Site-wide forest cover increased substantially in the 19 years since planting from none to 59%. The original planted plots had significantly higher stem density, particularly of bird-dispersed species, than unplanted areas. Species composition outside the planted plots was dominated by the wind-dispersed Fraxinus americana and several small-seeded bird-dispersed species, but there were few species indicative of later successional stages. The expected model of successional development via the nucleation model that rates of colonization would be highest near plantings and that forest cover would spread outward from established clusters was not supported after this time span. Given the site's isolation from potential sources of woody propagules, the experimental treatments may not have been enough to overcome many species' dispersal limitation. Regardless of the mechanism, however, the treatments transformed the once essentially treeless site into a densely wooded habitat, and did so at a rate faster than other descriptions of reforestation following disturbances or land-use changes in the region. Despite the relatively low species richness of the community, this experiment demonstrated that reforestation of even severely degraded habitat can be achieved with minimal management after site preparation and cluster plantings.

Shifts in Plant Assemblages Reduce the Richness of Galling Insects Across Edge-Affected Habitats in the Atlantic Forest.

PubMed

Souza, Danielle G; Santos, Jean C; Oliveira, Marcondes A; Tabarelli, Marcelo

2016-10-01

Impacts of habitat loss and fragmentation on specialist herbivores have been rarely addressed. Here we examine the structure of plant and galling insect assemblages in a fragmented landscape of the Atlantic forest to verify a potential impoverishment of these assemblages mediated by edge effects. Saplings and galling insects were recorded once within a 0.1-ha area at habitat level, covering forest interior stands, forest edges, and small fragments. A total of 1,769 saplings from 219 tree species were recorded across all three habitats, with differences in terms of sapling abundance and species richness. Additionally, edge-affected habitats exhibited reduced richness of both host-plant and galling insects at plot and habitat spatial scale. Attack levels also differed among forest types at habitat spatial scale (21.1% of attacked stems in forest interior, 12.4% in small fragments but only 8.5% in forest edges). Plot ordination resulted in three clearly segregated clusters: one formed by forest interior, one by small fragments, and another formed by edge plots. Finally, the indicator species analysis identified seven and one indicator plant species in forest interior and edge-affected habitats, respectively. Consequently, edge effects lead to formation of distinct taxonomic groups and also an impoverished assemblage of plants and galling insects at multiple spatial scales. The results of the present study indicate that fragmentation-related changes in plant assemblages can have a cascade effects on specialist herbivores. Accordingly, hyperfragmented landscapes may not be able to retain an expressive portion of tropical biodiversity. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cutoffs of Short-Term Heart Rate Variability Parameters in Brazilian Adolescents Male.

PubMed

Farah, Breno Quintella; Christofaro, Diego Giulliano Destro; Cavalcante, Bruno Remígio; Andrade-Lima, Aluísio; Germano-Soares, Antonio Henrique; Vanderlei, Luiz Carlos Marques; Lanza, Fernanda Cordoba; Ritti-Dias, Raphael Mendes

2018-05-15

A low heart rate variability (HRV) has been associated with cardiovascular risk factors in adolescents. However, no cut-off points are known for HRV parameters in this age group, making it difficult to use in clinical practice. Thus, the aims of the current study were to establish cutoffs of HRV parameters and to examine their association with cardiovascular risk in Brazilian adolescents male. For this reason, this cross-sectional study included 1152 adolescent boys (16.6 ± 1.2 years old). HRV measures of time (SD of all RR intervals, root mean square of the squared differences between adjacent normal RR intervals, and the percentage of adjacent intervals over 50 ms), frequency domains [low (LF) and high (HF) frequency], and Poincaré plot (SD1, SD2 and SD1/SD2 ratio) were assessed. Cardiovascular risk was assessed by sum of abdominal obesity, high blood pressure, overweight, and low physical activity level. The proposed cutoffs showed moderate to high sensitivity, specificity, and area under curve values (p < 0.05). HRV frequency parameters were statistically superior when compared to time-domain and Poincaré plot parameters. The binary logistic regression analysis indicated that all proposed HRV cutoffs were independently associated with a clustering of cardiovascular risk factors, with greater magnitude of HF and SD1/SD2 ratio (two or more risk factors: OR = 3.59 and 95% CI 1.76-7.34). In conclusion, proposed HRV cutoffs have moderate to high sensitivity in detecting of the cardiovascular risk factor and HRV frequency-domain were better discriminants of cardiovascular risk than time-domain and Poincaré plot parameters.

Analysis of variance calculations for irregular experiments

Treesearch

Jonathan W. Wright

1977-01-01

Irregular experiments may be more useful than much smaller regular experiments and can be analyzed statistically without undue expenditure of time. For a few missing plots, standard methods of calculating missing-plot values can be used. For more missing plots (up to 10 percent), seedlot means or randomly chosen plot means of the same seedlot can be substituted for...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wackerbarth, David

Sandia National Laboratories has developed a computer program to review, reduce and manipulate waveform data. PlotData is designed for post-acquisition waveform data analysis. PlotData is both a post-acquisition and an advanced interactive data analysis environment. PlotData requires unidirectional waveform data with both uniform and discrete time-series measurements. PlotData operates on a National Instruments' LabVIEW™ software platform. Using PlotData, the user can capture waveform data from digitizing oscilloscopes over a GPIB, USB and Ethernet interface from Tektronix, Lecroy or Agilent scopes. PlotData can both import and export several types of binary waveform files including, but not limited to, Tektronix .wmf files,more » Lecroy.trc files and xy pair ASCIIfiles. Waveform manipulation includes numerous math functions, integration, differentiation, smoothing, truncation, and other specialized data reduction routines such as VISAR, POV, PVDF (Bauer) piezoelectric gauges, and piezoresistive gauges such as carbon manganin pressure gauges.« less

BEANS - a software package for distributed Big Data analysis

NASA Astrophysics Data System (ADS)

Hypki, Arkadiusz

2018-07-01

BEANS software is a web-based, easy to install and maintain, new tool to store and analyse in a distributed way a massive amount of data. It provides a clear interface for querying, filtering, aggregating, and plotting data from an arbitrary number of data sets. Its main purpose is to simplify the process of storing, examining, and finding new relations in huge data sets. The software is an answer to a growing need of the astronomical community to have a versatile tool to store, analyse, and compare the complex astrophysical numerical simulations with observations (e.g. simulations of the Galaxy or star clusters with the Gaia archive). However, this software was built in a general form and it is ready to use in any other research field. It can be used as a building block for other open-source software too.

BEANS - a software package for distributed Big Data analysis

NASA Astrophysics Data System (ADS)

Hypki, Arkadiusz

2018-03-01

BEANS software is a web based, easy to install and maintain, new tool to store and analyse in a distributed way a massive amount of data. It provides a clear interface for querying, filtering, aggregating, and plotting data from an arbitrary number of datasets. Its main purpose is to simplify the process of storing, examining and finding new relations in huge datasets. The software is an answer to a growing need of the astronomical community to have a versatile tool to store, analyse and compare the complex astrophysical numerical simulations with observations (e.g. simulations of the Galaxy or star clusters with the Gaia archive). However, this software was built in a general form and it is ready to use in any other research field. It can be used as a building block for other open source software too.

Carbon, Hydrogen, and Oxygen Isotope Ratios of Cellulose from Plants Having Intermediary Photosynthetic Modes 1

PubMed Central

Sternberg, Leonel O'Reilly; Deniro, Michael J.; Ting, Irwin P.

1984-01-01

Carbon and hydrogen isotope ratios of cellulose nitrate and oxygen isotope ratios of cellulose from species of greenhouse plants having different photosynthetic modes were determined. When hydrogen isotope ratios are plotted against carbon isotope ratios, four clusters of points are discernible, each representing different photosynthetic modes: C3 plants, C4 plants, CAM plants, and C3 plants that can shift to CAM or show the phenomenon referred to as CAM-cycling. The combination of oxygen and carbon isotope ratios does not distinguish among the different photosynthetic modes. Analysis of the carbon and hydrogen isotope ratios of cellulose nitrate should prove useful for screening different photosynthetic modes in field specimens that grew near one another. This method will be particularly useful for detection of plants which show CAM-cycling. PMID:16663360

Remote sensing of soils in the eastern Palouse region with Landsat Thematic Mapper

NASA Technical Reports Server (NTRS)

Frazier, B. E.; Cheng, Yaan

1989-01-01

Soils of the Palouse region of eastern Washington State were investigated using Landsat Thematic Mapper (TM) band ratios to discriminate areas where erosion has caused paleosols to be exposed. Ratioed data were clustered and plotted to show soil lines which could be subdivided into various levels of organic matter and iron oxides. Successfully classified scenes of a summer fallow (bare soil) field were obtained with band ratios 1/4, 3/4, and 5/4 to map organic carbon and 3/4, 5/4, and 5/3 for the iron/carbon ratio indicator of erosion. Regression models were made with 5/4 data and organic carbon and 5/3 data and the iron/carbon ratio. Based on this analysis, 21 percent of the test field soils are exposed or nearly exposed paleosols.

Understanding the importance of the temperature dependence of viscosity on the crystallization dynamics in the Ge2Sb2Te5 phase-change material

NASA Astrophysics Data System (ADS)

Aladool, A.; Aziz, M. M.; Wright, C. D.

2017-06-01

The crystallization dynamics in the phase-change material Ge2Sb2Te5 is modelled using the more detailed Master equation method over a wide range of heating rates commensurate with published ultrafast calorimetry experiments. Through the attachment and detachment of monomers, the Master rate equation naturally traces nucleation and growth of crystallites with temperature history to calculate the transient distribution of cluster sizes in the material. Both the attachment and detachment rates in this theory are strong functions of viscosity, and thus, the value of viscosity and its dependence on temperature significantly affect the crystallization process. In this paper, we use the physically realistic Mauro-Yue-Ellison-Gupta-Allan viscosity model in the Master equation approach to study the role of the viscosity model parameters on the crystallization dynamics in Ge2Sb2Te5 under ramped annealing conditions with heating rates up to 4 × 104 K/s. Furthermore, due to the relatively low computational cost of the Master equation method compared to atomistic level computations, an iterative numerical approach was developed to fit theoretical Kissinger plots simulated with the Master equation system to experimental Kissinger plots from ultrafast calorimetry measurements at increasing heating rates. This provided a more rigorous method (incorporating both nucleation and growth processes) to extract the viscosity model parameters from the analysis of experimental data. The simulations and analysis revealed the strong coupling between the glass transition temperature and fragility index in the viscosity and crystallization models and highlighted the role of the dependence of the glass transition temperature on the heating rate for the accurate estimation of the fragility index of phase-change materials from the analysis of experimental measurements.

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

The second molecular epidemiological study of HIV infection in Mongolia between 2010 and 2016.

PubMed

Jagdagsuren, Davaalkham; Hayashida, Tsunefusa; Takano, Misao; Gombo, Erdenetuya; Zayasaikhan, Setsen; Kanayama, Naomi; Tsuchiya, Kiyoto; Oka, Shinichi

2017-01-01

Our previous 2005-2009 molecular epidemiological study in Mongolia identified a hot spot of HIV-1 transmission in men who have sex with men (MSM). To control the infection, we collaborated with NGOs to promote safer sex and HIV testing since mid-2010. In this study, we carried out the second molecular epidemiological survey between 2010 and 2016 to determine the status of HIV-1 infection in Mongolia. The study included 143 new cases of HIV-1 infection. Viral RNA was extracted from stocked plasma samples and sequenced for the pol and the env regions using the Sanger method. Near-full length sequencing using MiSeq was performed in 3 patients who were suspected to be infected with recombinant HIV-1. Phylogenetic analysis was performed using the neighbor-joining method and Bayesian Markov chain Monte Carlo method. MSM was the main transmission route in the previous and current studies. However, heterosexual route showed a significant increase in recent years. Phylogenetic analysis documented three taxa; Mongolian B, Korean B, and CRF51_01B, though the former two were also observed in the previous study. CRF51_01B, which originated from Singapore and Malaysia, was confirmed by near-full length sequencing. Although these strains were mainly detected in MSM, they were also found in increasing numbers of heterosexual males and females. Bayesian phylogenetic analysis estimated transmission of CRF51_01B into Mongolia around early 2000s. An extended Bayesian skyline plot showed a rapid increase in the effective population size of Mongolian B cluster around 2004 and that of CRF51_01B cluster around 2011. HIV-1 infection might expand to the general population in Mongolia. Our study documented a new cluster of HIV-1 transmission, enhancing our understanding of the epidemiological status of HIV-1 in Mongolia.

Relative equilibrium plot improves graphical analysis and allows bias correction of standardized uptake value ratio in quantitative 11C-PiB PET studies.

PubMed

Zhou, Yun; Sojkova, Jitka; Resnick, Susan M; Wong, Dean F

2012-04-01

Both the standardized uptake value ratio (SUVR) and the Logan plot result in biased distribution volume ratios (DVRs) in ligand-receptor dynamic PET studies. The objective of this study was to use a recently developed relative equilibrium-based graphical (RE) plot method to improve and simplify the 2 commonly used methods for quantification of (11)C-Pittsburgh compound B ((11)C-PiB) PET. The overestimation of DVR in SUVR was analyzed theoretically using the Logan and the RE plots. A bias-corrected SUVR (bcSUVR) was derived from the RE plot. Seventy-eight (11)C-PiB dynamic PET scans (66 from controls and 12 from participants with mild cognitive impaired [MCI] from the Baltimore Longitudinal Study of Aging) were acquired over 90 min. Regions of interest (ROIs) were defined on coregistered MR images. Both the ROI and the pixelwise time-activity curves were used to evaluate the estimates of DVR. DVRs obtained using the Logan plot applied to ROI time-activity curves were used as a reference for comparison of DVR estimates. Results from the theoretic analysis were confirmed by human studies. ROI estimates from the RE plot and the bcSUVR were nearly identical to those from the Logan plot with ROI time-activity curves. In contrast, ROI estimates from DVR images in frontal, temporal, parietal, and cingulate regions and the striatum were underestimated by the Logan plot (controls, 4%-12%; MCI, 9%-16%) and overestimated by the SUVR (controls, 8%-16%; MCI, 16%-24%). This bias was higher in the MCI group than in controls (P < 0.01) but was not present when data were analyzed using either the RE plot or the bcSUVR. The RE plot improves pixelwise quantification of (11)C-PiB dynamic PET, compared with the conventional Logan plot. The bcSUVR results in lower bias and higher consistency of DVR estimates than of SUVR. The RE plot and the bcSUVR are practical quantitative approaches that improve the analysis of (11)C-PiB studies.

Rapid discrimination of the causal agents of urinary tract infection using ToF-SIMS with chemometric cluster analysis

NASA Astrophysics Data System (ADS)

Fletcher, John S.; Henderson, Alexander; Jarvis, Roger M.; Lockyer, Nicholas P.; Vickerman, John C.; Goodacre, Royston

2006-07-01

Advances in time of flight secondary ion mass spectrometry (ToF-SIMS) have enabled this technique to become a powerful tool for the analysis of biological samples. Such samples are often very complex and as a result full interpretation of the acquired data can be extremely difficult. To simplify the interpretation of these information rich data, the use of chemometric techniques is becoming widespread in the ToF-SIMS community. Here we discuss the application of principal components-discriminant function analysis (PC-DFA) to the separation and classification of a number of bacterial samples that are known to be major causal agents of urinary tract infection. A large data set has been generated using three biological replicates of each isolate and three machine replicates were acquired from each biological replicate. Ordination plots generated using the PC-DFA are presented demonstrating strain level discrimination of the bacteria. The results are discussed in terms of biological differences between certain species and with reference to FT-IR, Raman spectroscopy and pyrolysis mass spectrometric studies of similar samples.

[A study of Boletus bicolor from different areas using Fourier transform infrared spectrometry].

PubMed

Zhou, Zai-Jin; Liu, Gang; Ren, Xian-Pei

2010-04-01

It is hard to differentiate the same species of wild growing mushrooms from different areas by macromorphological features. In this paper, Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis was used to identify 58 samples of boletus bicolor from five different areas. Based on the fingerprint infrared spectrum of boletus bicolor samples, principal component analysis was conducted on 58 boletus bicolor spectra in the range of 1 350-750 cm(-1) using the statistical software SPSS 13.0. According to the result, the accumulated contributing ratio of the first three principal components accounts for 88.87%. They included almost all the information of samples. The two-dimensional projection plot using first and second principal component is a satisfactory clustering effect for the classification and discrimination of boletus bicolor. All boletus bicolor samples were divided into five groups with a classification accuracy of 98.3%. The study demonstrated that wild growing boletus bicolor at species level from different areas can be identified by FTIR spectra combined with principal components analysis.

A tool to determine crown and plot canopy transparency for forest inventory and analysis phase 3 plots using digital photographs

Treesearch

Matthew F. Winn; Philip A. Araman

2012-01-01

The USDA Forest Service Forest Inventory and Analysis (FIA) program collects crown foliage transparency estimates for individual trees on Phase 3 (P3) inventory plots. The FIA crown foliage estimate is obtained from a pair of perpendicular side views of the tree. Researchers with the USDA Forest Service Southern Research Station have developed a computer program that...

An urban forest-inventory-and-analysis investigation in Oregon and Washington

Treesearch

Jacob L. Strunk; John R. Mills; Paul Ries; Hailemariam Temesgen; Lacey Jeroue

2016-01-01

The U.S. Department of Agriculture (USDA) Forest Service, Forest Inventory and Analysis program recently inventoried trees on 257 sample plots in the urbanized areas of Oregon and Washington. Plots were located on the standard grid (≈1 plot/2428 ha) and installed with the 4-subplot footprint (≈.067 ha with 4 circular subplots). Using these data, we examined: 1) use of...

Web-based interactive access, analysis and comparison of remotely sensed and in situ measured temperature data

NASA Astrophysics Data System (ADS)

Eberle, Jonas; Urban, Marcel; Hüttich, Christian; Schmullius, Christiane

2014-05-01

Numerous datasets providing temperature information from meteorological stations or remote sensing satellites are available. However, the challenging issue is to search in the archives and process the time series information for further analysis. These steps can be automated for each individual product, if the pre-conditions are complied, e.g. data access through web services (HTTP, FTP) or legal rights to redistribute the datasets. Therefore a python-based package was developed to provide data access and data processing tools for MODIS Land Surface Temperature (LST) data, which is provided by NASA Land Processed Distributed Active Archive Center (LPDAAC), as well as the Global Surface Summary of the Day (GSOD) and the Global Historical Climatology Network (GHCN) daily datasets provided by NOAA National Climatic Data Center (NCDC). The package to access and process the information is available as web services used by an interactive web portal for simple data access and analysis. Tools for time series analysis were linked to the system, e.g. time series plotting, decomposition, aggregation (monthly, seasonal, etc.), trend analyses, and breakpoint detection. Especially for temperature data a plot was integrated for the comparison of two temperature datasets based on the work by Urban et al. (2013). As a first result, a kernel density plot compares daily MODIS LST from satellites Aqua and Terra with daily means from GSOD and GHCN datasets. Without any data download and data processing, the users can analyze different time series datasets in an easy-to-use web portal. As a first use case, we built up this complimentary system with remotely sensed MODIS data and in situ measurements from meteorological stations for Siberia within the Siberian Earth System Science Cluster (www.sibessc.uni-jena.de). References: Urban, Marcel; Eberle, Jonas; Hüttich, Christian; Schmullius, Christiane; Herold, Martin. 2013. "Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale." Remote Sens. 5, no. 5: 2348-2367. Further materials: Eberle, Jonas; Clausnitzer, Siegfried; Hüttich, Christian; Schmullius, Christiane. 2013. "Multi-Source Data Processing Middleware for Land Monitoring within a Web-Based Spatial Data Infrastructure for Siberia." ISPRS Int. J. Geo-Inf. 2, no. 3: 553-576.

Identification of both copy number variation-type and constant-type core elements in a large segmental duplication region of the mouse genome

PubMed Central

2013-01-01

Background Copy number variation (CNV), an important source of diversity in genomic structure, is frequently found in clusters called CNV regions (CNVRs). CNVRs are strongly associated with segmental duplications (SDs), but the composition of these complex repetitive structures remains unclear. Results We conducted self-comparative-plot analysis of all mouse chromosomes using the high-speed and large-scale-homology search algorithm SHEAP. For eight chromosomes, we identified various types of large SD as tartan-checked patterns within the self-comparative plots. A complex arrangement of diagonal split lines in the self-comparative-plots indicated the presence of large homologous repetitive sequences. We focused on one SD on chromosome 13 (SD13M), and developed SHEPHERD, a stepwise ab initio method, to extract longer repetitive elements and to characterize repetitive structures in this region. Analysis using SHEPHERD showed the existence of 60 core elements, which were expected to be the basic units that form SDs within the repetitive structure of SD13M. The demonstration that sequences homologous to the core elements (>70% homology) covered approximately 90% of the SD13M region indicated that our method can characterize the repetitive structure of SD13M effectively. Core elements were composed largely of fragmented repeats of a previously identified type, such as long interspersed nuclear elements (LINEs), together with partial genic regions. Comparative genome hybridization array analysis showed that whereas 42 core elements were components of CNVR that varied among mouse strains, 8 did not vary among strains (constant type), and the status of the others could not be determined. The CNV-type core elements contained significantly larger proportions of long terminal repeat (LTR) types of retrotransposon than the constant-type core elements, which had no CNV. The higher divergence rates observed in the CNV-type core elements than in the constant type indicate that the CNV-type core elements have a longer evolutionary history than constant-type core elements in SD13M. Conclusions Our methodology for the identification of repetitive core sequences simplifies characterization of the structures of large SDs and detailed analysis of CNV. The results of detailed structural and quantitative analyses in this study might help to elucidate the biological role of one of the SDs on chromosome 13. PMID:23834397

Systematic Study on the Self-Assembled Hexagonal Au Voids, Nano-Clusters and Nanoparticles on GaN (0001).

PubMed

Pandey, Puran; Sui, Mao; Li, Ming-Yu; Zhang, Quanzhen; Kim, Eun-Soo; Lee, Jihoon

2015-01-01

Au nano-clusters and nanoparticles (NPs) have been widely utilized in various electronic, optoelectronic, and bio-medical applications due to their great potentials. The size, density and configuration of Au NPs play a vital role in the performance of these devices. In this paper, we present a systematic study on the self-assembled hexagonal Au voids, nano-clusters and NPs fabricated on GaN (0001) by the variation of annealing temperature and deposition amount. At relatively low annealing temperatures between 400 and 600°C, the fabrication of hexagonal shaped Au voids and Au nano-clusters are observed and discussed based on the diffusion limited aggregation model. The size and density of voids and nano-clusters can systematically be controlled. The self-assembled Au NPs are fabricated at comparatively high temperatures from 650 to 800°C based on the Volmer-Weber growth model and also the size and density can be tuned accordingly. The results are symmetrically analyzed and discussed in conjunction with the diffusion theory and thermodynamics by utilizing AFM and SEM images, EDS maps and spectra, FFT power spectra, cross-sectional line-profiles and size and density plots.

Systematic Study on the Self-Assembled Hexagonal Au Voids, Nano-Clusters and Nanoparticles on GaN (0001)

PubMed Central

Pandey, Puran; Sui, Mao; Li, Ming-Yu; Zhang, Quanzhen; Kim, Eun-Soo; Lee, Jihoon

2015-01-01

Au nano-clusters and nanoparticles (NPs) have been widely utilized in various electronic, optoelectronic, and bio-medical applications due to their great potentials. The size, density and configuration of Au NPs play a vital role in the performance of these devices. In this paper, we present a systematic study on the self-assembled hexagonal Au voids, nano-clusters and NPs fabricated on GaN (0001) by the variation of annealing temperature and deposition amount. At relatively low annealing temperatures between 400 and 600°C, the fabrication of hexagonal shaped Au voids and Au nano-clusters are observed and discussed based on the diffusion limited aggregation model. The size and density of voids and nano-clusters can systematically be controlled. The self-assembled Au NPs are fabricated at comparatively high temperatures from 650 to 800°C based on the Volmer-Weber growth model and also the size and density can be tuned accordingly. The results are symmetrically analyzed and discussed in conjunction with the diffusion theory and thermodynamics by utilizing AFM and SEM images, EDS maps and spectra, FFT power spectra, cross-sectional line-profiles and size and density plots. PMID:26285135

iCanPlot: Visual Exploration of High-Throughput Omics Data Using Interactive Canvas Plotting

PubMed Central

Sinha, Amit U.; Armstrong, Scott A.

2012-01-01

Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression. PMID:22393367

Accuracy assessments and areal estimates using two-phase stratified random sampling, cluster plots, and the multivariate composite estimator

Treesearch

Raymond L. Czaplewski

2000-01-01

Consider the following example of an accuracy assessment. Landsat data are used to build a thematic map of land cover for a multicounty region. The map classifier (e.g., a supervised classification algorithm) assigns each pixel into one category of land cover. The classification system includes 12 different types of forest and land cover: black spruce, balsam fir,...

New Agricultural Settlement, Meheba River, Zambia, Africa

NASA Technical Reports Server (NTRS)

1990-01-01

This infra-red view of a new settlement along the Meheba River, Zambia, Africa (12.5S, 26.0E) resembles the resettlement clusters in the Amazon basin of Brazil. However, this settlement is on savanna land not a tropical forest region, so relatively little land clearing was required. The familiar pattern of small single family plots, no large commercial fields, along the branches of a herringbone road network is evident.

Abundance and Production of Berry-producing Plants on the MOFEP Study Sites: The Soft Mast Study Pre-harvest Conditions (1994-1995)

Treesearch

Debby K. Fantz; David A. Hamilton

1997-01-01

We surveyed the permanent Missouri Ozark Forest Ecosystem Project (MOFEP) forest vegetation cluster plots in 1994 and 1995 to determine pre-treatment frequency of occurrence, amount of vegetative cover, and number of berries for plants that produce soft mast. Mean percentage occurrence of selected plants for each site ranged from 0.1 to 33.0 for Vaccinium...

Modeling post-fire woody carbon dynamics with data from remeasured inventory plots

Treesearch

Bianca N.I. Eskelson; Jeremy Fried; Vicente Monleon

2015-01-01

In California, the Forest Inventory and Analysis (FIA) plots within large fires were visited one year after the fire occurred resulting in a time series of measurements before and after fire. During this additional plot visit, the standard inventory measurements were augmented for these burned plots to assess fire effects. One example of the additional measurements is...

Practical Considerations When Using Perturbed Forest Inventory Plot Locations To Develop Spatial Models: A Case Study

Treesearch

John W. Coulston; Gregory A. Reams; Ronald E. McRoberts; William D. Smith

2006-01-01

U.S. Department of Agriculture Forest Service Forest Inventory and Analysis plot information is used in many capacities including timber inventories, forest health assessments, and environmental risk analyses. With few exceptions, actual plot locations cannot be revealed to the general public. The public does, however, have access to perturbed plot coordinates. The...

Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

Treesearch

Andrew Lister; Rachel Riemann; James Westfall; Mike Hoppus

2005-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered...

Runoff and soil erosion plot-scale studies under natural rainfall: A meta-analysis of the Brazilian experience

USDA-ARS?s Scientific Manuscript database

Research to measure soil erosion rates in the United States from natural rainfall runoff plots began in the early 1900’s. In Brazil, the first experimental study at the plot-scale was conducted in the 1940’s; however, the monitoring process and the creation of new experimental field plots have not c...

Detection and discrimination of cotton foreign matter using push-broom based hyperspectral imaging: system design and capability.

PubMed

Jiang, Yu; Li, Changying

2015-01-01

Cotton quality, a major factor determining both cotton profitability and marketability, is affected by not only the overall quantity of but also the type of the foreign matter. Although current commercial instruments can measure the overall amount of the foreign matter, no instrument can differentiate various types of foreign matter. The goal of this study was to develop a hyperspectral imaging system to discriminate major types of foreign matter in cotton lint. A push-broom based hyperspectral imaging system with a custom-built multi-thread software was developed to acquire hyperspectral images of cotton fiber with 15 types of foreign matter commonly found in the U.S. cotton lint. A total of 450 (30 replicates for each foreign matter) foreign matter samples were cut into 1 by 1 cm2 pieces and imaged on the lint surface using reflectance mode in the spectral range from 400-1000 nm. The mean spectra of the foreign matter and lint were extracted from the user-defined region-of-interests in the hyperspectral images. The principal component analysis was performed on the mean spectra to reduce the feature dimension from the original 256 bands to the top 3 principal components. The score plots of the 3 principal components were used to examine clusterization patterns for classifying the foreign matter. These patterns were further validated by statistical tests. The experimental results showed that the mean spectra of all 15 types of cotton foreign matter were different from that of the lint. Nine types of cotton foreign matter formed distinct clusters in the score plots. Additionally, all of them were significantly different from each other at the significance level of 0.05 except brown leaf and bract. The developed hyperspectral imaging system is effective to detect and classify cotton foreign matter on the lint surface and has the potential to be implemented in commercial cotton classing offices.

Using T-Z plots as a graphical method to infer lithological variations from growth strata

NASA Astrophysics Data System (ADS)

Castelltort, Sébastien; Pochat, Stéphane; Van Den Driessche, Jean

2004-08-01

The 'T-Z plot' method consists of plotting the throw of sedimentary horizons across a growth fault versus their depth in the hanging wall. This method has been initially developed for the analysis of growth fault kinematics from seismic data. A brief analytical examination of such plots shows that they can also provide valuable information about the evolution of fault topography. When growth is a continuous process, stages of topography creation (fault scarp) and filling (of the space available in the hanging-wall) are related to non-dynamic (draping, mud-prone pelagic settling) and dynamic (sand-prone, dynamically deposited) sedimentation, respectively. In this case, the T-Z plot analysis becomes a powerful tool to predict major lithological variations on seismic profiles in faulted settings.

Using variance components to estimate power in a hierarchically nested sampling design improving monitoring of larval Devils Hole pupfish

USGS Publications Warehouse

Dzul, Maria C.; Dixon, Philip M.; Quist, Michael C.; Dinsomore, Stephen J.; Bower, Michael R.; Wilson, Kevin P.; Gaines, D. Bailey

2013-01-01

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007–2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey's power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.

Kinetics of copper growth on graphene revealed by time-resolved small-angle x-ray scattering

NASA Astrophysics Data System (ADS)

Hodas, M.; Siffalovic, P.; Jergel, M.; Pelletta, M.; Halahovets, Y.; Vegso, K.; Kotlar, M.; Majkova, E.

2017-01-01

Metal growth on graphene has many applications. Transition metals are known to favor three-dimensional (3D) cluster growth on graphene. Copper is of particular interest for cost-effective surface-supported catalysis applications and as a contact material in electronics. This paper presents an in situ real-time study of Cu growth kinetics on graphene covering all stages preceding formation of a continuous film performed by laboratory-based grazing-incidence small-angle x-ray scattering (GISAXS) technique. In particular, nucleation and 3D cluster growth, coalescence, and percolation stages were identified. The cluster nucleation saturates after reaching a density of 1012c m-2 at ≈1 monolayer thickness. A Kratky plot and a paracrystal model with cumulative structural disorder were necessary to evaluate properly cluster growth and coalescence, respectively. The power law scaling constants 0.27 ±0.05 and 0.81 ±0.02 of the temporal evolution of Cu cluster size suggest the growth of isolated clusters and dynamic cluster coalescence keeping the cluster shape, respectively. Coalescence and percolation thresholds occur at Cu thicknesses of 2 ±0.4 and 8.8 ±0.7 nm , respectively. This paper demonstrates the potential of laboratory-based in situ GISAXS as a vital diagnostic tool for tailoring a large variety of Cu nanostructures on graphene based on an in situ Cu growth monitoring which is applicable in a broad range of deposition times.

Detecting small-study effects and funnel plot asymmetry in meta-analysis of survival data: A comparison of new and existing tests.

PubMed

Debray, Thomas P A; Moons, Karel G M; Riley, Richard D

2018-03-01

Small-study effects are a common threat in systematic reviews and may indicate publication bias. Their existence is often verified by visual inspection of the funnel plot. Formal tests to assess the presence of funnel plot asymmetry typically estimate the association between the reported effect size and their standard error, the total sample size, or the inverse of the total sample size. In this paper, we demonstrate that the application of these tests may be less appropriate in meta-analysis of survival data, where censoring influences statistical significance of the hazard ratio. We subsequently propose 2 new tests that are based on the total number of observed events and adopt a multiplicative variance component. We compare the performance of the various funnel plot asymmetry tests in an extensive simulation study where we varied the true hazard ratio (0.5 to 1), the number of published trials (N=10 to 100), the degree of censoring within trials (0% to 90%), and the mechanism leading to participant dropout (noninformative versus informative). Results demonstrate that previous well-known tests for detecting funnel plot asymmetry suffer from low power or excessive type-I error rates in meta-analysis of survival data, particularly when trials are affected by participant dropout. Because our novel test (adopting estimates of the asymptotic precision as study weights) yields reasonable power and maintains appropriate type-I error rates, we recommend its use to evaluate funnel plot asymmetry in meta-analysis of survival data. The use of funnel plot asymmetry tests should, however, be avoided when there are few trials available for any meta-analysis. © 2017 The Authors. Research Synthesis Methods Published by John Wiley & Sons, Ltd.

New red giant star in the Kepler open cluster NGC 6819

NASA Astrophysics Data System (ADS)

Komucyeya, E.; Abedigamba, O. P.; Jurua, E.; Anguma, S. K.

2018-05-01

A recent study indicated that 39 red giant stars showing solar-like oscillations were discovered in the field of Kepleropen cluster NGC 6819. The study was based on photometric distance estimates of 27 stars out of the 39. Using photometric method alone may not be adequate to confirm the membership of these stars. The stars were not previously known in literature to belong to the open cluster NGC 6819. In this study, Kepler data was used to study the membership of the 27 stars. A plot of apparent magnitude as a function of the large frequency separation, supplemented with the proper motion and radial velocity values from literature revealed KIC 5112840 to lie on the same plane with the well known members of the cluster. Echelle diagram was constructed, and the median gravity-mode period spacings (ΔP) calculated for KIC 5112840. A value of ΔP = 66.3 s was obtained, thus placing the red giant star KIC 5112840 on the Red Giant Branch stage of evolution. Our evolutionary status result using the approach in this paper is in agreement with what is in the available literature.

Pseudomonas canadensis sp. nov., a biological control agent isolated from a field plot under long-term mineral fertilization.

PubMed

Tambong, James T; Xu, Renlin; Bromfield, Eden S P

2017-04-01

The bacterial strain 2-92T, isolated from a field plot under long-term (>40 years) mineral fertilization, exhibited in vitro antagonistic properties against fungal pathogens. A polyphasic approach was undertaken to verify its taxonomic status. Strain 2-92T was Gram-reaction-negative, aerobic, non-spore-forming, motile by one or more flagella, and oxidase-, catalase- and urease-positive. The optimal growth temperature of strain 2-92T was 30 °C. 16S rRNA gene sequence analysis demonstrated that the strain is related to species of the genus Pseudomonas. Phylogenetic analysis of six housekeeping genes (dnaA, gyrB, recA, recF, rpoB and rpoD) revealed that strain 2-92T clustered as a distinct and well separated lineage with Pseudomonassimiae as the most closely related species. Polar lipid and fatty acid compositions corroborated the taxonomic position of strain 2-92T in the genus Pseudomonas. Phenotypic characteristics from carbon utilization tests could be used to differentiate strain 2-92T from closely related species of the genus Pseudomonas. DNA-DNA hybridization values (wet laboratory and genome-based) and average nucleotide identity data confirmed that this strain represents a novel species. On the basis of phenotypic and genotypic characteristics, it is concluded that this strain represents a separate novel species for which the name Pseudomonas canadensis sp. nov. is proposed, with type strain 2-92T (=LMG 28499T=DOAB 798T). The DNA G+C content is 60.30 mol%.

Rhizobium etli and Rhizobium gallicum Nodulate Common Bean (Phaseolus vulgaris) in a Traditionally Managed Milpa Plot in Mexico: Population Genetics and Biogeographic Implications

PubMed Central

Silva, Claudia; Vinuesa, Pablo; Eguiarte, Luis E.; Martínez-Romero, Esperanza; Souza, Valeria

2003-01-01

The stability of the genetic structure of rhizobial populations nodulating Phaseolus vulgaris cultivated in a traditionally managed milpa plot in Mexico was studied over three consecutive years. The set of molecular markers analyzed (including partial rrs, glnII, nifH, and nodB sequences), along with host range experiments, placed the isolates examined in Rhizobium etli bv. phaseoli and Rhizobium gallicum bv. gallicum. Cluster analysis of multilocus enzyme electrophoresis and plasmid profile data separated the two species and identified numerically dominant clones within each of them. Population genetic analyses showed that there was high genetic differentiation between the two species and that there was low intrapopulation differentiation of the species over the 3 years. The results of linkage disequilibrium analyses are consistent with an epidemic genetic structure for both species, with frequent genetic exchange taking place within conspecific populations but not between the R. etli and R. gallicum populations. A subsample of isolates was selected and used for 16S ribosomal DNA PCR-restriction fragment length polymorphism analysis, nifH copy number determination, and host range experiments. Plasmid profiles and nifH hybridization patterns also revealed the occurrence of lateral plasmid transfer among distinct multilocus genotypes within species but not between species. Both species were recovered from nodules of the same plants, indicating that mechanisms other than host, spatial, or temporal isolation may account for the genetic barrier between the species. The biogeographic implications of finding an R. gallicum bv. gallicum population nodulating common bean in America are discussed. PMID:12571008

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steed, Chad Allen

EDENx is a multivariate data visualization tool that allows interactive user driven analysis of large-scale data sets with high dimensionality. EDENx builds on our earlier system, called EDEN to enable analysis of more dimensions and larger scale data sets. EDENx provides an initial overview of summary statistics for each variable in the data set under investigation. EDENx allows the user to interact with graphical summary plots of the data to investigate subsets and their statistical associations. These plots include histograms, binned scatterplots, binned parallel coordinate plots, timeline plots, and graphical correlation indicators. From the EDENx interface, a user can selectmore » a subsample of interest and launch a more detailed data visualization via the EDEN system. EDENx is best suited for high-level, aggregate analysis tasks while EDEN is more appropriate for detail data investigations.« less

Interactive computer programs for the graphic analysis of nucleotide sequence data.

PubMed Central

Luckow, V A; Littlewood, R K; Rownd, R H

1984-01-01

A group of interactive computer programs have been developed which aid in the collection and graphical analysis of nucleotide and protein sequence data. The programs perform the following basic functions: a) enter, edit, list, and rearrange sequence data; b) permit automatic entry of nucleotide sequence data directly from an autoradiograph into the computer; c) search for restriction sites or other specified patterns and plot a linear or circular restriction map, or print their locations; d) plot base composition; e) analyze homology between sequences by plotting a two-dimensional graphic matrix; and f) aid in plotting predicted secondary structures of RNA molecules. PMID:6546437

Determination of variability in leaf biomass densities of conifers and mixed conifers under different environmental conditions in the San Joaquin Valley air basin. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Temple, P.J.; Mutters, R.J.; Adams, C.

1995-06-01

Biomass sampling plots were established at 29 locations within the dominant vegetation zones of the study area. Estimates of foliar biomass were made for each plot by three independent methods: regression analysis on the basis of tree diameter, calculation of the amount of light intercepted by the leaf canopy, and extrapolation from branch leaf area. Multivariate regression analysis was used to relate these foliar biomass estimates for oak plots and conifer plots to several independent predictor variables, including elevation, slope, aspect, temperature, precipitation, and soil chemical characteristics.

On spectral techniques in analysis of Boolean networks

NASA Astrophysics Data System (ADS)

Kesseli, Juha; Rämö, Pauli; Yli-Harja, Olli

2005-06-01

In this work we present results that can be used for analysis of Boolean networks. The results utilize Fourier spectra of the functions in the network. An accurate formula is given for Derrida plots of networks of finite size N based on a result on Boolean functions presented in another context. Derrida plots are widely used to examine the stability issues of Boolean networks. For the limit N→∞, we give a computationally simple form that can be used as a good approximation for rather small networks as well. A formula for Derrida plots of random Boolean networks (RBNs) presented earlier in the literature is given an alternative derivation. It is shown that the information contained in the Derrida plot is equal to the average Fourier spectrum of the functions in the network. In the case of random networks the mean Derrida plot can be obtained from the mean spectrum of the functions. The method is applied to real data by using the Boolean functions found in genetic regulatory networks of eukaryotic cells in an earlier study. Conventionally, Derrida plots and stability analysis have been computed with statistical sampling resulting in poorer accuracy.

Analysis and Visualization of ChIP-Seq and RNA-Seq Sequence Alignments Using ngs.plot.

PubMed

Loh, Yong-Hwee Eddie; Shen, Li

2016-01-01

The continual maturation and increasing applications of next-generation sequencing technology in scientific research have yielded ever-increasing amounts of data that need to be effectively and efficiently analyzed and innovatively mined for new biological insights. We have developed ngs.plot-a quick and easy-to-use bioinformatics tool that performs visualizations of the spatial relationships between sequencing alignment enrichment and specific genomic features or regions. More importantly, ngs.plot is customizable beyond the use of standard genomic feature databases to allow the analysis and visualization of user-specified regions of interest generated by the user's own hypotheses. In this protocol, we demonstrate and explain the use of ngs.plot using command line executions, as well as a web-based workflow on the Galaxy framework. We replicate the underlying commands used in the analysis of a true biological dataset that we had reported and published earlier and demonstrate how ngs.plot can easily generate publication-ready figures. With ngs.plot, users would be able to efficiently and innovatively mine their own datasets without having to be involved in the technical aspects of sequence coverage calculations and genomic databases.

Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

Treesearch

J. A. Blackard; M. V. Finco; E. H. Helmer; G. R. Holden; M. L. Hoppus; D.M. Jacobs; A. J. Lister; G. G. Moisen; M. D. Nelson; R. Riemann; B. Ruefenacht; D. Salajanu; D. L. Weyermann; K. C. Winterberger; T. J. Brandeis; R. L. Czaplewski; R. E. McRoberts; P. L. Patterson; R. P. Tymcio

2008-01-01

A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes...

Chemoradiotherapy enhanced the efficacy of radiotherapy in nasopharyngeal carcinoma patients: a network meta-analysis

PubMed Central

He, Jian; Wu, Ping; Tang, Yaoyun; Liu, Sulai; Xie, Chubo; Luo, Shi; Zeng, Junfeng; Xu, Jing; Zhao, Suping

2017-01-01

Object A Bayesian network meta-analysis (NMA) was conducted to estimate the overall survival (OS) and complete response (CR) performance in nasopharyngeal carcinoma (NPC) patients who have been given the treatment of radiotherapy, concurrent chemoradiotherapy (C), adjuvant chemotherapy (A), neoadjuvant chemotherapy (N), concurrent chemoradiotherapy with adjuvant chemotherapy (C+A), concurrent chemoradiotherapy with neoadjuvant chemotherapy (C+N) and neoadjuvant chemotherapy with adjuvant chemotherapy (N+A). Methods Literature search was conducted in electronic databases. Hazard ratios (HRs) accompanied their 95% confidence intervals (95%CIs) or 95% credible intervals (95%CrIs) were applied to measure the relative survival benefit between two comparators. Meanwhile odd ratios (ORs) with their 95% CIs or CrIs were given to present CR data from individual studies. RESULTS Totally 52 qualified studies with 10,081 patients were included in this NMA. In conventional meta-analysis (MA), patients with N+C exhibited an average increase of 9% in the 3-year OS in relation to those with C+A. As for the NMA results, five therapies were associated with a significantly reduced HR when compared with the control group when concerning 5-year OS. C, C+A and N+A also presented a decreased HR compared with A. There was continuity among 1-year, 3-year and 5-year OS status. Cluster analysis suggested that the three chemoradiotherapy appeared to be divided into the most compete group which is located in the upper right corner of the cluster plot. Conclusion In view of survival rate and complete response, the NMA results revealed that C, C+A and C+N showed excellent efficacy. As a result, these 3 therapies were supposed to be considered as the first-line treatment according to this NMA. PMID:28418901

Fingerprint analysis of Radix Aconiti using ultra-performance liquid chromatography-electrospray ionization/ tandem mass spectrometry (UPLC-ESI/MS n) combined with stoichiometry.

PubMed

Zhu, Hongbin; Wang, Chunyan; Qi, Yao; Song, Fengrui; Liu, Zhiqiang; Liu, Shuying

2013-01-15

A fingerprinting approach was developed by means of UPLC-ESI/MS(n) (ultra-performance liquid chromatography-electrospray ionization/mass spectrometry) for the quality control of processed Radix Aconiti, a widely used toxic traditional herbal medicine. The present fingerprinting approach was based on the two processing methods recorded in Chinese Pharmacopoeia for the purpose of reducing the toxicity and ensuring the clinical therapeutic efficacy. Similarity evaluation, hierarchical cluster analysis and principal component analysis were performed to evaluate the similarity and variation of the samples. The results showed that the well processed, unqualified processed and the raw Radix Aconiti could be clustered reasonably corresponding to the contents of their constituents. The loading plot shows that the main chemical markers having the most influence on the discrimination amongst the qualified and unqualified samples were mainly some monoester diterpenoid aconitines and diester diterpenoid aconitines. Finally, the UPLC-UV and UPLC-ESI/MS(n) characteristic fingerprints were established according to the well processed and purchased qualified samples. At the same time, a complementary quantification method of six Aconitine-type alkaloids was developed using UPLC-UV and UPLC-ESI/MS. The average recovery of the monoester diterpenoid aconitines was 95.4-99.1% and the average recovery of the diester diterpenoid aconitines was 103-112%. The proposed combined quantification method by UPLC-UV and UPLC-ESI/MS allows the samples analyzed in a wide concentration range. Therefore, the established fingerprinting approach in combination with chemometric analysis provides a flexible and reliable method for quality assessment of toxic herbal medicine. Copyright © 2012 Elsevier B.V. All rights reserved.

ANALYSIS/PLOT: a graphics package for use with the SORT/ANALYSIS data bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sady, C.A.

1983-08-01

This report describes a graphics package that is used with the SORT/ANALYSIS data bases. The data listed by the SORT/ANALYSIS program can be presented in pie, bar, line, or Gantt chart form. Instructions for the use of the plotting program and descriptions of the subroutines are given in the report.

Genetic affinity between diverse ethnoreligious communities of Tamil Nadu, India: a microsatellite study.

PubMed

Eaaswarkhanth, M; Vasulu, T S; Haque, Ikramul

2008-12-01

Historically, a number of local Hindu caste groups have converted to Islam and formed religious endogamous groups. Therefore the local caste groups and religious communities in a region are expected to show genetic relatedness. In this study we investigate the genetic relationship between Tamil-speaking (Dravidian language) Muslims (Sunni), six endogamous Hindu castes, and a tribal ethnic group (Irulars) using 13 CODIS (Combined DNA Index System) autosomal microsatellite markers. Muslims show the highest average heterozygosity (0.405) compared to the other groups. The neighbor-joining tree and the multidimensional-scaling plot show clustering of Tamil-speaking Muslims with three caste groups (Gounder, Paraiyar, and Vanniyar), whereas the Irular tribe is separated out of the cluster.

The isometric log-ratio (ilr)-ion plot: A proposed alternative to the Piper diagram

USGS Publications Warehouse

Shelton, Jenna L.; Engle, Mark A.; Buccianti, Antonella; Blondes, Madalyn S.

2018-01-01

The Piper diagram has been a staple for the analysis of water chemistry data since its introduction in 1944. It was conceived to be a method for water classification, determination of potential water mixing between end-members, and to aid in the identification of chemical reactions controlling a sample set. This study uses the information gleaned over the years since the release of the Piper diagram and proposes an alternative to it, capturing the strengths of the original diagram while adding new ideas to increase its robustness. The new method uses compositional data analysis to create 4 isometric log-ratio coordinates for the 6 major chemical species analyzed in the Piper diagram and transforms the data to a 4-field bi-plot, the ilr-ion plot. This ilr-ion plot conveys all of the information in the Piper diagram (water mixing, water types, and chemical reactions) while also visualizing additional data, the ability to examine Ca2+/Mg2+ versus Cl-/SO42−. The Piper and the ilr-ion plot were also compared using multiple synthetic and real datasets in order to illustrate the caveats and the advantages of using either diagram to analyze water chemistry data. Although there are challenges with using the ilr-ion plot (e.g., missing or zero values zeros in the dataset must be imputed by positive real numbers), it appears that the use of compositional data analysis coupled with the ilr-ion plot provides a more in-depth and complete analysis of water quality data compared to the original Piper diagram.

User's manual for the coupled rotor/airframe vibration analysis graphic package

NASA Technical Reports Server (NTRS)

Studwell, R. E.

1982-01-01

User instructions for a graphics package for coupled rotor/airframe vibration analysis are presented. Responses to plot package messages which the user must make to activate plot package operations and options are described. Installation instructions required to set up the program on the CDC system are included. The plot package overlay structure and subroutines which have to be modified for the CDC system are also described. Operating instructions for CDC applications are included.

Simpson's paradox visualized: The example of the Rosiglitazone meta-analysis

PubMed Central

Rücker, Gerta; Schumacher, Martin

2008-01-01

Background Simpson's paradox is sometimes referred to in the areas of epidemiology and clinical research. It can also be found in meta-analysis of randomized clinical trials. However, though readers are able to recalculate examples from hypothetical as well as real data, they may have problems to easily figure where it emerges from. Method First, two kinds of plots are proposed to illustrate the phenomenon graphically, a scatter plot and a line graph. Subsequently, these can be overlaid, resulting in a overlay plot. The plots are applied to the recent large meta-analysis of adverse effects of rosiglitazone on myocardial infarction and to an example from the literature. A large set of meta-analyses is screened for further examples. Results As noted earlier by others, occurrence of Simpson's paradox in the meta-analytic setting, if present, is associated with imbalance of treatment arm size. This is well illustrated by the proposed plots. The rosiglitazone meta-analysis shows an effect reversion if all trials are pooled. In a sample of 157 meta-analyses, nine showed an effect reversion after pooling, though non-significant in all cases. Conclusion The plots give insight on how the imbalance of trial arm size works as a confounder, thus producing Simpson's paradox. Readers can see why meta-analytic methods must be used and what is wrong with simple pooling. PMID:18513392

Parametric Analysis of a Hover Test Vehicle using Advanced Test Generation and Data Analysis

NASA Technical Reports Server (NTRS)

Gundy-Burlet, Karen; Schumann, Johann; Menzies, Tim; Barrett, Tony

2009-01-01

Large complex aerospace systems are generally validated in regions local to anticipated operating points rather than through characterization of the entire feasible operational envelope of the system. This is due to the large parameter space, and complex, highly coupled nonlinear nature of the different systems that contribute to the performance of the aerospace system. We have addressed the factors deterring such an analysis by applying a combination of technologies to the area of flight envelop assessment. We utilize n-factor (2,3) combinatorial parameter variations to limit the number of cases, but still explore important interactions in the parameter space in a systematic fashion. The data generated is automatically analyzed through a combination of unsupervised learning using a Bayesian multivariate clustering technique (AutoBayes) and supervised learning of critical parameter ranges using the machine-learning tool TAR3, a treatment learner. Covariance analysis with scatter plots and likelihood contours are used to visualize correlations between simulation parameters and simulation results, a task that requires tool support, especially for large and complex models. We present results of simulation experiments for a cold-gas-powered hover test vehicle.

Cross-Scale Analysis of the Region Effect on Vascular Plant Species Diversity in Southern and Northern European Mountain Ranges

PubMed Central

Lenoir, Jonathan; Gégout, Jean-Claude; Guisan, Antoine; Vittoz, Pascal; Wohlgemuth, Thomas; Zimmermann, Niklaus E.; Dullinger, Stefan; Pauli, Harald; Willner, Wolfgang; Grytnes, John-Arvid; Virtanen, Risto; Svenning, Jens-Christian

2010-01-01

Background The divergent glacial histories of southern and northern Europe affect present-day species diversity at coarse-grained scales in these two regions, but do these effects also penetrate to the more fine-grained scales of local communities? Methodology/Principal Findings We carried out a cross-scale analysis to address this question for vascular plants in two mountain regions, the Alps in southern Europe and the Scandes in northern Europe, using environmentally paired vegetation plots in the two regions (n = 403 in each region) to quantify four diversity components: (i) total number of species occurring in a region (total γ-diversity), (ii) number of species that could occur in a target plot after environmental filtering (habitat-specific γ-diversity), (iii) pair-wise species compositional turnover between plots (plot-to-plot β-diversity) and (iv) number of species present per plot (plot α-diversity). We found strong region effects on total γ-diversity, habitat-specific γ-diversity and plot-to-plot β-diversity, with a greater diversity in the Alps even towards distances smaller than 50 m between plots. In contrast, there was a slightly greater plot α-diversity in the Scandes, but with a tendency towards contrasting region effects on high and low soil-acidity plots. Conclusions/Significance We conclude that there are strong regional differences between coarse-grained (landscape- to regional-scale) diversity components of the flora in the Alps and the Scandes mountain ranges, but that these differences do not necessarily penetrate to the finest-grained (plot-scale) diversity component, at least not on acidic soils. Our findings are consistent with the contrasting regional Quaternary histories, but we also consider alternative explanatory models. Notably, ecological sorting and habitat connectivity may play a role in the unexpected limited or reversed region effect on plot α-diversity, and may also affect the larger-scale diversity components. For instance, plot connectivity and/or selection for high dispersal ability may increase plot α-diversity and compensate for low total γ-diversity. PMID:21203521

Monazite chemical age and composition correlations, an insight in the Palaeozoic evolution of the Leaota Massif, South Carpathians

NASA Astrophysics Data System (ADS)

Săbău, Gavril; Negulescu, Elena

2015-04-01

Notwithstanding remarkable advantages of monazite microprobe U-Th-PbT geochronology of metamorphic formations, such as the direct investigation of a metamorphic mineral in a truly in situ setting, unequalled spatial resolution, and cost-effective analyses, it essentially remains affected by indeterminations as regards the accuracy and the representativity of the results. Besides the experimental hurdles related to trace element analyses with the microprobe (sensitivity, background and overlap effects) the method faces two main biases, firstly its inherently blind status emerging from the aprioric assumption of isotopic equilibrium, and secondly the marked susceptibility of monazite to fluid-stimulated chemical recrystallization and compositional resetting (e. g. Kelly et al. 2012). Age spectra obtained from individual sampled habitually display a significant scatter of calculated age data, in such a way that the separation of coherent and geologically relevant populations may often represent a substantial challenge. The interpretation of the results greatly benefits from the qualitative analysis of the textural and paragenetic setting or a trial-and error quantitative statistical assessment of distinct age clusters (Montel et al., 1996), though still maintaining a variable degree of subjectivity, as in any interpretative process not fully sustained by quantitative analysis. Additional dependable support can be gained from further qualitative parameters characterizing, besides the distribution of individual age data, also the global chemical composition of the analysed monazite grains, as well as the relationship to the corresponding metamorphic assemblages (Săbău & Negulescu, 2013). The quantitative assessment of the age patterns of individual samples can be achieved by plotting the normalized age gradient from the sorted age pattern, allowing distinction of quasi-gaussian distribution domains likely to correspond to coherent age clusters of geologic significance. On the other hand, the chemical variability of the monazite grains enables separation of discrete populations, which cluster in ternary chemical plots (LREE - Y+Nd+MREE - U+Th+Ca, LREE - Nd+MREE - Y) and display similar chondrite-normalized lanthanide patterns, quantitatively evaluated by ratios such as (La/Nd)CN, (Nd/Gd)CN, (Gd/Y)CN, (U/Th)CN, (Y/Y*)CN, and (Eu/Eu*)CN. The correspondence between age and chemical clusters endorses their geological relevance and make a case for geunuine tectonothermal events. Distinct compositional domains corresponding to well-defined age clusters have been identified in gneissic rocks of the Leaota Massif, South Carpathians, highlighting the lower Paleozoic evolution of a crustal fragment detached during the Cambrian from northern Gondwana. Relict ages of Panafrican affinity of around 530 Ma are heavily overprinted by Lower Ordovician crustal thickening followed by tectonic relaxation coeval with granitization (around 470 Ma), followed in turn by high-pressure metamorphism at the Ordovician-Silurian boundary (Negulescu et al., 2015) and final tectonic stacking associated to Variscan docking to Laurussia + Avalonia, reflected in a high-pressure overprint at 350-325 Ma. References Kelly N. M., Harley S. L., Möller A. et al. (2012) Chemical Geology 322-323, 192-208 Montel J.-M., Foret S., Veschambre M., Nicollet C., Provost A. (1996) Chemical Geology 131, 37-53 Săbău G., Negulescu E. (2013) GSTF International Journal of Geological Sciences 1/ 1, 20-29 Negulescu E., Săbău G., Massonne H.-J. (2015) EGU2015-6663

Forest and community structure of tropical sub-montane rain forests on the island of Dominica, Lesser Antilles

Treesearch

S.J. DeWalt; K. Ickes; A. James

2016-01-01

To examine short- and long-term changes in hurricane-prone sub-montane rain forests on Dominica in the Lesser Antilles of the eastern Caribbean, we established 17 permanent, 0.25-ha vegetation plots clustered in 3 regions of the island—northeast, northwest, and southwest. We counted all trees ≥10 cm diameter almost 30 years after Hurricane David caused substantial tree...

Maintaining the confidentiality of plot locations by exploiting the low sensitivity of forest structure models to different spectral extraction kernels

Treesearch

Sean P. Healey; Elizabeth Lapoint; Gretchen G. Moisen; Scott L. Powell

2011-01-01

The United States Forest Service Forest Inventory and Analysis (FIA) unit maintains a large national network of inventory plots.While the consistency and extent of this network make FIA data attractive for ecological modelling, the FIA is charged by statute not to publicly reveal inventory plot locations. However, use of FIA plot data by the remote sensing community...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krause, Josua; Dasgupta, Aritra; Fekete, Jean-Daniel

Dealing with the curse of dimensionality is a key challenge in high-dimensional data visualization. We present SeekAView to address three main gaps in the existing research literature. First, automated methods like dimensionality reduction or clustering suffer from a lack of transparency in letting analysts interact with their outputs in real-time to suit their exploration strategies. The results often suffer from a lack of interpretability, especially for domain experts not trained in statistics and machine learning. Second, exploratory visualization techniques like scatter plots or parallel coordinates suffer from a lack of visual scalability: it is difficult to present a coherent overviewmore » of interesting combinations of dimensions. Third, the existing techniques do not provide a flexible workflow that allows for multiple perspectives into the analysis process by automatically detecting and suggesting potentially interesting subspaces. In SeekAView we address these issues using suggestion based visual exploration of interesting patterns for building and refining multidimensional subspaces. Compared to the state-of-the-art in subspace search and visualization methods, we achieve higher transparency in showing not only the results of the algorithms, but also interesting dimensions calibrated against different metrics. We integrate a visually scalable design space with an iterative workflow guiding the analysts by choosing the starting points and letting them slice and dice through the data to find interesting subspaces and detect correlations, clusters, and outliers. We present two usage scenarios for demonstrating how SeekAView can be applied in real-world data analysis scenarios.« less

First and second order stereology of hyaline cartilage: Application on mice femoral cartilage.

PubMed

Noorafshan, Ali; Niazi, Behnam; Mohamadpour, Masoomeh; Hoseini, Leila; Hoseini, Najmeh; Owji, Ali Akbar; Rafati, Ali; Sadeghi, Yasaman; Karbalay-Doust, Saied

2016-11-01

Stereological techniques could be considered in research on cartilage to obtain quantitative data. The present study aimed to explain application of the first- and second-order stereological methods on articular cartilage of mice and the methods applied on the mice exposed to cadmium (Cd). The distal femoral articular cartilage of BALB/c mice (control and Cd-treated) was removed. Then, volume and surface area of the cartilage and number of chondrocytes were estimated using Cavalieri and optical dissector techniques on isotropic uniform random sections. Pair-correlation function [g(r)] and cross-correlation function were calculated to express the spatial arrangement of chondrocytes-chondrocytes and chondrocytes-matrix (chondrocyte clustering/dispersing), respectively. The mean±standard deviation of the cartilage volume, surface area, and thickness were 1.4±0.1mm 3 , 26.2±5.4mm 2 , and 52.8±6.7μm, respectively. Besides, the mean number of chondrocytes was 680±200 (×10 3 ). The cartilage volume, cartilage surface area, and number of chondrocytes were respectively reduced by 25%, 27%, and 27% in the Cd-treated mice in comparison to the control animals (p<0.03). Estimates of g(r) for the cells and matrix against the dipole distances, r, have been plotted. This plot showed that the chondrocytes and the matrix were neither dispersed nor clustered in the two study groups. Application of design-based stereological methods and also evaluation of spatial arrangement of the cartilage components carried potential advantages for investigating the cartilage in different joint conditions. Chondrocyte clustering/dispersing and cellularity can be evaluated in cartilage assessment in normal or abnormal situations. Copyright © 2016 Elsevier GmbH. All rights reserved.

Satellite inventory of Minnesota forest resources

NASA Technical Reports Server (NTRS)

Bauer, Marvin E.; Burk, Thomas E.; Ek, Alan R.; Coppin, Pol R.; Lime, Stephen D.; Walsh, Terese A.; Walters, David K.; Befort, William; Heinzen, David F.

1993-01-01

The methods and results of using Landsat Thematic Mapper (TM) data to classify and estimate the acreage of forest covertypes in northeastern Minnesota are described. Portions of six TM scenes covering five counties with a total area of 14,679 square miles were classified into six forest and five nonforest classes. The approach involved the integration of cluster sampling, image processing, and estimation. Using cluster sampling, 343 plots, each 88 acres in size, were photo interpreted and field mapped as a source of reference data for classifier training and calibration of the TM data classifications. Classification accuracies of up to 75 percent were achieved; most misclassification was between similar or related classes. An inverse method of calibration, based on the error rates obtained from the classifications of the cluster plots, was used to adjust the classification class proportions for classification errors. The resulting area estimates for total forest land in the five-county area were within 3 percent of the estimate made independently by the USDA Forest Service. Area estimates for conifer and hardwood forest types were within 0.8 and 6.0 percent respectively, of the Forest Service estimates. A trial of a second method of estimating the same classes as the Forest Service resulted in standard errors of 0.002 to 0.015. A study of the use of multidate TM data for change detection showed that forest canopy depletion, canopy increment, and no change could be identified with greater than 90 percent accuracy. The project results have been the basis for the Minnesota Department of Natural Resources and the Forest Service to define and begin to implement an annual system of forest inventory which utilizes Landsat TM data to detect changes in forest cover.

PuffinPlot: A versatile, user-friendly program for paleomagnetic analysis

NASA Astrophysics Data System (ADS)

Lurcock, P. C.; Wilson, G. S.

2012-06-01

PuffinPlot is a user-friendly desktop application for analysis of paleomagnetic data, offering a unique combination of features. It runs on several operating systems, including Windows, Mac OS X, and Linux; supports both discrete and long core data; and facilitates analysis of very weakly magnetic samples. As well as interactive graphical operation, PuffinPlot offers batch analysis for large volumes of data, and a Python scripting interface for programmatic control of its features. Available data displays include demagnetization/intensity, Zijderveld, equal-area (for sample, site, and suite level demagnetization data, and for magnetic susceptibility anisotropy data), a demagnetization data table, and a natural remanent magnetization intensity histogram. Analysis types include principal component analysis, Fisherian statistics, and great-circle path intersections. The results of calculations can be exported as CSV (comma-separated value) files; graphs can be printed, and can also be saved as publication-quality vector files in SVG or PDF format. PuffinPlot is free, and the program, user manual, and fully documented source code may be downloaded from http://code.google.com/p/puffinplot/.

From fuzzy recurrence plots to scalable recurrence networks of time series

NASA Astrophysics Data System (ADS)

Pham, Tuan D.

2017-04-01

Recurrence networks, which are derived from recurrence plots of nonlinear time series, enable the extraction of hidden features of complex dynamical systems. Because fuzzy recurrence plots are represented as grayscale images, this paper presents a variety of texture features that can be extracted from fuzzy recurrence plots. Based on the notion of fuzzy recurrence plots, defuzzified, undirected, and unweighted recurrence networks are introduced. Network measures can be computed for defuzzified recurrence networks that are scalable to meet the demand for the network-based analysis of big data.

High performance geospatial and climate data visualization using GeoJS

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Beezley, J. D.

2015-12-01

GeoJS (https://github.com/OpenGeoscience/geojs) is an open-source library developed to support interactive scientific and geospatial visualization of climate and earth science datasets in a web environment. GeoJS has a convenient application programming interface (API) that enables users to harness the fast performance of WebGL and Canvas 2D APIs with sophisticated Scalable Vector Graphics (SVG) features in a consistent and convenient manner. We started the project in response to the need for an open-source JavaScript library that can combine traditional geographic information systems (GIS) and scientific visualization on the web. Many libraries, some of which are open source, support mapping or other GIS capabilities, but lack the features required to visualize scientific and other geospatial datasets. For instance, such libraries are not be capable of rendering climate plots from NetCDF files, and some libraries are limited in regards to geoinformatics (infovis in a geospatial environment). While libraries such as d3.js are extremely powerful for these kinds of plots, in order to integrate them into other GIS libraries, the construction of geoinformatics visualizations must be completed manually and separately, or the code must somehow be mixed in an unintuitive way.We developed GeoJS with the following motivations:• To create an open-source geovisualization and GIS library that combines scientific visualization with GIS and informatics• To develop an extensible library that can combine data from multiple sources and render them using multiple backends• To build a library that works well with existing scientific visualizations tools such as VTKWe have successfully deployed GeoJS-based applications for multiple domains across various projects. The ClimatePipes project funded by the Department of Energy, for example, used GeoJS to visualize NetCDF datasets from climate data archives. Other projects built visualizations using GeoJS for interactively exploring data and analysis regarding 1) the human trafficking domain, 2) New York City taxi drop-offs and pick-ups, and 3) the Ebola outbreak. GeoJS supports advanced visualization features such as picking and selecting, as well as clustering. It also supports 2D contour plots, vector plots, heat maps, and geospatial graphs.

Determination, speciation and distribution of mercury in soil in the surroundings of a former chlor-alkali plant: assessment of sequential extraction procedure and analytical technique

PubMed Central

2013-01-01

Background The paper presents the evaluation of soil contamination with total, water-available, mobile, semi-mobile and non-mobile Hg fractions in the surroundings of a former chlor-alkali plant in connection with several chemical soil characteristics. Principal Component Analysis and Cluster Analysis were used to evaluate the chemical composition variability of soil and factors influencing the fate of Hg in such areas. The sequential extraction EPA 3200-Method and the determination technique based on capacitively coupled microplasma optical emission spectrometry were checked. Results A case study was conducted in the Turda town, Romania. The results revealed a high contamination with Hg in the area of the former chlor-alkali plant and waste landfills, where soils were categorized as hazardous waste. The weight of the Hg fractions decreased in the order semi-mobile > non-mobile > mobile > water leachable. Principal Component Analysis revealed 7 factors describing chemical composition variability of soil, of which 3 attributed to Hg species. Total Hg, semi-mobile, non-mobile and mobile fractions were observed to have a strong influence, while the water leachable fraction a weak influence. The two-dimensional plot of PCs highlighted 3 groups of sites according to the Hg contamination factor. The statistical approach has shown that the Hg fate in soil is dependent on pH, content of organic matter, Ca, Fe, Mn, Cu and SO42- rather than natural components, such as aluminosilicates. Cluster analysis of soil characteristics revealed 3 clusters, one of which including Hg species. Soil contamination with Cu as sulfate and Zn as nitrate was also observed. Conclusions The approach based on speciation and statistical interpretation of data developed in this study could be useful in the investigation of other chlor-alkali contaminated areas. According to the Bland and Altman test the 3-step sequential extraction scheme is suitable for Hg speciation in soil, while the used determination method of Hg is appropriate. PMID:24252185

Population delineation of polar bears using satellite collar data

USGS Publications Warehouse

Bethke, R.; Taylor, Mitchell K.; Amstrup, Steven C.; Messier, François

1996-01-01

To produce reliable estimates of the size or vital rates of a given population, it is important that the boundaries of the population under study are clearly defined. This is particularly critical for large, migratory animals where levels of sustainable harvest are based on these estimates, and where small errors may have serious long-term consequences for the population. Once populations are delineated, rates of exchange between adjacent populations can be determined and accounted/corrected for when calculating abundance (e.g., based on mark-recapture data). Using satellite radio-collar locations for polar bears in the western Canadian Arctic, we illustrate one approach to delineating wildlife populations that integrates cluster analysis methods for determining group membership with home range plotting procedures to define spatial utilization. This approach is flexible with respect to the specific procedures used and provides an objective and quantitative basis for defining population boundaries.

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots.

PubMed

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-11

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-01

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Automated detection and analysis of particle beams in laser-plasma accelerator simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ushizima, Daniela Mayumi; Geddes, C.G.; Cormier-Michel, E.

Numerical simulations of laser-plasma wakefield (particle) accelerators model the acceleration of electrons trapped in plasma oscillations (wakes) left behind when an intense laser pulse propagates through the plasma. The goal of these simulations is to better understand the process involved in plasma wake generation and how electrons are trapped and accelerated by the wake. Understanding of such accelerators, and their development, offer high accelerating gradients, potentially reducing size and cost of new accelerators. One operating regime of interest is where a trapped subset of electrons loads the wake and forms an isolated group of accelerated particles with low spread inmore » momentum and position, desirable characteristics for many applications. The electrons trapped in the wake may be accelerated to high energies, the plasma gradient in the wake reaching up to a gigaelectronvolt per centimeter. High-energy electron accelerators power intense X-ray radiation to terahertz sources, and are used in many applications including medical radiotherapy and imaging. To extract information from the simulation about the quality of the beam, a typical approach is to examine plots of the entire dataset, visually determining the adequate parameters necessary to select a subset of particles, which is then further analyzed. This procedure requires laborious examination of massive data sets over many time steps using several plots, a routine that is unfeasible for large data collections. Demand for automated analysis is growing along with the volume and size of simulations. Current 2D LWFA simulation datasets are typically between 1GB and 100GB in size, but simulations in 3D are of the order of TBs. The increase in the number of datasets and dataset sizes leads to a need for automatic routines to recognize particle patterns as particle bunches (beam of electrons) for subsequent analysis. Because of the growth in dataset size, the application of machine learning techniques for scientific data mining is increasingly considered. In plasma simulations, Bagherjeiran et al. presented a comprehensive report on applying graph-based techniques for orbit classification. They used the KAM classifier to label points and components in single and multiple orbits. Love et al. conducted an image space analysis of coherent structures in plasma simulations. They used a number of segmentation and region-growing techniques to isolate regions of interest in orbit plots. Both approaches analyzed particle accelerator data, targeting the system dynamics in terms of particle orbits. However, they did not address particle dynamics as a function of time or inspected the behavior of bunches of particles. Ruebel et al. addressed the visual analysis of massive laser wakefield acceleration (LWFA) simulation data using interactive procedures to query the data. Sophisticated visualization tools were provided to inspect the data manually. Ruebel et al. have integrated these tools to the visualization and analysis system VisIt, in addition to utilizing efficient data management based on HDF5, H5Part, and the index/query tool FastBit. In Ruebel et al. proposed automatic beam path analysis using a suite of methods to classify particles in simulation data and to analyze their temporal evolution. To enable researchers to accurately define particle beams, the method computes a set of measures based on the path of particles relative to the distance of the particles to a beam. To achieve good performance, this framework uses an analysis pipeline designed to quickly reduce the amount of data that needs to be considered in the actual path distance computation. As part of this process, region-growing methods are utilized to detect particle bunches at single time steps. Efficient data reduction is essential to enable automated analysis of large data sets as described in the next section, where data reduction methods are steered to the particular requirements of our clustering analysis. Previously, we have described the application of a set of algorithms to automate the data analysis and classification of particle beams in the LWFA simulation data, identifying locations with high density of high energy particles. These algorithms detected high density locations (nodes) in each time step, i.e. maximum points on the particle distribution for only one spatial variable. Each node was correlated to a node in previous or later time steps by linking these nodes according to a pruned minimum spanning tree (PMST). We call the PMST representation 'a lifetime diagram', which is a graphical tool to show temporal information of high dense groups of particles in the longitudinal direction for the time series. Electron bunch compactness was described by another step of the processing, designed to partition each time step, using fuzzy clustering, into a fixed number of clusters.« less

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

PubMed

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Multi-Scale Clustering of Lyme Disease Risk at the Expanding Leading Edge of the Range of Ixodes scapularis in Canada.

PubMed

Ripoche, Marion; Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H; Thivierge, Karine; Leighton, Patrick A

2018-03-27

Since its detection in Canada in the early 1990s, Ixodes scapularis , the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick's broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens.

Multi-Scale Clustering of Lyme Disease Risk at the Expanding Leading Edge of the Range of Ixodes scapularis in Canada

PubMed Central

Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H.; Thivierge, Karine; Leighton, Patrick A.

2018-01-01

Since its detection in Canada in the early 1990s, Ixodes scapularis, the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick’s broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens. PMID:29584627

Identification of Two New HIV-1 Circulating Recombinant Forms (CRF87_cpx and CRF88_BC) from Reported Unique Recombinant Forms in Asia.

PubMed

Hu, Yihong; Wan, Zhenzhou; Zhou, Yan-Heng; Smith, Davey; Zheng, Yong-Tang; Zhang, Chiyu

2017-04-01

The on-going generation of HIV-1 intersubtype recombination has led to new circulating recombinant forms (CRFs) and unique recombinant forms (URFs) in Asia. In this study, we evaluated whether previously reported URFs were actually CRFs. All available complete or near full-length HIV-1 URF sequences from Asia were retrieved from the HIV Los Alamos National Laboratory Sequence database, and phylogenetic, transmission cluster, and bootscan analyses were performed using MEGA 6.0, Cluster Picker 1.2.1, and SimPlot3.5.1. According to the criterion of new CRFs, two new HIV-1 CRFs (CRF87_cpx and CRF88_BC) were identified from these available URFs. CRF87_cpx comprised HIV-1 subtypes B, C, and CRF01_AE, and CRF88_BC comprised subtypes B and C. HIV Blast and bootscan analysis revealed that besides the three representative strains, there were two additional CRF87_cpx strains. Furthermore, we defined seven dominant URFs (dURF01-dURF07), each of which contained two strains sharing same recombination map and can be used as sequence references to facilitate the finding of new potential CRFs in future. These results will benefit the molecular epidemiological investigation of HIV-1 in Asia.

Impact of Upfront Cellular Enrichment by Laser Capture Microdissection on Protein and Phosphoprotein Drug Target Signaling Activation Measurements in Human Lung Cancer: Implications for Personalized Medicine

PubMed Central

Elisa, Baldelli; B., Haura Eric; Lucio, Crinò; Douglas, Cress W.; Vienna, Ludovini; B., Schabath Matthew; A., Liotta Lance; F., Petricoin Emanuel; Mariaelena, Pierobon

2015-01-01

Purpose The aim of this study was to evaluate whether upfront cellular enrichment via laser capture microdissection is necessary for accurately quantifying predictive biomarkers in non-small cell lung cancer tumors. Experimental design Fifteen snap frozen surgical biopsies were analyzed. Whole tissue lysate and matched highly enriched tumor epithelium via laser capture microdissection (LCM) were obtained for each patient. The expression and activation/phosphorylation levels of 26 proteins were measured by reverse phase protein microarray. Differences in signaling architecture of dissected and undissected matched pairs were visualized using unsupervised clustering analysis, bar graphs, and scatter plots. Results Overall patient matched LCM and undissected material displayed very distinct and differing signaling architectures with 93% of the matched pairs clustering separately. These differences were seen regardless of the amount of starting tumor epithelial content present in the specimen. Conclusions and clinical relevance These results indicate that LCM driven upfront cellular enrichment is necessary to accurately determine the expression/activation levels of predictive protein signaling markers although results should be evaluated in larger clinical settings. Upfront cellular enrichment of the target cell appears to be an important part of the workflow needed for the accurate quantification of predictive protein signaling biomarkers. Larger independent studies are warranted. PMID:25676683

Analysis of Cost Growth and Cost Composition in the Defense Aerospace Industry

DTIC Science & Technology

1988-09-01

Making. New York: Harcourt Brace Jovanovich, Inc., 1977. 16. Horngren , Charles T. Cost Accounting , A Managerial Emphasis. Englewood Cliffs NJ: Prentice...58 7. Scatter Plot of Cost /DL Hour Ratio, Data Set C ................ .................. 59 8. Scatter Plot of Cost /DL S Ratio, Data Set...C 62 9. Scatter Plot of Cost /DL S Ratio, Then-Year Dollars ................... .................... 63 10. Scatter Plot of OH/TC Ratio, Data Set C

Analysis of arson fire debris by low temperature dynamic headspace adsorption porous layer open tubular columns.

PubMed

Nichols, Jessica E; Harries, Megan E; Lovestead, Tara M; Bruno, Thomas J

2014-03-21

In this paper we present results of the application of PLOT-cryoadsorption (PLOT-cryo) to the analysis of ignitable liquids in fire debris. We tested ignitable liquids, broadly divided into fuels and solvents (although the majority of the results presented here were obtained with gasoline and diesel fuel) on three substrates: Douglas fir, oak plywood and Nylon carpet. We determined that PLOT-cryo allows the analyst to distinguish all of the ignitable liquids tested by use of a very rapid sampling protocol, and performs better (more recovered components, higher efficiency, lower elution solvent volumes) than a conventional purge and trap method. We also tested the effect of latency (the time period between applying the ignitable liquid and ignition), and we tested a variety of sampling times and a variety of PLOT capillary lengths. Reliable results can be obtained with sampling time periods as short as 3min, and on PLOT capillaries as short as 20cm. The variability of separate samples was also assessed, a study made possible by the high throughput nature of the PLOT-cryo method. We also determined that the method performs better than the conventional carbon strip method that is commonly used in fire debris analysis. Published by Elsevier B.V.

Grid-Enabled High Energy Physics Research using a Beowulf Cluster

NASA Astrophysics Data System (ADS)

Mahmood, Akhtar

2005-04-01

At Edinboro University of Pennsylvania, we have built a 8-node 25 Gflops Beowulf Cluster with 2.5 TB of disk storage space to carry out grid-enabled, data-intensive high energy physics research for the ATLAS experiment via Grid3. We will describe how we built and configured our Cluster, which we have named the Sphinx Beowulf Cluster. We will describe the results of our cluster benchmark studies and the run-time plots of several parallel application codes. Once fully functional, the Cluster will be part of Grid3[www.ivdgl.org/grid3]. The current ATLAS simulation grid application, models the entire physical processes from the proton anti-proton collisions and detector's response to the collision debri through the complete reconstruction of the event from analyses of these responses. The end result is a detailed set of data that simulates the real physical collision event inside a particle detector. Grid is the new IT infrastructure for the 21^st century science -- a new computing paradigm that is poised to transform the practice of large-scale data-intensive research in science and engineering. The Grid will allow scientist worldwide to view and analyze huge amounts of data flowing from the large-scale experiments in High Energy Physics. The Grid is expected to bring together geographically and organizationally dispersed computational resources, such as CPUs, storage systems, communication systems, and data sources.

Dalitz plot analysis of the D+→K-π+π+ decay in the FOCUS experiment

NASA Astrophysics Data System (ADS)

Link, J. M.; Yager, P. M.; Anjos, J. C.; Bediaga, I.; Castromonte, C.; Machado, A. A.; Magnin, J.; Massafferri, A.; de Miranda, J. M.; Pepe, I. M.; Polycarpo, E.; Dos Reis, A. C.; Carrillo, S.; Casimiro, E.; Cuautle, E.; Sánchez-Hernández, A.; Uribe, C.; Vázquez, F.; Agostino, L.; Cinquini, L.; Cumalat, J. P.; Frisullo, V.; O'Reilly, B.; Segoni, I.; Stenson, K.; Butler, J. N.; Cheung, H. W. K.; Chiodini, G.; Gaines, I.; Garbincius, P. H.; Garren, L. A.; Gottschalk, E.; Kasper, P. H.; Kreymer, A. E.; Kutschke, R.; Wang, M.; Benussi, L.; Bianco, S.; Fabbri, F. L.; Zallo, A.; Reyes, M.; Cawlfield, C.; Kim, D. Y.; Rahimi, A.; Wiss, J.; Gardner, R.; Kryemadhi, A.; Chung, Y. S.; Kang, J. S.; Ko, B. R.; Kwak, J. W.; Lee, K. B.; Cho, K.; Park, H.; Alimonti, G.; Barberis, S.; Boschini, M.; Cerutti, A.; D'Angelo, P.; Dicorato, M.; Dini, P.; Edera, L.; Erba, S.; Inzani, P.; Leveraro, F.; Malvezzi, S.; Menasce, D.; Mezzadri, M.; Moroni, L.; Pedrini, D.; Pontoglio, C.; Prelz, F.; Rovere, M.; Sala, S.; Davenport, T. F.; Arena, V.; Boca, G.; Bonomi, G.; Gianini, G.; Liguori, G.; Lopes Pegna, D.; Merlo, M. M.; Pantea, D.; Ratti, S. P.; Riccardi, C.; Vitulo, P.; Göbel, C.; Otalora, J.; Hernandez, H.; Lopez, A. M.; Mendez, H.; Paris, A.; Quinones, J.; Ramirez, J. E.; Zhang, Y.; Wilson, J. R.; Handler, T.; Mitchell, R.; Engh, D.; Hosack, M.; Johns, W. E.; Luiggi, E.; Nehring, M.; Sheldon, P. D.; Vaandering, E. W.; Webster, M.; Sheaff, M.; Pennington, M. R.; Focus Collaboration

2007-09-01

Using data collected by the high-energy photoproduction experiment FOCUS at Fermilab we performed a Dalitz plot analysis of the Cabibbo favored decay D+ →K-π+π+. This study uses 53653 Dalitz-plot events with a signal fraction of ∼ 97%, and represents the highest statistics, most complete Dalitz plot analysis for this channel. Results are presented and discussed using two different formalisms. The first is a simple sum of Breit-Wigner functions with freely fitted masses and widths. It is the model traditionally adopted and serves as comparison with the already published analyses. The second uses a K-matrix approach for the dominant S-wave, in which the parameters are fixed by first fitting Kπ scattering data and continued to threshold by Chiral Perturbation Theory. We show that the Dalitz plot distribution for this decay is consistent with the assumption of two-body dominance of the final state interactions and the description of these interactions is in agreement with other data on the Kπ final state.

Variable number of tandem repeats and pulsed-field gel electrophoresis cluster analysis of enterohemorrhagic Escherichia coli serovar O157 strains.

PubMed

Yokoyama, Eiji; Uchimura, Masako

2007-11-01

Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.

Spatiotemporal variations of hydrogeochemistry and its controlling factors in the Gandaki River Basin, Central Himalaya Nepal.

PubMed

Pant, Ramesh Raj; Zhang, Fan; Rehman, Faizan Ur; Wang, Guanxing; Ye, Ming; Zeng, Chen; Tang, Handuo

2018-05-01

The characterization and assessment of water quality in the head water region of Himalaya is necessary, given the immense importance of this region in sustaining livelihoods of people and maintaining ecological balance. A total of 165 water samples were collected from 55 sites during pre-monsoon, monsoon and post-monsoon seasons in 2016 from the Gandaki River Basin of the Central Himalaya, Nepal. The pH, EC values and TDS concentrations were measured in-situ and the concentrations of major ions (Ca 2+ , Mg 2+ , K + , Na + , Cl - , SO 4 2- , NO 3 - ) and Si were analyzed in laboratory. Correlation matrices, paired t-test, cluster analysis, principal component analysis (PCA), the Piper, Gibbs, and Mixing plots, and saturation index were applied to the measurements for evaluating spatiotemporal variation of the major ions. The results reveal mildly alkaline pH values and the following pattern of average ionic dominance: Ca 2+ >Mg 2+ >Na + >K + for cations and HCO 3 - >SO 4 2 - >Cl - >NO 3 - for anions. The results of PCA, Gibbs plot and the ionic relationships displayed the predominance of geogenic weathering processes in areas with carbonate dominant lithology. This conclusion is supported by geochemically different water facies identified in the Piper plot as Ca-HCO 3 (83.03%), mixed Ca-Mg-Cl (12.73.0%) and Ca-Cl (4.24%). Pronounced spatiotemporal heterogeneity demonstrates the influence of climatic, geogenic and anthropogenic conditions. For instance, the Ca 2+ -SO 4 2- , Mg 2+ -SO 4 2- and Na + -Cl - pairs exhibit strong positive correlation with each other in the upstream region, whereas relatively weak correlation in the downstream region, likely indicating the influence of evapo-crystallization processes in the upstream region. Analyses of the suitability of the water supply for drinking and irrigation reveal that the river has mostly retained its natural water quality but poses safety concern at a few locations. Knowledge obtained through this study can contribute to the sustainable management of water quality in the climatically and lithologically distinct segments of the Himalayan river basins. Copyright © 2017 Elsevier B.V. All rights reserved.

Vegetation associations in a rare community type - Coastal tallgrass prairie

USGS Publications Warehouse

Grace, James B.; Allain, Larry K.; Allen, Charles

2000-01-01

The coastal prairie ecoregion is located along the northwestern coastal plain of the Gulf of Mexico in North America. Because of agricultural and urban development, less than 1% of the original 3.4 million ha of this ecosystem type remains in native condition, making it one of the most endangered ecosystems in North America. The objective of this study was to characterize the vegetation and environmental relationships in a relatively pristine example of lowland coastal prairie in order to provide information for use in conservation and restoration. The study area was a small, isolated prairie located near the southern boundary of the coastal prairie region. Samples were taken along three parallel transects that spanned the prairie. Parameters measured included species composition, elevation, soil characteristics, indications of recent disturbance, above-ground biomass, and light penetration through the plant canopy. Fifty-four species were found in the 107 0.25-m2 plots and a total of 96 species were found at the site. Only two non-native species occurred in sample plots, both of which were uncommon. Cluster analysis was used to identify six vegetation groups, which were primarily dominated by members of the Poaceae or Asteraceae. A conspicuous, natural edaphic feature of the prairie was the presence of 'mima' mounds, which are raised areas approximately 0.5 to 1 m high and 5 to 10 m across. Indicator species analysis revealed a significant number of species that were largely restricted to mounds and these were predominately upland and colonizing species. Ordination was performed using nonmetric, multidimensional scaling. The dominant environmental influence on species composition was found to be elevation and a host of correlated factors including those associated with soil organic content. A secondary group of factors, consisting primarily of soil cations, was found to explain additional variance among plots. Overall, this prairie was found to contain plant associations that are now rare in the surrounding landscape. Within the prairie, plant groups were largely separated by a suite of environmental conditions associated with topography. These results suggest that conservation and restoration efforts will need to carefully consider local topographic influences in order to be successful.

Quantitative chemical exchange saturation transfer (qCEST) MRI--RF spillover effect-corrected omega plot for simultaneous determination of labile proton fraction ratio and exchange rate.

PubMed

Sun, Phillip Zhe; Wang, Yu; Dai, ZhuoZhi; Xiao, Gang; Wu, Renhua

2014-01-01

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute proteins and peptides as well as microenvironmental properties. However, the complexity of the CEST MRI effect, which varies with the labile proton content, exchange rate and experimental conditions, underscores the need for developing quantitative CEST (qCEST) analysis. Towards this goal, it has been shown that omega plot is capable of quantifying paramagnetic CEST MRI. However, the use of the omega plot is somewhat limited for diamagnetic CEST (DIACEST) MRI because it is more susceptible to direct radio frequency (RF) saturation (spillover) owing to the relatively small chemical shift. Recently, it has been found that, for dilute DIACEST agents that undergo slow to intermediate chemical exchange, the spillover effect varies little with the labile proton ratio and exchange rate. Therefore, we postulated that the omega plot analysis can be improved if RF spillover effect could be estimated and taken into account. Specifically, simulation showed that both labile proton ratio and exchange rate derived using the spillover effect-corrected omega plot were in good agreement with simulated values. In addition, the modified omega plot was confirmed experimentally, and we showed that the derived labile proton ratio increased linearly with creatine concentration (p < 0.01), with little difference in their exchange rate (p = 0.32). In summary, our study extends the conventional omega plot for quantitative analysis of DIACEST MRI. Copyright © 2014 John Wiley & Sons, Ltd.

F-15 inlet/engine test techniques and distortion methodologies studies. Volume 2: Time variant data quality analysis plots

NASA Technical Reports Server (NTRS)

Stevens, C. H.; Spong, E. D.; Hammock, M. S.

1978-01-01

Time variant data quality analysis plots were used to determine if peak distortion data taken from a subscale inlet model can be used to predict peak distortion levels for a full scale flight test vehicle.

Weighted analysis methods for mapped plot forest inventory data: Tables, regressions, maps and graphs

Treesearch

Paul C. Van Deusen; Linda S. Heath

2010-01-01

Weighted estimation methods for analysis of mapped plot forest inventory data are discussed. The appropriate weighting scheme can vary depending on the type of analysis and graphical display. Both statistical issues and user expectations need to be considered in these methods. A weighting scheme is proposed that balances statistical considerations and the logical...

Studies of cluster X-ray sources, energy spectra for the Perseus, Virgo, and Coma clusters

NASA Technical Reports Server (NTRS)

Kellogg, E.; Baldwin, J. R.; Koch, D.

1975-01-01

Final Uhuru X-ray differential-energy spectra are presented for the Perseus, Virgo, and Coma clusters. Power-law and isothermal bremsstrahlung model spectra with low-energy cutoffs are given, and the energy-dependent Gaunt factor is calculated for the bremsstrahlung. The spectra, which are best fits to the Uhuru data between 2 and 10 keV, are compared with previous observations of these sources in the energy range from 0.1 to 100 keV. The problem of parameter estimation is discussed, error bars with 68% confidence are given for the independently determined slope and cutoff parameters, and the 68% confidence limits are plotted for the fitted spectral functions. The data for Perseus above 20 keV marginally favor the bremsstrahlung fit, those for Virgo between 0.25 and 1.0 keV clearly favor that curve, and those for Coma indicate a low-energy turnover or cutoff. Implications of such a cutoff are briefly discussed.

An RR Lyrae period shift in terms of the Fourier parameter Phi sub 31

NASA Technical Reports Server (NTRS)

Clement, Christine M.; Jankulak, Michael; Simon, Norman R.

1992-01-01

The Fourier phase parameter Phi sub 31 has been determined for RRc stars in five globular clusters, NGC 6171, M5, M3, M53, and M15. The results indicate that the RRc stars in a given cluster show a sequence of Phi sub 31 increasing with period, and that the higher the cluster metallicity, the higher the sequence lies in a plot of Phi sub 31 with period. The Phi sub 31 values for the stars in NGC 6171 and M5 presented here are based on observations made with the University of Toronto 0.61 m telescope at Las Campanas, Chile, while those for M3, M53, and M15 are based on published data. A bootstrap procedure has been used to establish the uncertainties in the Fourier parameters. The physical significance of the relationship among Phi sub 31, period, and metallicity is not yet understood. It will need to be tested with hydrodynamic pulsation models computed with new opacities.

Inductive sensor performance in partial discharges and noise separation by means of spectral power ratios.

PubMed

Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo

2014-02-19

Partial discharge (PD) detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shum, Andrew D.; Parkinson, Dilworth Y.; Xiao, Xianghui

The performance of polymer-electrolyte fuel cells is heavily dependent on proper management of liquid water. One particular reason is that liquid water can collect in the gas diffusion layers (GDLs) blocking the reactant flow to the catalyst layer. This results in increased mass-transport losses. At higher temperatures, evaporation of water becomes a dominant water-removal mechanism and specifically phase-change-induced (PCI) flow is present due to thermal gradients. This study used synchrotron based micro X-ray computed tomography (CT) to visualize and quantify the water distribution within gas diffusion layers subject to a thermal gradient. Plotting saturation as a function of through-plane distancemore » quantitatively shows water redistribution, where water evaporates at hotter locations and condenses in colder locations. The morphology of the 2 GDLs on the micro-scale, as well as evaporating water clusters, are resolved, indicating that the GDL voids are slightly prolate, whereas water clusters are oblate. From the mean radii of water distributions and visual inspection, it is observed that larger water clusters evaporate faster than smaller ones.« less

A hemagglutinating variant of Prevotella melaninogenica isolated from the oral cavity.

PubMed

Haraldsson, G; Holbrook, W P

1998-12-01

Strains resembling Prevotella melaninogenica were isolated from healthy subjects and patients with periodontal disease and were identified using: a 5-test phenotypic screen; commercial identification kits; and a 16S rRNA-based polymerase chain reaction (PCR) method. Eleven clinical isolates closely resembling P. melaninogenica, and all from patients with periodontitis, were able to agglutinate erythrocytes. In the electron microscope, hemagglutinating isolates showed fimbria-like structures, that were not seen on non-hemagglutinating isolates. Some strains were further classified with PCR-restriction fragment-length polymorphism (RFLP) of 16S rRNA genes. Amplified 16S rDNA was digested using five different endonucleases, separated with agarose gel electrophoresis, stained and photographed. Photographs were then scanned, digitized and a distance matrix calculated using Dice coefficient, where the presence or absence of a band was used as a character. The distance matrix was plotted as a phenogram. At 70% similarity six clusters were seen. Type strains of separate Prevotella species did not fall into any cluster. Hemagglutinating isolates fell into three clusters: four clustered with the type strains of P. melaninogenica and Prevotella veroralis; four with other P. melaninogenica isolates and two hemagglutinating isolates clustered together Prevotella loescheii. The PCR-RFLP results showed that the hemagglutinating strains did not form a homogenous group inside the Prevotella genus.

Investigating the limitations of tree species classification using the Combined Cluster and Discriminant Analysis method for low density ALS data from a dense forest region in Aggtelek (Hungary)

NASA Astrophysics Data System (ADS)

Koma, Zsófia; Deák, Márton; Kovács, József; Székely, Balázs; Kelemen, Kristóf; Standovár, Tibor

2016-04-01

Airborne Laser Scanning (ALS) is a widely used technology for forestry classification applications. However, single tree detection and species classification from low density ALS point cloud is limited in a dense forest region. In this study we investigate the division of a forest into homogenous groups at stand level. The study area is located in the Aggtelek karst region (Northeast Hungary) with a complex relief topography. The ALS dataset contained only 4 discrete echoes (at 2-4 pt/m2 density) from the study area during leaf-on season. Ground-truth measurements about canopy closure and proportion of tree species cover are available for every 70 meter in 500 square meter circular plots. In the first step, ALS data were processed and geometrical and intensity based features were calculated into a 5×5 meter raster based grid. The derived features contained: basic statistics of relative height, canopy RMS, echo ratio, openness, pulse penetration ratio, basic statistics of radiometric feature. In the second step the data were investigated using Combined Cluster and Discriminant Analysis (CCDA, Kovács et al., 2014). The CCDA method first determines a basic grouping for the multiple circle shaped sampling locations using hierarchical clustering and then for the arising grouping possibilities a core cycle is executed comparing the goodness of the investigated groupings with random ones. Out of these comparisons difference values arise, yielding information about the optimal grouping out of the investigated ones. If sub-groups are then further investigated, one might even find homogeneous groups. We found that low density ALS data classification into homogeneous groups are highly dependent on canopy closure, and the proportion of the dominant tree species. The presented results show high potential using CCDA for determination of homogenous separable groups in LiDAR based tree species classification. Aggtelek Karst/Slovakian Karst Caves" (HUSK/1101/221/0180, Aggtelek NP), data evaluation: 'Multipurpose assessment serving forest biodiversity conservation in the Carpathian region of Hungary', Swiss-Hungarian Cooperation Programme (SH/4/13 Project). BS contributed as an Alexander von Humboldt Research Fellow. J. Kovács, S. Kovács, N. Magyar, P. Tanos, I. G. Hatvani, and A. Anda (2014), Classification into homogeneous groups using combined cluster and discriminant analysis, Environmental Modelling & Software, 57, 52-59.

Automated extraction and analysis of rock discontinuity characteristics from 3D point clouds

NASA Astrophysics Data System (ADS)

Bianchetti, Matteo; Villa, Alberto; Agliardi, Federico; Crosta, Giovanni B.

2016-04-01

A reliable characterization of fractured rock masses requires an exhaustive geometrical description of discontinuities, including orientation, spacing, and size. These are required to describe discontinuum rock mass structure, perform Discrete Fracture Network and DEM modelling, or provide input for rock mass classification or equivalent continuum estimate of rock mass properties. Although several advanced methodologies have been developed in the last decades, a complete characterization of discontinuity geometry in practice is still challenging, due to scale-dependent variability of fracture patterns and difficult accessibility to large outcrops. Recent advances in remote survey techniques, such as terrestrial laser scanning and digital photogrammetry, allow a fast and accurate acquisition of dense 3D point clouds, which promoted the development of several semi-automatic approaches to extract discontinuity features. Nevertheless, these often need user supervision on algorithm parameters which can be difficult to assess. To overcome this problem, we developed an original Matlab tool, allowing fast, fully automatic extraction and analysis of discontinuity features with no requirements on point cloud accuracy, density and homogeneity. The tool consists of a set of algorithms which: (i) process raw 3D point clouds, (ii) automatically characterize discontinuity sets, (iii) identify individual discontinuity surfaces, and (iv) analyse their spacing and persistence. The tool operates in either a supervised or unsupervised mode, starting from an automatic preliminary exploration data analysis. The identification and geometrical characterization of discontinuity features is divided in steps. First, coplanar surfaces are identified in the whole point cloud using K-Nearest Neighbor and Principal Component Analysis algorithms optimized on point cloud accuracy and specified typical facet size. Then, discontinuity set orientation is calculated using Kernel Density Estimation and principal vector similarity criteria. Poles to points are assigned to individual discontinuity objects using easy custom vector clustering and Jaccard distance approaches, and each object is segmented into planar clusters using an improved version of the DBSCAN algorithm. Modal set orientations are then recomputed by cluster-based orientation statistics to avoid the effects of biases related to cluster size and density heterogeneity of the point cloud. Finally, spacing values are measured between individual discontinuity clusters along scanlines parallel to modal pole vectors, whereas individual feature size (persistence) is measured using 3D convex hull bounding boxes. Spacing and size are provided both as raw population data and as summary statistics. The tool is optimized for parallel computing on 64bit systems, and a Graphic User Interface (GUI) has been developed to manage data processing, provide several outputs, including reclassified point clouds, tables, plots, derived fracture intensity parameters, and export to modelling software tools. We present test applications performed both on synthetic 3D data (simple 3D solids) and real case studies, validating the results with existing geomechanical datasets.

[Application of Stata software to test heterogeneity in meta-analysis method].

PubMed

Wang, Dan; Mou, Zhen-yun; Zhai, Jun-xia; Zong, Hong-xia; Zhao, Xiao-dong

2008-07-01

To introduce the application of Stata software to heterogeneity test in meta-analysis. A data set was set up according to the example in the study, and the corresponding commands of the methods in Stata 9 software were applied to test the example. The methods used were Q-test and I2 statistic attached to the fixed effect model forest plot, H statistic and Galbraith plot. The existence of the heterogeneity among studies could be detected by Q-test and H statistic and the degree of the heterogeneity could be detected by I2 statistic. The outliers which were the sources of the heterogeneity could be spotted from the Galbraith plot. Heterogeneity test in meta-analysis can be completed by the four methods in Stata software simply and quickly. H and I2 statistics are more robust, and the outliers of the heterogeneity can be clearly seen in the Galbraith plot among the four methods.

Segmented Poincaré plot analysis for risk stratification in patients with dilated cardiomyopathy.

PubMed

Voss, A; Fischer, C; Schroeder, R; Figulla, H R; Goernig, M

2010-01-01

The prognostic value of heart rate variability in patients with dilated cardiomyopathy (DCM) is limited and does not contribute to risk stratification although the dynamics of ventricular repolarization differs considerably between DCM patients and healthy subjects. Neither linear nor nonlinear methods of heart rate variability analysis could discriminate between patients at high and low risk for sudden cardiac death. The aim of this study was to analyze the suitability of the new developed segmented Poincaré plot analysis (SPPA) to enhance risk stratification in DCM. In contrast to the usual applied Poincaré plot analysis the SPPA retains nonlinear features from investigated beat-to-beat interval time series. Main features of SPPA are the rotation of cloud of points and their succeeded variability depended segmentation. Significant row and column probabilities were calculated from the segments and led to discrimination (up to p<0.005) between low and high risk in DCM patients. For the first time an index from Poincaré plot analysis of heart rate variability was able to contribute to risk stratification in patients suffering from DCM.

Treelink: data integration, clustering and visualization of phylogenetic trees.

PubMed

Allende, Christian; Sohn, Erik; Little, Cedric

2015-12-29

Phylogenetic trees are central to a wide range of biological studies. In many of these studies, tree nodes need to be associated with a variety of attributes. For example, in studies concerned with viral relationships, tree nodes are associated with epidemiological information, such as location, age and subtype. Gene trees used in comparative genomics are usually linked with taxonomic information, such as functional annotations and events. A wide variety of tree visualization and annotation tools have been developed in the past, however none of them are intended for an integrative and comparative analysis. Treelink is a platform-independent software for linking datasets and sequence files to phylogenetic trees. The application allows an automated integration of datasets to trees for operations such as classifying a tree based on a field or showing the distribution of selected data attributes in branches and leafs. Genomic and proteonomic sequences can also be linked to the tree and extracted from internal and external nodes. A novel clustering algorithm to simplify trees and display the most divergent clades was also developed, where validation can be achieved using the data integration and classification function. Integrated geographical information allows ancestral character reconstruction for phylogeographic plotting based on parsimony and likelihood algorithms. Our software can successfully integrate phylogenetic trees with different data sources, and perform operations to differentiate and visualize those differences within a tree. File support includes the most popular formats such as newick and csv. Exporting visualizations as images, cluster outputs and genomic sequences is supported. Treelink is available as a web and desktop application at http://www.treelinkapp.com .

Myth Structure and Media Fiction Plot: An Exploration.

ERIC Educational Resources Information Center

Harless, James D.

Based on the general research of Joseph Campbell in adventure plots from mythology, the author explores the simplified monomyth plots currently in frequent use in mass media programing. The close relationship of media fiction to mythic stories is established through the analysis of more than 25 stories resulting from media broadcasting. The media…

Precise FIA plot registration using field and dense LIDAR data

Treesearch

Demetrios Gatziolis

2009-01-01

Precise registration of forest inventory and analysis (FIA) plots is a prerequisite for an effective fusion of field data with ancillary spatial information, which is an approach commonly employed in the mapping of various forest parameters. Although the adoption of Global Positioning System technology has improved the precision of plot coordinates obtained during...

Comparison of Imputation Procedures for Replacing Denied-access Plots

Treesearch

Susan L. King

2005-01-01

In forest inventories, missing plots are caused by hazardous terrain, inaccessible locations, or denied access. Maryland had a large number of denied-access plots in the latest periodic inventory conducted by the Northeastern Forest Inventory and Analysis unit. The denial pattern, which can introduce error into the estimates, was investigated by dropping the 1999...

Refining FIA plot locations using LiDAR point clouds

Treesearch

Charlie Schrader-Patton; Greg C. Liknes; Demetrios Gatziolis; Brian M. Wing; Mark D. Nelson; Patrick D. Miles; Josh Bixby; Daniel G. Wendt; Dennis Kepler; Abbey Schaaf

2015-01-01

Forest Inventory and Analysis (FIA) plot location coordinate precision is often insufficient for use with high resolution remotely sensed data, thereby limiting the use of these plots for geospatial applications and reducing the validity of models that assume the locations are precise. A practical and efficient method is needed to improve coordinate precision. To...

National FIA plot intensification procedure report

Treesearch

Jock A. Blackard; Paul L. Patterson

2014-01-01

The Forest Inventory and Analysis (FIA) program of the U.S. Forest Service (USFS) measures a spatially distributed base grid of forest inventory plots across the United States. The sampling intensity of plots may be increased in some regions when warranted by specific inventory objectives. Several intensification methods have been developed within FIA and USFS National...

An investigation of condition mapping and plot proportion calculation issues

Treesearch

Demetrios Gatziolis

2007-01-01

A systematic examination of Forest Inventory and Analysis condition data collected under the annual inventory protocol in the Pacific Northwest region between 2000 and 2004 revealed the presence of errors both in condition topology and plot proportion computations. When plots were compiled to generate population estimates, proportion errors were found to cause...

The Role of Recurrence Plots in Characterizing the Output-Unemployment Relationship: An Analysis

PubMed Central

Caraiani, Petre; Haven, Emmanuel

2013-01-01

We analyse the output-unemployment relationship using an approach based on cross-recurrence plots and quantitative recurrence analysis. We use post-war period quarterly U.S. data. The results obtained show the emergence of a complex and interesting relationship. PMID:23460814

The Impact of Selection, Gene Conversion, and Biased Sampling on the Assessment of Microbial Demography.

PubMed

Lapierre, Marguerite; Blin, Camille; Lambert, Amaury; Achaz, Guillaume; Rocha, Eduardo P C

2016-07-01

Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using skyline plots and site frequency spectra (SFS). Forward simulations based on biologically relevant parameters from Escherichia coli populations showed that theoretical arguments on the detrimental impact of recombination and especially natural selection on the reconstructed genealogies cannot be ignored in practice. In fact, both processes systematically lead to spurious interpretations of population expansion in skyline plots (and in SFS for selection). Weak purifying selection, and especially positive selection, had important effects on skyline plots, showing patterns akin to those of population expansions. State-of-the-art techniques to remove recombination further amplified these biases. We simulated three common sampling biases in microbiological research: uniform, clustered, and mixed sampling. Alone, or together with recombination and selection, they further mislead demographic inferences producing almost any possible skyline shape or SFS. Interestingly, sampling sub-populations also affected skyline plots and SFS, because the coalescent rates of populations and their sub-populations had different distributions. This study suggests that extreme caution is needed to infer demographic changes solely based on reconstructed genealogies. We suggest that the development of novel sampling strategies and the joint analyzes of diverse population genetic methods are strictly necessary to estimate demographic changes in populations where selection, recombination, and biased sampling are present. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.

PubMed

Van Gassen, Sofie; Callebaut, Britt; Van Helden, Mary J; Lambrecht, Bart N; Demeester, Piet; Dhaene, Tom; Saeys, Yvan

2015-07-01

The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self-Organizing Map. Using a two-level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at https://github.com/SofieVG/FlowSOM and will be made available at Bioconductor. © 2015 International Society for Advancement of Cytometry.

Changes in tree growth, biomass and vegetation over a 13-year period in the Swedish sub-Arctic.

PubMed

Hedenås, Henrik; Olsson, Håkan; Jonasson, Christer; Bergstedt, Johan; Dahlberg, Ulrika; Callaghan, Terry V

2011-09-01

This study was conducted in the Swedish subArctic, near Abisko, in order to assess the direction and scale of possible vegetation changes in the alpine-birch forest ecotone. We have re-surveyed shrub, tree and vegetation data at 549 plots grouped into 61 clusters. The plots were originally surveyed in 1997 and re-surveyed in 2010. Our study is unique for the area as we have quantitatively estimated a 19% increase in tree biomass mainly within the existing birch forest. We also found significant increases in the cover of two vegetation types--"birch forest-heath with mosses" and "meadow with low herbs", while the cover of snowbed vegetation decreased significantly. The vegetation changes might be caused by climate, herbivory and past human impact but irrespective of the causes, the observed transition of the vegetation will have substantial effects on the mountain ecosystems.

Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research.

PubMed

Graffelman, Jan; van Eeuwijk, Fred

2005-12-01

The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.

Computation of shock wave/target interaction

NASA Technical Reports Server (NTRS)

Mark, A.; Kutler, P.

1983-01-01

Computational results of shock waves impinging on targets and the ensuing diffraction flowfield are presented. A number of two-dimensional cases are computed with finite difference techniques. The classical case of a shock wave/cylinder interaction is compared with shock tube data and shows the quality of the computations on a pressure-time plot. Similar results are obtained for a shock wave/rectangular body interaction. Here resolution becomes important and the use of grid clustering techniques tend to show good agreement with experimental data. Computational results are also compared with pressure data resulting from shock impingement experiments for a complicated truck-like geometry. Here of significance are the grid generation and clustering techniques used. For these very complicated bodies, grids are generated by numerically solving a set of elliptic partial differential equations.

Ripening-dependent metabolic changes in the volatiles of pineapple (Ananas comosus (L.) Merr.) fruit: II. Multivariate statistical profiling of pineapple aroma compounds based on comprehensive two-dimensional gas chromatography-mass spectrometry.

PubMed

Steingass, Christof Björn; Jutzi, Manfred; Müller, Jenny; Carle, Reinhold; Schmarr, Hans-Georg

2015-03-01

Ripening-dependent changes of pineapple volatiles were studied in a nontargeted profiling analysis. Volatiles were isolated via headspace solid phase microextraction and analyzed by comprehensive 2D gas chromatography and mass spectrometry (HS-SPME-GC×GC-qMS). Profile patterns presented in the contour plots were evaluated applying image processing techniques and subsequent multivariate statistical data analysis. Statistical methods comprised unsupervised hierarchical cluster analysis (HCA) and principal component analysis (PCA) to classify the samples. Supervised partial least squares discriminant analysis (PLS-DA) and partial least squares (PLS) regression were applied to discriminate different ripening stages and describe the development of volatiles during postharvest storage, respectively. Hereby, substantial chemical markers allowing for class separation were revealed. The workflow permitted the rapid distinction between premature green-ripe pineapples and postharvest-ripened sea-freighted fruits. Volatile profiles of fully ripe air-freighted pineapples were similar to those of green-ripe fruits postharvest ripened for 6 days after simulated sea freight export, after PCA with only two principal components. However, PCA considering also the third principal component allowed differentiation between air-freighted fruits and the four progressing postharvest maturity stages of sea-freighted pineapples.

[Recurrence plot analysis of HRV for brain ischemia and asphyxia].

PubMed

Chen, Xiaoming; Qiu, Yihong; Zhu, Yisheng

2008-02-01

Heart rate variability (HRV) is the tiny variability existing in the cycles of the heart beats, which reflects the corresponding balance between sympathetic and vagus nerves. Since the nonlinear characteristic of HRV is confirmed, the Recurrence Plot method, a nonlinear dynamic analysis method based on the complexity, could be used to analyze HRV. The results showed the recurrence plot structures and some quantitative indices (L-Mean, L-Entr) during asphyxia insult vary significantly as compared to those in normal conditions, which offer a new method to monitor brain asphyxia injury.

Numerical flow analysis of axial flow compressor for steady and unsteady flow cases

NASA Astrophysics Data System (ADS)

Prabhudev, B. M.; Satish kumar, S.; Rajanna, D.

2017-07-01

Performance of jet engine is dependent on the performance of compressor. This paper gives numerical study of performance characteristics for axial compressor. The test rig is present at CSIR LAB Bangalore. Flow domains are meshed and fluid dynamic equations are solved using ANSYS package. Analysis is done for six different speeds and for operating conditions like choke, maximum efficiency & before stall point. Different plots are compared and results are discussed. Shock displacement, vortex flows, leakage patterns are presented along with unsteady FFT plot and time step plot.

Representing Uncertainty on Model Analysis Plots

ERIC Educational Resources Information Center

Smith, Trevor I.

2016-01-01

Model analysis provides a mechanism for representing student learning as measured by standard multiple-choice surveys. The model plot contains information regarding both how likely students in a particular class are to choose the correct answer and how likely they are to choose an answer consistent with a well-documented conceptual model.…

Model-independent plot of dynamic PET data facilitates data interpretation and model selection.

PubMed

Munk, Ole Lajord

2012-02-21

When testing new PET radiotracers or new applications of existing tracers, the blood-tissue exchange and the metabolism need to be examined. However, conventional plots of measured time-activity curves from dynamic PET do not reveal the inherent kinetic information. A novel model-independent volume-influx plot (vi-plot) was developed and validated. The new vi-plot shows the time course of the instantaneous distribution volume and the instantaneous influx rate. The vi-plot visualises physiological information that facilitates model selection and it reveals when a quasi-steady state is reached, which is a prerequisite for the use of the graphical analyses by Logan and Gjedde-Patlak. Both axes of the vi-plot have direct physiological interpretation, and the plot shows kinetic parameter in close agreement with estimates obtained by non-linear kinetic modelling. The vi-plot is equally useful for analyses of PET data based on a plasma input function or a reference region input function. The vi-plot is a model-independent and informative plot for data exploration that facilitates the selection of an appropriate method for data analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Au-nanocluster emission based glucose sensing.

PubMed

Hussain, A M P; Sarangi, S N; Kesarwani, J A; Sahu, S N

2011-11-15

Fabrication of a glucose biosensor based on Au-cluster emission quenching in the UV region is reported. The glucose biosensor is highly sensitive to β-d-glucose in 2.5-25.0mM range as confirmed from a linear calibration plot between Au-cluster colloid emission intensity as a function of β-d-glucose concentration. The interaction of β-d-glucose with l-cysteine capped Au cluster colloids has been confirmed from their Fourier transformed infrared spectroscopy (FTIR) measurements. It has been found that the biomolecules present in the serum such as ascorbic and uric acids, proteins and peptides do not interfere and affect in glucose estimation as confirmed from their absorption and fluorescence (FL) emission measurements. Practical utility of this sensor based on FL quenching method has been demonstrated by estimating the glucose level in human serum that includes diabetes and the data were found to be comparable or more accurate than those of the pathological data obtained from a local hospital. In addition, this biosensor is useful to detect glucose level over a wide range with sensor response time of the order of nano to picoseconds that is emission lifetime of Au clusters. Copyright © 2011 Elsevier B.V. All rights reserved.

Variety identification of brown sugar using short-wave near infrared spectroscopy and multivariate calibration

NASA Astrophysics Data System (ADS)

Yang, Haiqing; Wu, Di; He, Yong

2007-11-01

Near-infrared spectroscopy (NIRS) with the characteristics of high speed, non-destructiveness, high precision and reliable detection data, etc. is a pollution-free, rapid, quantitative and qualitative analysis method. A new approach for variety discrimination of brown sugars using short-wave NIR spectroscopy (800-1050nm) was developed in this work. The relationship between the absorbance spectra and brown sugar varieties was established. The spectral data were compressed by the principal component analysis (PCA). The resulting features can be visualized in principal component (PC) space, which can lead to discovery of structures correlative with the different class of spectral samples. It appears to provide a reasonable variety clustering of brown sugars. The 2-D PCs plot obtained using the first two PCs can be used for the pattern recognition. Least-squares support vector machines (LS-SVM) was applied to solve the multivariate calibration problems in a relatively fast way. The work has shown that short-wave NIR spectroscopy technique is available for the brand identification of brown sugar, and LS-SVM has the better identification ability than PLS when the calibration set is small.

Size-based emphysema cluster analysis on low attenuation area in 3D volumetric CT: comparison with pulmonary functional test

NASA Astrophysics Data System (ADS)

Lee, Minho; Kim, Namkug; Lee, Sang Min; Seo, Joon Beom; Oh, Sang Young

2015-03-01

To quantify low attenuation area (LAA) of emphysematous regions according to cluster size in 3D volumetric CT data of chronic obstructive pulmonary disease (COPD) patients and to compare these indices with their pulmonary functional test (PFT). Sixty patients with COPD were scanned by a more than 16-multi detector row CT scanner (Siemens Sensation 16 and 64) within 0.75mm collimation. Based on these LAA masks, a length scale analysis to estimate each emphysema LAA's size was performed as follows. At first, Gaussian low pass filter from 30mm to 1mm kernel size with 1mm interval on the mask was performed from large to small size, iteratively. Centroid voxels resistant to the each filter were selected and dilated by the size of the kernel, which was regarded as the specific size emphysema mask. The slopes of area and number of size based LAA (slope of semi-log plot) were analyzed and compared with PFT. PFT parameters including DLco, FEV1, and FEV1/FVC were significantly (all p-value< 0.002) correlated with the slopes (r-values; -0.73, 0.54, 0.69, respectively) and EI (r-values; -0.84, -0.60, -0.68, respectively). In addition, the D independently contributed regression for FEV1 and FEV1/FVC (adjust R sq. of regression study: EI only, 0.70, 0.45; EI and D, 0.71, 0.51, respectively). By the size based LAA segmentation and analysis, we evaluated the Ds of area, number, and distribution of size based LAA, which would be independent factors for predictor of PFT parameters.

Identification of hidden relationships from the coupling of hydrophobic cluster analysis and domain architecture information.

PubMed

Faure, Guilhem; Callebaut, Isabelle

2013-07-15

Describing domain architecture is a critical step in the functional characterization of proteins. However, some orphan domains do not match any profile stored in dedicated domain databases and are thereby difficult to analyze. We present here an original novel approach, called TREMOLO-HCA, for the analysis of orphan domain sequences and inspired from our experience in the use of Hydrophobic Cluster Analysis (HCA). Hidden relationships between protein sequences can be more easily identified from the PSI-BLAST results, using information on domain architecture, HCA plots and the conservation degree of amino acids that may participate in the protein core. This can lead to reveal remote relationships with known families of domains, as illustrated here with the identification of a hidden Tudor tandem in the human BAHCC1 protein and a hidden ET domain in the Saccharomyces cerevisiae Taf14p and human AF9 proteins. The results obtained in such a way are consistent with those provided by HHPRED, based on pairwise comparisons of HHMs. Our approach can, however, be applied even in absence of domain profiles or known 3D structures for the identification of novel families of domains. It can also be used in a reverse way for refining domain profiles, by starting from known protein domain families and identifying highly divergent members, hitherto considered as orphan. We provide a possible integration of this approach in an open TREMOLO-HCA package, which is fully implemented in python v2.7 and is available on request. Instructions are available at http://www.impmc.upmc.fr/∼callebau/tremolohca.html. isabelle.callebaut@impmc.upmc.fr Supplementary Data are available at Bioinformatics online.

PETRO.CALC.PLOT, Microsoft Excel macros to aid petrologic interpretation

USGS Publications Warehouse

Sidder, G.B.

1994-01-01

PETRO.CALC.PLOT is a package of macros which normalizes whole-rock oxide data to 100%, calculates the cation percentages and molecular proportions used for normative mineral calculations, computes the apices for ternary diagrams, determines sums and ratios of specific elements of petrologic interest, and plots 33 X-Y graphs and five ternary diagrams. PETRO.CALC.PLOT also may be used to create other diagrams as desired by the user. The macros run in Microsoft Excel 3.0 and 4.0 for Macintosh computers and in Microsoft Excel 3.0 and 4.0 for Windows. Macros provided in PETRO.CALC.PLOT minimize repetition and time required to recalculate and plot whole-rock oxide data for petrologic analysis. ?? 1994.

User manual for two simple postscript output FORTRAN plotting routines

NASA Technical Reports Server (NTRS)

Nguyen, T. X.

1991-01-01

Graphics is one of the important tools in engineering analysis and design. However, plotting routines that generate output on high quality laser printers normally come in graphics packages, which tend to be expensive and system dependent. These factors become important for small computer systems or desktop computers, especially when only some form of a simple plotting routine is sufficient. With the Postscript language becoming popular, there are more and more Postscript laser printers now available. Simple, versatile, low cost plotting routines that can generate output on high quality laser printers are needed and standard FORTRAN language plotting routines using output in Postscript language seems logical. The purpose here is to explain two simple FORTRAN plotting routines that generate output in Postscript language.

The Zombie Plot: A Simple Graphic Method for Visualizing the Efficacy of a Diagnostic Test.

PubMed

Richardson, Michael L

2016-08-09

One of the most important jobs of a radiologist is to pick the most appropriate imaging test for a particular clinical situation. Making a proper selection sometimes requires statistical analysis. The objective of this article is to introduce a simple graphic technique, an ROC plot that has been divided into zones of mostly bad imaging efficacy (ZOMBIE, hereafter referred to as the "zombie plot"), that transforms information about imaging efficacy from the numeric domain into the visual domain. The numeric rationale for the use of zombie plots is given, as are several examples of the clinical use of these plots. Two online calculators are described that simplify the process of producing a zombie plot.

Investigation on the structural, magnetic and magnetocaloric properties of nanocrystalline Pr-deficient Pr1-xSrxMnO3-δ manganites

NASA Astrophysics Data System (ADS)

Arun, B.; Athira, M.; Akshay, V. R.; Sudakshina, B.; Mutta, Geeta R.; Vasundhara, M.

2018-02-01

We have investigated the structural, magnetic and magnetocaloric properties of nanocrystalline Pr-deficient Pr1-xSrxMnO3-δ Perovskite manganites. Rietveld refinement of the X-ray powder diffraction patterns confirms that all the studied compounds have crystallized into an orthorhombic structure with Pbnm space group. Transmission electron microscopy analysis reveals nanocrystalline compounds with crystallite size less than 50 nm. The selected area electron diffraction patterns reveal the highly crystalline nature of the compounds and energy dispersive X-ray spectroscopic analysis shows that the obtained compositions are nearly identical with the nominal one. The oxygen stoichiometry is estimated by iodometric titration method and stoichiometric compositions are confirmed by X-ray Fluorescence Spectrometry analysis. A large bifurcation is observed in the ZFC/FC curves and Arrott plots not show a linear relation but have a convex curvature nature. The temperature dependence of inverse magnetic susceptibility at higher temperature confirms the existence of ferromagnetic clusters. The experimental results reveal that the reduction of crystallite size to nano metric scale in Pr-deficient manganites adversely influences structural, magnetic and magnetocaloric properties as compared to its bulk counterparts reported earlier.

Feasibility of laser-induced breakdown spectroscopy (LIBS) for classification of sea salts.

PubMed

Tan, Man Minh; Cui, Sheng; Yoo, Jonghyun; Han, Song-Hee; Ham, Kyung-Sik; Nam, Sang-Ho; Lee, Yonghoon

2012-03-01

We have investigated the feasibility of laser-induced breakdown spectroscopy (LIBS) as a fast, reliable classification tool for sea salts. For 11 kinds of sea salts, potassium (K), magnesium (Mg), calcium (Ca), and aluminum (Al), concentrations were measured by inductively coupled plasma-atomic emission spectroscopy (ICP-AES), and the LIBS spectra were recorded in the narrow wavelength region between 760 and 800 nm where K (I), Mg (I), Ca (II), Al (I), and cyanide (CN) band emissions are observed. The ICP-AES measurements revealed that the K, Mg, Ca, and Al concentrations varied significantly with the provenance of each salt. The relative intensities of the K (I), Mg (I), Ca (II), and Al (I) peaks observed in the LIBS spectra are consistent with the results using ICP-AES. The principal component analysis of the LIBS spectra provided the score plot with quite a high degree of clustering. This indicates that classification of sea salts by chemometric analysis of LIBS spectra is very promising. Classification models were developed by partial least squares discriminant analysis (PLS-DA) and evaluated. In addition, the Al (I) peaks enabled us to discriminate between different production methods of the salts. © 2012 Society for Applied Spectroscopy

Analysis issues due to mapped conditions changing over time

Treesearch

Paul. Van Deusen

2015-01-01

Plot mapping is one of the innovations that were implemented when FIA moved to the annual forest inventory system. Mapped plots can improve the precision of estimates if the mapped conditions are carefully chosen and used judiciously. However, after plots are remeasured multiple times, it can be difficult to properly track changes in conditions and incorporate this...

Compensating for missing plot observations inforest inventory estimation

Treesearch

Ronald E. McRoberts

2003-01-01

The Enhanced Forest Inventory and Analysis program of the U.S. Forest Service has established a nationwide array of permanent field plots, each representing approximately 2400 ha. Each plot has been assigned to one of five interpenetrating, nonoverlapping panels, with one panel selected for measurement on a rotating basis each year. As with most large surveys,...

Estimating number and size of forest patches from FIA plot data

Treesearch

Mark D. Nelson; Andrew J. Lister; Mark H. Hansen

2009-01-01

Forest inventory and analysis (FIA) annual plot data provide for estimates of forest area, type, volume, growth, and other attributes. Estimates of forest landscape metrics, such as those describing abundance, size, and shape of forest patches, however, typically are not derived from FIA plot data but from satellite image-based land cover maps. Associating image-based...

The hexagon/panel system for selecting FIA plots under an annual inventory

Treesearch

Gary J. Brand; Mark D. Nelson; Daniel G. Wendt; Kevin K. Nimerfro

2000-01-01

Forest Inventory and Analysis (FIA) is changing to an annual nationwide forest inventory. This paper describes the sampling grid used to distribute FIA plots across the landscape and to allocate them to a particular measurement year. We also describe the integration of the F1A and Forest Health Monitoring (FHM) plot networks.

Effects of plot size on forest-type algorithm accuracy

Treesearch

James A. Westfall

2009-01-01

The Forest Inventory and Analysis (FIA) program utilizes an algorithm to consistently determine the forest type for forested conditions on sample plots. Forest type is determined from tree size and species information. Thus, the accuracy of results is often dependent on the number of trees present, which is highly correlated with plot area. This research examines the...

Estimating mapped-plot forest attributes with ratios of means

Treesearch

S.J. Zarnoch; W.A. Bechtold

2000-01-01

The mapped-plot design utilized by the U.S. Department of Agriculture (USDA) Forest Inventory and Analysis and the National Forest Health Monitoring Programs is described. Data from 2458 forested mapped plots systematically spread across 25 States reveal that 35 percent straddle multiple conditions. The ratio-of-means estimator is developed as a method to obtain...

The Gran Plot Analysis of an Acid Mixture. An Undergraduate Experiment to Highlight this Alternate Method.

ERIC Educational Resources Information Center

Boiani, James A.

1986-01-01

Describes an experiment which uses the Gran plot for analyzing free ions as well as those involved in an equilibrium. Discusses the benefits of using Gran plots in the study of acids, as well as other analytes in solutions. Presents background theory along with a description of the experimental procedures. (TW)

An Intuitive Graphical Approach to Understanding the Split-Plot Experiment

ERIC Educational Resources Information Center

Robinson, Timothy J.; Brenneman, William A.; Myers, William R.

2009-01-01

While split-plot designs have received considerable attention in the literature over the past decade, there seems to be a general lack of intuitive understanding of the error structure of these designs and the resulting statistical analysis. Typically, students learn the proper error terms for testing factors of a split-plot design via "expected…

Adding uncertainty to forest inventory plot locations: effects on analyses using geospatial data

Treesearch

Alexia A. Sabor; Volker C. Radeloff; Ronald E. McRoberts; Murray Clayton; Susan I. Stewart

2007-01-01

The Forest Inventory and Analysis (FIA) program of the USDA Forest Service alters plot locations before releasing data to the public to ensure landowner confidentiality and sample integrity, but using data with altered plot locations in conjunction with other spatially explicit data layers produces analytical results with unknown amounts of error. We calculated the...

magicaxis: Pretty scientific plotting with minor-tick and log minor-tick support

NASA Astrophysics Data System (ADS)

Robotham, Aaron S. G.

2016-04-01

The R suite magicaxis makes useful and pretty plots for scientific plotting and includes functions for base plotting, with particular emphasis on pretty axis labelling in a number of circumstances that are often used in scientific plotting. It also includes functions for generating images and contours that reflect the 2D quantile levels of the data designed particularly for output of MCMC posteriors where visualizing the location of the 68% and 95% 2D quantiles for covariant parameters is a necessary part of the post MCMC analysis, can generate low and high error bars, and allows clipping of values, rejection of bad values, and log stretching.

Evaluation of a Biostimulant (Pepton) Based in Enzymatic Hydrolyzed Animal Protein in Comparison to Seaweed Extracts on Root Development, Vegetative Growth, Flowering, and Yield of Gold Cherry Tomatoes Grown under Low Stress Ambient Field Conditions

PubMed Central

Polo, Javier; Mata, Pedro

2018-01-01

The objectives of this experiment were to determine the effects of different application rates of an enzyme hydrolyzed animal protein biostimulant (Pepton) compared to a standard application rate of a biostimulant derived from seaweed extract (Acadian) on plant growth parameters and yield of gold cherry tomatoes (Solanum lycopersicum L.). Biostimulant treatments were applied starting at 15 days after transplant and every 2 weeks thereafter for a total of 5 applications. One treatment group received no biostimulant (Control). Three treatment groups (Pepton-2, Pepton-3, Pepton-4) received Pepton at different application rates equivalent to 2, 3, or 4 kg/ha applied by foliar (first 2 applications) and by irrigation (last 3 applications). Another treatment group (Acadian) received Acadian at 1.5 L/ha by irrigation for all five applications. All groups received the regular fertilizer application for this crop at transplantation, flowering, and fruiting periods. There were four plots per treatment group. Each plot had a surface area of 21 m2 that consisted of two rows that were 7 m long and 1.5 m wide. Plant height, stem diameter, distance from head to bouquet flowering, fruit set distance between the entire cluster and cluster flowering fruit set, leaf length, and number of leaves per plant was recorded for 20 plants (5 plants per plot) at 56 and 61 days after the first application. Root length and diameter of cherry tomatoes were determined at harvest from 20 randomly selected plants. Harvesting yield per plot was registered and production per hectare was calculated. Both biostimulants improved (P < 0.05) all vegetative parameters compared with the control group. There was a positive linear (P < 0.001) effect of Pepton application rate for all parameters. The calculated yield was 7.8 and 1 Ton/ha greater that represent 27 and 2.9% higher production for Pepton applied at 4 kg/ha compared to the control and to Acadian, respectively. In conclusion, Pepton was effective improving yield of gold cherry tomatoes under the low stress ambient growing conditions of this experiment. Probably short-chain peptides present in Pepton are involved in endogenous hormones and metabolic mediators that could explain the results obtained in this study. PMID:29403513

Graphical augmentations to the funnel plot assess the impact of additional evidence on a meta-analysis.

PubMed

Langan, Dean; Higgins, Julian P T; Gregory, Walter; Sutton, Alexander J

2012-05-01

We aim to illustrate the potential impact of a new study on a meta-analysis, which gives an indication of the robustness of the meta-analysis. A number of augmentations are proposed to one of the most widely used of graphical displays, the funnel plot. Namely, 1) statistical significance contours, which define regions of the funnel plot in which a new study would have to be located to change the statistical significance of the meta-analysis; and 2) heterogeneity contours, which show how a new study would affect the extent of heterogeneity in a given meta-analysis. Several other features are also described, and the use of multiple features simultaneously is considered. The statistical significance contours suggest that one additional study, no matter how large, may have a very limited impact on the statistical significance of a meta-analysis. The heterogeneity contours illustrate that one outlying study can increase the level of heterogeneity dramatically. The additional features of the funnel plot have applications including 1) informing sample size calculations for the design of future studies eligible for inclusion in the meta-analysis; and 2) informing the updating prioritization of a portfolio of meta-analyses such as those prepared by the Cochrane Collaboration. Copyright © 2012 Elsevier Inc. All rights reserved.

Visual Data Analysis for Satellites

NASA Technical Reports Server (NTRS)

Lau, Yee; Bhate, Sachin; Fitzpatrick, Patrick

2008-01-01

The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.

A method for developing design diagrams for ceramic and glass materials using fatigue data

NASA Technical Reports Server (NTRS)

Heslin, T. M.; Magida, M. B.; Forrest, K. A.

1986-01-01

The service lifetime of glass and ceramic materials can be expressed as a plot of time-to-failure versus applied stress whose plot is parametric in percent probability of failure. This type of plot is called a design diagram. Confidence interval estimates for such plots depend on the type of test that is used to generate the data, on assumptions made concerning the statistical distribution of the test results, and on the type of analysis used. This report outlines the development of design diagrams for glass and ceramic materials in engineering terms using static or dynamic fatigue tests, assuming either no particular statistical distribution of test results or a Weibull distribution and using either median value or homologous ratio analysis of the test results.

An investigation of wing buffeting response at subsonic and transonic speeds. Phase 2: F-111A flight data analysis. Volume 2: Plotted power spectra

NASA Technical Reports Server (NTRS)

Benepe, D. B.; Cunningham, A. M., Jr.; Traylor, S., Jr.; Dunmyer, W. D.

1978-01-01

Plotted power spectra for all of the flight points examined during the Phase 2 flight data analysis are presented. Detailed descriptions of the aircraft, the flight instrumentation and the analysis techniques are given. Measured and calculated vibration mode frequencies are also presented to assist in further interpretation of the PSD data.

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.

The provenance of low-calcic black shales

NASA Astrophysics Data System (ADS)

Quinby-Hunt, M. S.; Wilde, P.

1991-04-01

The elemental concentration of sedimentary rocks depends on the varying reactivity of each element as it goes from the source through weathering, deposition, diagenesis, lithification, and even low rank metamorphism. However, non-reactive components of detrital particles ideally are characteristic of the original igneous source and thus are useful in provenance studies. To determine the source of detrital granitic and volcanic components of low-calcic (<1% CaCO3) marine black shales, the concentrations of apparently non-reactive (i.e. unaffected by diagenetic, redox and/or low-rank metamorphic processes) trace elements were examined using standard trace element discrimination diagrams developed for igneous rocks. The chemical data was obtained by neutron activation analyses of about 200 stratigraphically well-documented black shale samples from the Cambrian through the Jurassic. A La-Th-Sc ternary diagram distinguishes among contributions from the upper and bulk continental crust and the oceanic crust (Taylor and McLennan 1985). All the low-calcic black shales cluster within the region of the upper crust. Th-Hf-Co ternary diagrams also are commonly used to distinguish among the upper and bulk continental crust and the oceanic crust (Taylor and McLennan 1985). As Co is redox sensitive in black shale environments, it was necessary to substitute an immobile element (i.e. example Rb) in the diagram. With this substitution of black shales all cluster in the region of the upper continental crust. To determine the provenance of the granitic component (Pearce et al. 1984), plots of Ta vs Yb and Rb vs Yb + Ta shows a cluster at the junction of the boundaries separating the volcanic arc granite (VAG), syn-collision granite (syn-COLG), and within-plate granite (WPG) fields. The majority fall within the VAG field. There are no occurrences of ocean ridge granite (ORG). The minimal contribution of basalts to marine black shales is confirmed by the ternary Wood diagram Th-Hf/3-Ta (Wood et al. 1979). The black shales plot in a cluster in a high Th region outside the various basalt fields, which suggests contribution from the continental crust.

Analysis Tools (AT)

Treesearch

Larry J. Gangi

2006-01-01

The FIREMON Analysis Tools program is designed to let the user perform grouped or ungrouped summary calculations of single measurement plot data, or statistical comparisons of grouped or ungrouped plot data taken at different sampling periods. The program allows the user to create reports and graphs, save and print them, or cut and paste them into a word processor....

Omitted Variable Sensitivity Analysis with the Annotated Love Plot

ERIC Educational Resources Information Center

Hansen, Ben B.; Fredrickson, Mark M.

2014-01-01

The goal of this research is to make sensitivity analysis accessible not only to empirical researchers but also to the various stakeholders for whom educational evaluations are conducted. To do this it derives anchors for the omitted variable (OV)-program participation association intrinsically, using the Love plot to present a wide range of…

Technologies for Teaching and Learning about Box Plots and Statistical Analysis

ERIC Educational Resources Information Center

Forster, Patricia A.

2007-01-01

This paper analyses technology-based instruction on data-analysis with box plots. Examples of instruction taken from the research literature inform a study of two classes of 17 year-old students (upper secondary) in which the mathematical relationships that their teachers targeted are distinguished as being, or not being, relevant to statistical…

Importance of the Correlation between Width and Length in the Shape Analysis of Nanorods: Use of a 2D Size Plot To Probe Such a Correlation.

PubMed

Zhao, Zhihua; Zheng, Zhiqin; Roux, Clément; Delmas, Céline; Marty, Jean-Daniel; Kahn, Myrtil L; Mingotaud, Christophe

2016-08-22

Analysis of nanoparticle size through a simple 2D plot is proposed in order to extract the correlation between length and width in a collection or a mixture of anisotropic particles. Compared to the usual statistics on the length associated with a second and independent statistical analysis of the width, this simple plot easily points out the various types of nanoparticles and their (an)isotropy. For each class of nano-objects, the relationship between width and length (i.e., the strong or weak correlations between these two parameters) may suggest information concerning the nucleation/growth processes. It allows one to follow the effect on the shape and size distribution of physical or chemical processes such as simple ripening. Various electron microscopy pictures from the literature or from the authors' own syntheses are used as examples to demonstrate the efficiency and simplicity of the proposed 2D plot combined with a multivariate analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

OpenStereo: Open Source, Cross-Platform Software for Structural Geology Analysis

NASA Astrophysics Data System (ADS)

Grohmann, C. H.; Campanha, G. A.

2010-12-01

Free and open source software (FOSS) are increasingly seen as synonyms of innovation and progress. Freedom to run, copy, distribute, study, change and improve the software (through access to the source code) assure a high level of positive feedback between users and developers, which results in stable, secure and constantly updated systems. Several software packages for structural geology analysis are available to the user, with commercial licenses or that can be downloaded at no cost from the Internet. Some provide basic tools of stereographic projections such as plotting poles, great circles, density contouring, eigenvector analysis, data rotation etc, while others perform more specific tasks, such as paleostress or geotechnical/rock stability analysis. This variety also means a wide range of data formating for input, Graphical User Interface (GUI) design and graphic export format. The majority of packages is built for MS-Windows and even though there are packages for the UNIX-based MacOS, there aren't native packages for *nix (UNIX, Linux, BSD etc) Operating Systems (OS), forcing the users to run these programs with emulators or virtual machines. Those limitations lead us to develop OpenStereo, an open source, cross-platform software for stereographic projections and structural geology. The software is written in Python, a high-level, cross-platform programming language and the GUI is designed with wxPython, which provide a consistent look regardless the OS. Numeric operations (like matrix and linear algebra) are performed with the Numpy module and all graphic capabilities are provided by the Matplolib library, including on-screen plotting and graphic exporting to common desktop formats (emf, eps, ps, pdf, png, svg). Data input is done with simple ASCII text files, with values of dip direction and dip/plunge separated by spaces, tabs or commas. The user can open multiple file at the same time (or the same file more than once), and overlay different elements of each dataset (poles, great circles etc). The GUI shows the opened files in a tree structure, similar to “layers” of many illustration software, where the vertical order of the files in the tree reflects the drawing order of the selected elements. At this stage, the software performs plotting operations of poles to planes, lineations, great circles, density contours and rose diagrams. A set of statistics is calculated for each file and its eigenvalues and eigenvectors are used to suggest if the data is clustered about a mean value or distributed along a girdle. Modified Flinn, Triangular and histograms plots are also available. Next step of development will focus on tools as merging and rotation of datasets, possibility to save 'projects' and paleostress analysis. In its current state, OpenStereo requires Python, wxPython, Numpy and Matplotlib installed in the system. We recommend installing PythonXY or the Enthought Python Distribution on MS-Windows and MacOS machines, since all dependencies are provided. Most Linux distributions provide an easy way to install all dependencies through software repositories. OpenStereo is released under the GNU General Public License. Programmers willing to contribute are encouraged to contact the authors directly. FAPESP Grant #09/17675-5

Amplitude Analysis of the Decay $$D_s^+ \\to \\pi^+ \\pi^- \\pi^+$$ in the Experiment E831/FOCUS (in Portuguese)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schilithz, Anderson Correa; /Rio de Janeiro, CBPF

We present in this thesis the Dalitz Plot analysis of the D{sub s}{sup +} {yields} {pi}{sup +}{pi}{sup -}{pi}{sup +} decay, with the data of the E831/FOCUS, that took data in 1996 and 1997. The masses and widhts of f{sub 0}(980) and f{sub 0}(1370) are free parametres of the fit on Dalitz Plot, objectiving to study in detail these resonances. After this analysis we present the Spectator Model study on the S wave in this decay. For this study we used the formalism developed by M. Svec [2] for scattering. We present the comparison between the Isobar Model, frequently used inmore » Dalitz Plot analysis, and this formalism.« less

Alternative states of a semiarid grassland ecosystem: implications for ecosystem services

USGS Publications Warehouse

Miller, Mark E.; Belote, R. Travis; Bowker, Matthew A.; Garman, Steven L.

2011-01-01

Ecosystems can shift between alternative states characterized by persistent differences in structure, function, and capacity to provide ecosystem services valued by society. We examined empirical evidence for alternative states in a semiarid grassland ecosystem where topographic complexity and contrasting management regimes have led to spatial variations in levels of livestock grazing. Using an inventory data set, we found that plots (n = 72) cluster into three groups corresponding to generalized alternative states identified in an a priori conceptual model. One cluster (biocrust) is notable for high coverage of a biological soil crust functional group in addition to vascular plants. Another (grass-bare) lacks biological crust but retains perennial grasses at levels similar to the biocrust cluster. A third (annualized-bare) is dominated by invasive annual plants. Occurrence of grass-bare and annualized-bare conditions in areas where livestock have been excluded for over 30 years demonstrates the persistence of these states. Significant differences among all three clusters were found for percent bare ground, percent total live cover, and functional group richness. Using data for vegetation structure and soil erodibility, we also found large among-cluster differences in average levels of dust emissions predicted by a wind-erosion model. Predicted emissions were highest for the annualized-bare cluster and lowest for the biocrust cluster, which was characterized by zero or minimal emissions even under conditions of extreme wind. Results illustrate potential trade-offs among ecosystem services including livestock production, soil retention, carbon storage, and biodiversity conservation. Improved understanding of these trade-offs may assist ecosystem managers when evaluating alternative management strategies.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Automated mesostructural analyses using GIS, Beta test: Paleozoic structures from the New Jersey Great Valley region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herman, G.C.; French, M.A.; Monteverde, D.H.

1993-03-01

An automated method has been developed for representing outcrop data on geologic structures on maps. Using a MS-DOS custom database management system in conjunction with the ARC/INFO Geographic Information System (GIS), trends of geologic structures are plotted with user-specific symbols. The length of structural symbols can be frequency-weighted based on collective values from structural domains. The PC-based data manager is the NJGS Field data Management System (FMS) Version 2.0 which includes sort, output, and analysis functions for structural data input in either azimuth or quadrant form. Program options include lineament sorting, data output to other data management and analysis software,more » and a circular histogram (rose diagram) routine for trend frequency analysis. Trends can be displayed with either half-or full-rose diagrams using either 10[degree] sectors or one degree spikes for strike, trend, or dip azimuth readings. Scalar and vector statistics are both included. For the mesostructural analysis, ASCII files containing the station number, structural trend and inclination, and plot-symbol-length value are downloaded from FMS and uploaded into an ARC/INFO macro which sequentially plots the information. Plots can be generated in conjunction with any complimentary GIS coverage for various types of spatial analyses. Mesostructural plots can be used for regional tectonic analyses, for hydrogeologic analysis of fractured bedrock aquifers, or for ground-truthing data from fracture-trace or lineament analyses.« less

Phylogeography of the sandy beach amphipod Haustorioides japonicus along the Sea of Japan: Paleogeographical signatures of cryptic regional divergences

NASA Astrophysics Data System (ADS)

Takada, Yoshitake; Sakuma, Kay; Fujii, Tetsuo; Kojima, Shigeaki

2018-01-01

Recent findings of genetic breaks within apparently continuous marine populations challenge the traditional vicariance paradigm in population genetics. Such "invisible" boundaries are sometimes associated with potential geographic barriers that have forced divergence of an ancestral population, habitat discontinuities, biogeographic disjunctions due to environmental gradients, or a combination of these factors. To explore the factors that influence the genetic population structure of apparently continuous populations along the Sea of Japan, the sandy beach amphipod Haustorioides japonicus was examined. We sampled a total of 300 individuals of H. japonicus from the coast of Japan, and obtained partial sequences of the mitochondrial COI gene. The sequences from 19 local populations were clustered into five groups (Northwestern Pacific, Northern, Central, Southern Sea of Japan, and East China Sea) based on a spatial genetic mixture analysis and a minimum-spanning network. AMOVA and pairwise Fst tests further supported the significant divergence of the five groups. Phylogenetic analysis revealed the relationship among the haplotypes of H. japonicus and outgroups, which inferred the northward range expansion of the species. A relaxed molecular-clock Bayesian analysis inferred the early-to middle-Pleistocene divergence of the populations. Among the five clusters, the Central Sea of Japan showed the highest values for genetic diversity indices indicating the existence of a relatively stable and large population there. The hypothesis is also supported by Bayesian Skyline Plots that showed sudden population expansion for all the clusters except for Central Sea of Japan. The present study shows genetic boundaries between the Sea of Japan and the neighboring seas, probably due to geographic isolation during the Pleistocene glacial periods. We further found divergence between the populations along the apparently continuous coast of the Sea of Japan. Historical changes in the geographic range of H. japonicus in relation to sandy beach habitat availability, account for the genetic breaks among the three populations in the Sea of Japan. The present results infer that the past geographic events influenced the population formation of H. japonicus.

A technique for identifying treatment opportunities from western Oregon and Washington forest survey plots.

Treesearch

Colin D. MacLean

1980-01-01

Identification of opportunities for silvicultural treatment from inventory data is an important objective of Renewable Resources Evaluation in the Pacific Northwest. This paper describes the field plot design and data analysis procedure used by what used to be known as Forest Survey to determine the treatment opportunity associated with each inventory plot in western...

Field methods and data processing techniques associated with mapped inventory plots

Treesearch

William A. Bechtold; Stanley J. Zarnoch

1999-01-01

The U.S. Forest Inventory and Analysis (FIA) and Forest Health Monitoring (FHM) programs utilize a fixed-area mapped-plot design as the national standard for extensive forest inventories. The mapped-plot design is explained, as well as the rationale for its selection as the national standard. Ratio-of-means estimators am presented as a method to process data from...

Access and Use of FIA Data Through FIA Spatial Data Services

Treesearch

Elizabeth LaPoint

2005-01-01

Forest Inventory and Analysis (FIA) Spatial Data Services (SDS) was established in May 2002 to facilitate outside access to FIA data and allow use of georeferenced plot data while protecting the confidentiality of plot locations. Modification of the Food Security Act of 1985 legislated the protection of information on plot location and ownership. Penalties were put in...

Development of carbon response trajectories using FIA plot data and FVS growth simulator: challenges of a large scale simulation project

Treesearch

James B. McCarter; Sean Healey

2015-01-01

The Forest Carbon Management Framework (ForCaMF) integrates Forest Inventory and Analysis (FIA) plot inventory data, disturbance histories, and carbon response trajectories to develop estimates of disturbance and management effects on carbon pools for the National Forest System. All appropriate FIA inventory plots are simulated using the Forest Vegetation Simulator (...

Accuracy assessment of the vegetation continuous field tree cover product using 3954 ground plots in the southwestern USA

Treesearch

M. A. White; J. D. Shaw; R. D. Ramsey

2005-01-01

An accuracy assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous field (VCF) tree cover product using two independent ground-based tree cover databases was conducted. Ground data included 1176 Forest Inventory and Analysis (FIA) plots for Arizona and 2778 Southwest Regional GAP (SWReGAP) plots for Utah and western Colorado....

Comparative study of Poincaré plot analysis using short electroencephalogram signals during anaesthesia with spectral edge frequency 95 and bispectral index.

PubMed

Hayashi, K; Yamada, T; Sawa, T

2015-03-01

The return or Poincaré plot is a non-linear analytical approach in a two-dimensional plane, where a timed signal is plotted against itself after a time delay. Its scatter pattern reflects the randomness and variability in the signals. Quantification of a Poincaré plot of the electroencephalogram has potential to determine anaesthesia depth. We quantified the degree of dispersion (i.e. standard deviation, SD) along the diagonal line of the electroencephalogram-Poincaré plot (named as SD1/SD2), and compared SD1/SD2 values with spectral edge frequency 95 (SEF95) and bispectral index values. The regression analysis showed a tight linear regression equation with a coefficient of determination (R(2) ) value of 0.904 (p < 0.0001) between the Poincaré index (SD1/SD2) and SEF95, and a moderate linear regression equation between SD1/SD2 and bispectral index (R(2)  = 0.346, p < 0.0001). Quantification of the Poincaré plot tightly correlates with SEF95, reflecting anaesthesia-dependent changes in electroencephalogram oscillation. © 2014 The Association of Anaesthetists of Great Britain and Ireland.

Newly discovered globular clusters in NGC 147 and NGC 185 from PAndAS

NASA Astrophysics Data System (ADS)

Veljanoski, J.; Ferguson, A. M. N.; Huxor, A. P.; Mackey, A. D.; Fishlock, C. K.; Irwin, M. J.; Tanvir, N.; Chapman, S. C.; Ibata, R. A.; Lewis, G. F.; McConnachie, A.

2013-11-01

Using data from the Pan-Andromeda Archaeological Survey (PAndAS), we have discovered four new globular clusters (GCs) associated with the M31 dwarf elliptical (dE) satellites NGC 147 and NGC 185. Three of these are associated with NGC 147 and one with NGC 185. All lie beyond the main optical boundaries of the galaxies and are the most remote clusters yet known in these systems. Radial velocities derived from low-resolution spectra are used to argue that the GCs are bound to the dwarfs and are not part of the M31 halo population. Combining PAndAS with United Kingdom Infrared Telescope (UKIRT)/WFCAM (Wide-Field Camera) data, we present the first homogeneous optical and near-IR photometry for the entire GC systems of these dEs. Colour-colour plots and published colour-metallicity relations are employed to constrain GC ages and metallicities. It is demonstrated that the clusters are in general metal poor ([Fe/H] < -1.25 dex), while the ages are more difficult to constrain. The mean (V - I)0 colours of the two GC systems are very similar to those of the GC systems of dEs in the Virgo and Fornax clusters, as well as the extended halo GC population in M31. The new clusters bring the GC-specific frequency (SN) to ˜9 in NGC 147 and ˜5 in NGC 185, consistent with values found for dEs of similar luminosity residing in a range of environments.

Comparison of Precision of Biomass Estimates in Regional Field Sample Surveys and Airborne LiDAR-Assisted Surveys in Hedmark County, Norway

NASA Technical Reports Server (NTRS)

Naesset, Erik; Gobakken, Terje; Bollandsas, Ole Martin; Gregoire, Timothy G.; Nelson, Ross; Stahl, Goeran

2013-01-01

Airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool to provide auxiliary data for sample surveys aiming at estimation of above-ground tree biomass (AGB), with potential applications in REDD forest monitoring. For larger geographical regions such as counties, states or nations, it is not feasible to collect airborne LiDAR data continuously ("wall-to-wall") over the entire area of interest. Two-stage cluster survey designs have therefore been demonstrated by which LiDAR data are collected along selected individual flight-lines treated as clusters and with ground plots sampled along these LiDAR swaths. Recently, analytical AGB estimators and associated variance estimators that quantify the sampling variability have been proposed. Empirical studies employing these estimators have shown a seemingly equal or even larger uncertainty of the AGB estimates obtained with extensive use of LiDAR data to support the estimation as compared to pure field-based estimates employing estimators appropriate under simple random sampling (SRS). However, comparison of uncertainty estimates under SRS and sophisticated two-stage designs is complicated by large differences in the designs and assumptions. In this study, probability-based principles to estimation and inference were followed. We assumed designs of a field sample and a LiDAR-assisted survey of Hedmark County (HC) (27,390 km2), Norway, considered to be more comparable than those assumed in previous studies. The field sample consisted of 659 systematically distributed National Forest Inventory (NFI) plots and the airborne scanning LiDAR data were collected along 53 parallel flight-lines flown over the NFI plots. We compared AGB estimates based on the field survey only assuming SRS against corresponding estimates assuming two-phase (double) sampling with LiDAR and employing model-assisted estimators. We also compared AGB estimates based on the field survey only assuming two-stage sampling (the NFI plots being grouped in clusters) against corresponding estimates assuming two-stage sampling with the LiDAR and employing model-assisted estimators. For each of the two comparisons, the standard errors of the AGB estimates were consistently lower for the LiDAR-assisted designs. The overall reduction of the standard errors in the LiDAR-assisted estimation was around 40-60% compared to the pure field survey. We conclude that the previously proposed two-stage model-assisted estimators are inappropriate for surveys with unequal lengths of the LiDAR flight-lines and new estimators are needed. Some options for design of LiDAR-assisted sample surveys under REDD are also discussed, which capitalize on the flexibility offered when the field survey is designed as an integrated part of the overall survey design as opposed to previous LiDAR-assisted sample surveys in the boreal and temperate zones which have been restricted by the current design of an existing NFI.

Intelligence Constraints on Terrorist Network Plots

NASA Astrophysics Data System (ADS)

Woo, Gordon

Since 9/11, the western intelligence and law enforcement services have managed to interdict the great majority of planned attacks against their home countries. Network analysis shows that there are important intelligence constraints on the number and complexity of terrorist plots. If two many terrorists are involved in plots at a given time, a tipping point is reached whereby it becomes progressively easier for the dots to be joined and for the conspirators to be arrested, and for the aggregate evidence to secure convictions. Implications of this analysis are presented for the campaign to win hearts and minds.

A Bibliometric Analysis of U.S.-Based Research on the Behavioral Risk Factor Surveillance System

PubMed Central

Khalil, George M.; Gotway Crawford, Carol A.

2017-01-01

Background Since Alan Pritchard defined bibliometrics as “the application of statistical methods to media of communication” in 1969, bibliometric analyses have become widespread. To date, however, bibliometrics has not been used to analyze publications related to the U.S. Behavioral Risk Factor Surveillance System (BRFSS). Purpose To determine the most frequently cited BRFSS-related topical areas, institutions, and journals. Methods A search of the Web of Knowledge database in 2013 identified U.S.-published studies related to BRFSS, from its start in 1984 through 2012. Search terms were BRFSS, Behavioral Risk Factor Surveillance System, or Behavioral Risk Survey. The resulting 1,387 articles were analyzed descriptively and produced data for VOSviewer, a computer program that plotted a relevance distance–based map and clustered keywords from text in titles and abstracts. Results Topics, journals, and publishing institutions ranged widely. Most research was clustered by content area, such as cancer screening, access to care, heart health, and quality of life. The American Journal of Preventive Medicine and American Journal of Public Health published the most BRFSS-related papers (95 and 70, respectively). Conclusions Bibliometrics can help identify the most frequently published BRFSS-related topics, publishing journals, and publishing institutions. BRFSS data are widely used, particularly by CDC and academic institutions such as the University of Washington and other universities hosting top-ranked schools of public health. Bibliometric analysis and mapping provides an innovative way of quantifying and visualizing the plethora of research conducted using BRFSS data and summarizing the contribution of this surveillance system to public health. PMID:25442231

A comparative study of mid-infrared diffuse reflection (DR) and attenuated total reflection (ATR) spectroscopy for the detection of fungal infection on RWA2-corn.

PubMed

Kos, Gregor; Krska, Rudolf; Lohninger, Hans; Griffiths, Peter R

2004-01-01

An investigation into the rapid detection of mycotoxin-producing fungi on corn by two mid-infrared spectroscopic techniques was undertaken. Corn samples from a single genotype (RWA2, blanks, and contaminated with Fusarium graminearum) were ground, sieved and, after appropriate sample preparation, subjected to mid-infrared spectroscopy using two different accessories (diffuse reflection and attenuated total reflection). The measured spectra were evaluated with principal component analysis (PCA) and the blank and contaminated samples were classified by cluster analysis. Reference data for fungal metabolites were obtained with conventional methods. After extraction and clean-up, each sample was analyzed for the toxin deoxynivalenol (DON) by gas chromatography with electron capture detection (GC-ECD) and ergosterol (a parameter for the total fungal biomass) by high-performance liquid chromatography with diode array detection (HPLC-DAD). The concentration ranges for contaminated samples were 880-3600 microg/kg for ergosterol and 300-2600 microg/kg for DON. Classification efficiency was 100% for ATR spectra. DR spectra did not show as obvious a clustering of contaminated and blank samples. Results and trends were also observed in single spectra plots. Quantification using a PLS1 regression algorithm showed good correlation with DON reference data, but a rather high standard error of prediction (SEP) with 600 microg/kg (DR) and 490 microg/kg (ATR), respectively, for ergosterol. Comparing measurement procedures and results showed advantages for the ATR technique, mainly owing to its ease of use and the easier interpretation of results that were better with respect to classification and quantification.

Grassland degradation caused by tourism activities in Hulunbuir, Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Le, C.; Ikazaki, K.; Siriguleng; Kadono, A.; Kosaki, T.

2014-02-01

The recent increase in the number of tourists has raised serious concerns about grassland degradation by tourism activities in Inner Mongolia. Thus, we evaluated the effects of tourism activities on the vegetation and soil in Hulunbuir grassland. We identified all the plant species, measured the number and height of plant and plant coverage rate, and calculated species diversity, estimated above-ground biomass in use plot and non-use plot. We also measured soil hardness, and collected soil samples for physical and chemical analysis in both plots. The obtained results were as follows: a) the height of the dominant plants, plant coverage rate, species diversity, and above-ground biomass were significantly lower in use plot than in non-use plot, b) Carex duriuscula C.A.Mey., indicator plant for soil degradation, was dominant in use plot, c) soil hardness was significantly higher in use plot than in non-use plot, and spatial dependence of soil hardness was only found in the use plot, d) CEC, TC, TN and pH in the topsoil were significantly lower in use plot than non-use plot. On the basis of the results, we concluded that the tourism activities can be another major cause of the grassland degradation in Inner Mongolia.

Plant functional traits and diversity in sand dune ecosystems across different biogeographic regions

NASA Astrophysics Data System (ADS)

Mahdavi, P.; Bergmeier, E.

2016-07-01

Plant species of a functional group respond similarly to environmental pressures and may be expected to act similarly on ecosystem processes and habitat properties. However, feasibility and applicability of functional groups in ecosystems across very different climatic regions have not yet been studied. In our approach we specified the functional groups in sand dune ecosystems of the Mediterranean, Hyrcanian and Irano-Turanian phytogeographic regions. We examined whether functional groups are more influenced by region or rather by habitat characteristics, and identified trait syndromes associated with common habitat types in sand dunes (mobile dunes, stabilized dunes, salt marshes, semi-wet sands, disturbed habitats). A database of 14 traits, 309 species and 314 relevés was examined and trait-species, trait-plot and species-plot matrices were built. Cluster analysis revealed similar plant functional groups in sand dune ecosystems across regions of very different species composition and climate. Specifically, our study showed that plant traits in sand dune ecosystems are grouped reflecting habitat affiliation rather than region and species pool. Environmental factors and constraints such as sand mobility, soil salinity, water availability, nutrient status and disturbance are more important for the occurrence and distribution of plant functional groups than regional belonging. Each habitat is shown to be equipped with specific functional groups and can be described by specific sets of traits. In restoration ecology the completeness of functional groups and traits in a site may serve as a guideline for maintaining or restoring the habitat.

Classification of alloys using laser induced breakdown spectroscopy with principle component analysis

NASA Astrophysics Data System (ADS)

Syuhada Mangsor, Aneez; Haider Rizvi, Zuhaib; Chaudhary, Kashif; Safwan Aziz, Muhammad

2018-05-01

The study of atomic spectroscopy has contributed to a wide range of scientific applications. In principle, laser induced breakdown spectroscopy (LIBS) method has been used to analyse various types of matter regardless of its physical state, either it is solid, liquid or gas because all elements emit light of characteristic frequencies when it is excited to sufficiently high energy. The aim of this work was to analyse the signature spectrums of each element contained in three different types of samples. Metal alloys of Aluminium, Titanium and Brass with the purities of 75%, 80%, 85%, 90% and 95% were used as the manipulated variable and their LIBS spectra were recorded. The characteristic emission lines of main elements were identified from the spectra as well as its corresponding contents. Principal component analysis (PCA) was carried out using the data from LIBS spectra. Three obvious clusters were observed in 3-dimensional PCA plot which corresponding to the different group of alloys. Findings from this study showed that LIBS technology with the help of principle component analysis could conduct the variety discrimination of alloys demonstrating the capability of LIBS-PCA method in field of spectro-analysis. Thus, LIBS-PCA method is believed to be an effective method for classifying alloys with different percentage of purifications, which was high-cost and time-consuming before.

Complete genome sequence of a coxsackievirus B3 recombinant isolated from an aseptic meningitis outbreak in eastern China.

PubMed

Zhang, Wenqiang; Lin, Xiaojuan; Jiang, Ping; Tao, Zexin; Liu, Xiaolin; Ji, Feng; Wang, Tongzhan; Wang, Suting; Lv, Hui; Xu, Aiqiang; Wang, Haiyan

2016-08-01

Coxsackievirus B3 (CV-B3) has frequently been associated with aseptic meningitis outbreaks in China. To identify sequence motifs related to aseptic meningitis and to construct an infectious clone, the genome sequence of 08TC170, a representative strain isolated from cerebrospinal fluid (CSF) samples from an outbreak in Shandong in 2008, was determined, and the coding regions for P1-P3 and VP1 were aligned. The first 21 and last 20 residues were "TTAAAACAGCCTGTGGGTTGT" and "ATTCTCCGCATTCGGTGCGG", respectively. The whole genome consisted of 7401 nucleotides, sharing 80.8 % identity with the prototype strain Nancy and low sequence similarity with members of clusters A-C. In contrast, 08TC170 showed high sequence similarity to members of cluster D. An especially high level of sequence identity (≥97.7 %) was found within a branch constituted by 08TC170 and four Chinese strains that clustered together in all of the P1-P3 phylogenic trees. In addition, 08TC170 also possessed a close relationship to the Hong Kong strain 26362/08 in VP1. Similarity plot analysis showed that 08TC170 was most similar to the Chinese CV-B3 strain SSM in P1 and the partial P2 coding region but to the CV-B5 or E-6 strain in 2C and following regions. A T277A mutation was found in 08TC170 and other strains isolated in 2008-2010, but not in strains isolated before 2008, which had high sequence similarity and formed the cluster A277. The results suggested that 08TC170 was the product of both intertypic recombination and point mutation, whose effects on viral neurovirulence will be investigated in a further study. The high homology between 08TC170 and other strains revealed their co-circulation in mainland China and Hong Kong and indicates that further surveillance is needed.

Using Data Analysis to Explore Class Enrollment.

ERIC Educational Resources Information Center

Davis, Gretchen

1990-01-01

Describes classroom activities and shows that statistics is a practical tool for solving real problems. Presents a histogram, a stem plot, and a box plot to compare data involving class enrollments. (YP)

The WHISPER Relaxation Sounder and the CLUSTER Active Archive

NASA Astrophysics Data System (ADS)

Trotignon, J. G.; Décréau, P. M. E.; Rauch, J. L.; Vallières, X.; Rochel, A.; Kougblénou, S.; Lointier, G.; Facskó, G.; Canu, P.; Darrouzet, F.; Masson, A.

The Waves of HIgh frequency and Sounder for Probing of Electron density by Relaxation (WHISPER) instrument is part of the Wave Experiment Consortium (WEC) of the CLUSTER mission. With the help of the long double sphere antennae of the Electric Field and Wave (EFW) instrument and the Digital Wave Processor (DWP), it delivers active (sounding) and natural (transmitter off) electric field spectra, respectively from 4 to 82 kHz, and from 2 to 80 kHz. These frequency ranges have been chosen to include the electron plasma frequency, which is closely related to the total electron density, in most of the regions encountered by the CLUSTER spacecraft. Presented here is an overview of the WHISPER data products available in the CLUSTER Active Archive (CAA). The instrument and its performance are first recalled. The way the WHISPER products are obtained is then described, with particular attention being paid to the density determination. Both sounding and natural measurements are commonly used in this process, which depends on the ambient plasma regime. This is illustrated using drawings similar to the Bryant plots commonly used in the CLUSTER master science plan. These give a clear overview of typical density values and the parts of the orbits where they are obtained. More information on the applied software or on the quality/reliability of the density determination can also be highlighted.

Super Star Cluster Velocity Dispersions and Virial Masses in the M82 Nuclear Starburst

NASA Astrophysics Data System (ADS)

McCrady, Nate; Graham, James R.

2007-07-01

We use high-resolution near-infrared spectroscopy from Keck Observatory to measure the stellar velocity dispersions of 19 super star clusters (SSCs) in the nuclear starburst of M82. The clusters have ages on the order of 10 Myr, which is many times longer than the crossing times implied by their velocity dispersions and radii. We therefore apply the virial theorem to derive the kinematic mass for 15 of the SSCs. The SSCs have masses of 2×105 to 4×106 Msolar, with a total population mass of 1.4×107 Msolar. Comparison of the loci of the young M82 SSCs and old Milky Way globular clusters in a plot of radius versus velocity dispersion suggests that the SSCs are a population of potential globular clusters. We present the mass function for the SSCs and find a power-law fit with an index of γ=-1.91+/-0.06. This result is nearly identical to the mass function of young SSCs in the Antennae galaxies. Based on observations made at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

A CN Band Survey of Red Giants in the Globular Cluster M53

NASA Astrophysics Data System (ADS)

Martell, S. L.; Smith, G. H.

2004-12-01

We investigate the star-to-star variations in λ 3883 CN bandstrength among red giant stars in the low-metallicity globular cluster M53 ([Fe/H] = --2.0). Our data were taken with the Kast spectrograph on the 3-meter Shane telescope at Lick Observatory in April 2001. Star-to-star variations in CN bandstrength are common in intermediate- and high-metallicity globular clusters ([Fe/H] ≥ --1.6). Our data were obtained to test whether that variation will also be present in a low-metallicity globular cluster, or whether it will be suppressed by the overall lack of metals in the stars. Our preliminary result is that the λ 3883 CN band is weak in our program stars, which span the brightest magnitude of the red giant branch. On visual inspection, the M53 giants appear to be similar in their CN bandstrength to the four CN-weak giants in NGC 6752 whose average spectrum is plotted in Fig. 4 of Norris et al. (1981, ApJ, 244, 205). This work is planned to form part of a larger study of the metallicity dependence of CN bandstrength and carbon abundance behavior on the upper giant branch of globular clusters. This work is supported by NSF grant AST 00-98453 and by an award from the ARCS foundation, Northern California Chapter.

Visualizing the deep end of sound: plotting multi-parameter results from infrasound data analysis

NASA Astrophysics Data System (ADS)

Perttu, A. B.; Taisne, B.

2016-12-01

Infrasound is sound below the threshold of human hearing: approximately 20 Hz. The field of infrasound research, like other waveform based fields relies on several standard processing methods and data visualizations, including waveform plots and spectrograms. The installation of the International Monitoring System (IMS) global network of infrasound arrays, contributed to the resurgence of infrasound research. Array processing is an important method used in infrasound research, however, this method produces data sets with a large number of parameters, and requires innovative plotting techniques. The goal in designing new figures is to be able to present easily comprehendible, and information-rich plots by careful selection of data density and plotting methods.

Parallel line analysis: multifunctional software for the biomedical sciences

NASA Technical Reports Server (NTRS)

Swank, P. R.; Lewis, M. L.; Damron, K. L.; Morrison, D. R.

1990-01-01

An easy to use, interactive FORTRAN program for analyzing the results of parallel line assays is described. The program is menu driven and consists of five major components: data entry, data editing, manual analysis, manual plotting, and automatic analysis and plotting. Data can be entered from the terminal or from previously created data files. The data editing portion of the program is used to inspect and modify data and to statistically identify outliers. The manual analysis component is used to test the assumptions necessary for parallel line assays using analysis of covariance techniques and to determine potency ratios with confidence limits. The manual plotting component provides a graphic display of the data on the terminal screen or on a standard line printer. The automatic portion runs through multiple analyses without operator input. Data may be saved in a special file to expedite input at a future time.

Spatial Distribution of Taenia solium Porcine Cysticercosis within a Rural Area of Mexico

PubMed Central

Morales, Julio; Martínez, José Juan; Rosetti, Marcos; Fleury, Agnes; Maza, Victor; Hernandez, Marisela; Villalobos, Nelly; Fragoso, Gladis; de Aluja, Aline S.; Larralde, Carlos; Sciutto, Edda

2008-01-01

Cysticercosis is caused by Taenia solium, a parasitic disease that affects humans and rurally bred pigs in developing countries. The cysticercus may localize in the central nervous system of the human, causing neurocysticercosis, the most severe and frequent form of the disease. There appears to be an association between the prevalence of porcine cysticercosis and domestic pigs that wander freely and have access to human feces. In order to assess whether the risk of cysticercosis infection is clustered or widely dispersed in a limited rural area, a spatial analysis of rural porcine cysticercosis was applied to 13 villages of the Sierra de Huautla in Central Mexico. Clustering of cases in specific households would indicate tapeworm carriers in the vicinity, whereas their dispersal would suggest that the ambulatory habits of both humans and pigs contribute to the spread of cysticercosis. A total of 562 pigs were included in this study (August–December 2003). A global positioning system was employed in order to plot the geographic distribution of both cysticercotic pigs and risk factors for infection within the villages. Prevalence of pig tongue cysticercosis varied significantly in sampled villages (p = 0.003), ranging from 0% to 33.3% and averaging 13.3%. Pigs were clustered in households, but no differences in the clustering of cysticercotic and healthy pigs were found. In contrast, the presence of pigs roaming freely and drinking stagnant water correlated significantly with porcine cysticercosis (p = 0.07), as did the absence of latrines (p = 0.0008). High prevalence of porcine cysticercosis proves that transmission is still quite common in rural Mexico. The lack of significant differentiation in the geographical clustering of healthy and cysticercotic pigs weakens the argument that focal factors (e.g., household location of putative tapeworm carriers) play an important role in increasing the risk of cysticercosis transmission in pigs. Instead, it would appear that other wide-ranging biological, physical, and cultural factors determine the geographic spread of the disease. Extensive geographic dispersal of the risk of cysticercosis makes it imperative that control measures be applied indiscriminately to all pigs and humans living in this endemic area. PMID:18846230

Structure of the San Andreas Fault Zone in the Salton Trough Region of Southern California: A Comparison with San Andreas Fault Structure in the Loma Prieta Area of Central California

NASA Astrophysics Data System (ADS)

Fuis, G. S.; Catchings, R.; Scheirer, D. S.; Goldman, M.; Zhang, E.; Bauer, K.

2016-12-01

The San Andreas fault (SAF) in the northern Salton Trough, or Coachella Valley, in southern California, appears non-vertical and non-planar. In cross section, it consists of a steeply dipping segment (75 deg dip NE) from the surface to 6- to 9-km depth, and a moderately dipping segment below 6- to 9-km depth (50-55 deg dip NE). It also appears to branch upward into a flower-like structure beginning below about 10-km depth. Images of the SAF zone in the Coachella Valley have been obtained from analysis of steep reflections, earthquakes, modeling of potential-field data, and P-wave tomography. Review of seismological and geodetic research on the 1989 M 6.9 Loma Prieta earthquake, in central California (e.g., U.S. Geological Survey Professional Paper 1550), shows several features of SAF zone structure similar to those seen in the northern Salton Trough. Aftershocks in the Loma Prieta epicentral area form two chief clusters, a tabular zone extending from 18- to 9-km depth and a complex cluster above 5-km depth. The deeper cluster has been interpreted to surround the chief rupture plane, which dips 65-70 deg SW. When double-difference earthquake locations are plotted, the shallower cluster contains tabular subclusters that appear to connect the main rupture with the surface traces of the Sargent and Berrocal faults. In addition, a diffuse cluster may surround a steep to vertical fault connecting the main rupture to the surface trace of the SAF. These interpreted fault connections from the main rupture to surface fault traces appear to define a flower-like structure, not unlike that seen above the moderately dipping segment of the SAF in the Coachella Valley. But importantly, the SAF, interpreted here to include the main rupture plane, appears segmented, as in the Coachella Valley, with a moderately dipping segment below 9-km depth and a steep to vertical segment above that depth. We hope to clarify fault-zone structure in the Loma Prieta area by reanalyzing active-source data collected after the earthquake for steep reflections.

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

A statistical data analysis and plotting program for cloud microphysics experiments

NASA Technical Reports Server (NTRS)

Jordan, A. J.

1981-01-01

The analysis software developed for atmospheric cloud microphysics experiments conducted in the laboratory as well as aboard a KC-135 aircraft is described. A group of four programs was developed and implemented on a Hewlett Packard 1000 series F minicomputer running under HP's RTE-IVB operating system. The programs control and read data from a MEMODYNE Model 3765-8BV cassette recorder, format the data on the Hewlett Packard disk subsystem, and generate statistical data (mean, variance, standard deviation) and voltage and engineering unit plots on a user selected plotting device. The programs are written in HP FORTRAN IV and HP ASSEMBLY Language with the graphics software using the HP 1000 Graphics. The supported plotting devices are the HP 2647A graphics terminal, the HP 9872B four color pen plotter, and the HP 2608A matrix line printer.

Metaplot: a novel stata graph for assessing heterogeneity at a glance.

PubMed

Poorolajal, J; Mahmoodi, M; Majdzadeh, R; Fotouhi, A

2010-01-01

Heterogeneity is usually a major concern in meta-analysis. Although there are some statistical approaches for assessing variability across studies, here we present a new approach to heterogeneity using "MetaPlot" that investigate the influence of a single study on the overall heterogeneity. MetaPlot is a two-way (x, y) graph, which can be considered as a complementary graphical approach for testing heterogeneity. This method shows graphically as well as numerically the results of an influence analysis, in which Higgins' I(2) statistic with 95% (Confidence interval) CI are computed omitting one study in each turn and then are plotted against reciprocal of standard error (1/SE) or "precision". In this graph, "1/SE" lies on x axis and "I(2) results" lies on y axe. Having a first glance at MetaPlot, one can predict to what extent omission of a single study may influence the overall heterogeneity. The precision on x-axis enables us to distinguish the size of each trial. The graph describes I(2) statistic with 95% CI graphically as well as numerically in one view for prompt comparison. It is possible to implement MetaPlot for meta-analysis of different types of outcome data and summary measures. This method presents a simple graphical approach to identify an outlier and its effect on overall heterogeneity at a glance. We wish to suggest MetaPlot to Stata experts to prepare its module for the software.

Forest Inventory and Analysis and Forest Health Monitoring: Piecing the Quilt

Treesearch

Joseph M. McCollum; Jamie K. Cochran

2005-01-01

Against the backdrop of a discussion about patchwork quilt assembly, the authors present background information on global grids. They show how to compose hexagons, an important task in systematically developing a subset of Forest Health Monitoring (FHM) Program plots from Forest Inventory and Analysis (FIA) plots. Finally, they outline the FHM and FIA grids, along with...

Graphical and Numerical Descriptive Analysis: Exploratory Tools Applied to Vietnamese Data

ERIC Educational Resources Information Center

Haughton, Dominique; Phong, Nguyen

2004-01-01

This case study covers several exploratory data analysis ideas, the histogram and boxplot, kernel density estimates, the recently introduced bagplot--a two-dimensional extension of the boxplot--as well as the violin plot, which combines a boxplot with a density shape plot. We apply these ideas and demonstrate how to interpret the output from these…

South Carolina, 2010 forest inventory and analysis factsheet

Treesearch

Roger C. Conner

2011-01-01

The Forest Inventory and Analysis (FIA) Program implemented a nationally consistent annual inventory system in 1998. Under the new design, one-fifth of all inventory plots in South Carolina are visited each year. The southern FIA unit, working cooperatively with South Carolina Forestry Commission crews, established the State’s initial annual inventory plots during the...

Path Analysis and Residual Plotting as Methods of Environmental Scanning in Higher Education: An Illustration with Applications and Enrollments.

ERIC Educational Resources Information Center

Morcol, Goktug; McLaughlin, Gerald W.

1990-01-01

The study proposes using path analysis and residual plotting as methods supporting environmental scanning in strategic planning for higher education institutions. Path models of three levels of independent variables are developed. Dependent variables measuring applications and enrollments at Virginia Polytechnic Institute and State University are…

Florida, 2011-forest inventory and analysis factsheet

Treesearch

Mark J. Brown; Jarek Nowak

2013-01-01

Forest Inventory and Analysis (FIA) factsheets are produced periodically to keep the public up to date on the extent and condition of the forest lands in each State. The forestrelated estimates in the factsheets are based upon data collected from thousands of sample plots distributed across the landscape in a systematic manner. The total number of these plots is...

Presenting simulation results in a nested loop plot.

PubMed

Rücker, Gerta; Schwarzer, Guido

2014-12-12

Statisticians investigate new methods in simulations to evaluate their properties for future real data applications. Results are often presented in a number of figures, e.g., Trellis plots. We had conducted a simulation study on six statistical methods for estimating the treatment effect in binary outcome meta-analyses, where selection bias (e.g., publication bias) was suspected because of apparent funnel plot asymmetry. We varied five simulation parameters: true treatment effect, extent of selection, event proportion in control group, heterogeneity parameter, and number of studies in meta-analysis. In combination, this yielded a total number of 768 scenarios. To present all results using Trellis plots, 12 figures were needed. Choosing bias as criterion of interest, we present a 'nested loop plot', a diagram type that aims to have all simulation results in one plot. The idea was to bring all scenarios into a lexicographical order and arrange them consecutively on the horizontal axis of a plot, whereas the treatment effect estimate is presented on the vertical axis. The plot illustrates how parameters simultaneously influenced the estimate. It can be combined with a Trellis plot in a so-called hybrid plot. Nested loop plots may also be applied to other criteria such as the variance of estimation. The nested loop plot, similar to a time series graph, summarizes all information about the results of a simulation study with respect to a chosen criterion in one picture and provides a suitable alternative or an addition to Trellis plots.

Graphical analysis of power systems for mobile robotics

NASA Astrophysics Data System (ADS)

Raade, Justin William

The field of mobile robotics places stringent demands on the power system. Energetic autonomy, or the ability to function for a useful operation time independent of any tether, refueling, or recharging, is a driving force in a robot designed for a field application. The focus of this dissertation is the development of two graphical analysis tools, namely Ragone plots and optimal hybridization plots, for the design of human scale mobile robotic power systems. These tools contribute to the intuitive understanding of the performance of a power system and expand the toolbox of the design engineer. Ragone plots are useful for graphically comparing the merits of different power systems for a wide range of operation times. They plot the specific power versus the specific energy of a system on logarithmic scales. The driving equations in the creation of a Ragone plot are derived in terms of several important system parameters. Trends at extreme operation times (both very short and very long) are examined. Ragone plot analysis is applied to the design of several power systems for high-power human exoskeletons. Power systems examined include a monopropellant-powered free piston hydraulic pump, a gasoline-powered internal combustion engine with hydraulic actuators, and a fuel cell with electric actuators. Hybrid power systems consist of two or more distinct energy sources that are used together to meet a single load. They can often outperform non-hybrid power systems in low duty-cycle applications or those with widely varying load profiles and long operation times. Two types of energy sources are defined: engine-like and capacitive. The hybridization rules for different combinations of energy sources are derived using graphical plots of hybrid power system mass versus the primary system power. Optimal hybridization analysis is applied to several power systems for low-power human exoskeletons. Hybrid power systems examined include a fuel cell and a solar panel coupled with lithium polymer batteries. In summary, this dissertation describes the development and application of two graphical analysis tools for the intuitive design of mobile robotic power systems. Several design examples are discussed involving human exoskeleton power systems.

Texture Analysis of Recurrence Plots Based on Wavelets and PSO for Laryngeal Pathologies Detection.

PubMed

Souza, Taciana A; Vieira, Vinícius J D; Correia, Suzete E N; Costa, Silvana L N C; de A Costa, Washington C; Souza, Micael A

2015-01-01

This paper deals with the discrimination between healthy and pathological speech signals using recurrence plots and wavelet transform with texture features. Approximation and detail coefficients are obtained from the recurrence plots using Haar wavelet transform, considering one decomposition level. The considered laryngeal pathologies are: paralysis, Reinke's edema and nodules. Accuracy rates above 86% were obtained by means of the employed method.

Finding Your Way out of the Forest without a Trail of Bread Crumbs: Development and Evaluation of Two Novel Displays of Forest Plots

ERIC Educational Resources Information Center

Schild, Anne H. E.; Voracek, Martin

2015-01-01

Research has shown that forest plots are a gold standard in the visualization of meta-analytic results. However, research on the general interpretation of forest plots and the role of researchers' meta-analysis experience and field of study is still unavailable. Additionally, the traditional display of effect sizes, confidence intervals, and…

Using publically available forest inventory data in climate-based modes of tree species distribution: Examining effects of true versus altered location coordinates

Treesearch

Jacob Gibson; Gretchen Moisen; Tracey Frescino; Thomas C. Edwards

2013-01-01

Species distribution models (SDMs) were built with US Forest Inventory and Analysis (FIA) publicly available plot coordinates, which are altered for plot security purposes, and compared with SDMs built with true plot coordinates. Six species endemic to the western US, including four junipers (Juniperus deppeana var. deppeana, J. monosperma, J. occidentalis, J....

Analysis of the Korean Navy Selection Process for the Naval Post Graduate School

DTIC Science & Technology

1988-06-01

OUTCOME OF ECL TESTING SCORE..........................54 C. OUTCOME OF TOEFL TESTING SCORE.......................55 D. PLOT OF NPS GRADE WITH ECL...TESTING SCORE..............55 E. PLOT OF NPS GRADE WIHT NA GRADE......................56 F. PLOT OF NPS GRADE WITH TOEFL TESTING SCORE............56...OF ECL TESTING SCORE ............. 30 Table S. EXPECTANCY TABLE OF NAG ............................ 31 Table 9. EXPECTANCY TABLE OF TOEFL TESTING SCORE

Redrawing the baseline: a method for adjusting biased historical forest estimates using a spatial and temporally representative plot network

Treesearch

Sara A. Goeking; Paul L. Patterson

2015-01-01

Users of Forest Inventory and Analysis (FIA) data sometimes compare historic and current forest inventory estimates, despite warnings that such comparisons may be tenuous. The purpose of this study was to demonstrate a method for obtaining a more accurate and representative reference dataset using data collected at co-located plots (i.e., plots that were measured...

Effects of low intensity prescribed fires on ponderosa pine forests in wilderness areas of Zion National Park, Utah

Treesearch

Henry V. Bastian

2001-01-01

Vegetation and fuel loading plots were monitored and sampled in wilderness areas treated with prescribed fire. Changes in ponderosa pine (Pinus ponderosa) forest structure tree species and fuel loading are presented. Plots were randomly stratified and established in burn units in 1995. Preliminary analysis of nine plots 2 years after burning show litter was reduced 54....

Pilot Inventory of FIA plots traditionally called `nonforest'

Treesearch

Rachel Riemann

2003-01-01

Forest-inventory data were collected on plots defined as ?nonforest? by the USDA Forest Service?s Forest Inventory and Analysis (FIA) unit. Nonforest plots may have trees on them, but they do not fit FIA?s definition of forest because the area covered by trees is too small, too sparsely populated by trees, too narrow (e.g., trees between fields or in the middle of a...

Pioneer identification of fake tiger claws using morphometric and DNA-based analysis in wildlife forensics in India.

PubMed

Vipin; Sharma, Vinita; Sharma, Chandra Prakash; Kumar, Ved Prakash; Goyal, Surendra Prakash

2016-09-01

The illegal trade in wildlife is a serious threat to the existence of wild animals throughout the world. The short supply and high demand for wildlife articles have caused an influx of many different forms of fake wildlife articles into this trade. The task of identifying the materials used in making such articles poses challenges in wildlife forensics as different approaches are required for species identification. Claws constitute 3.8% of the illegal animal parts (n=2899) received at the Wildlife Institute of India (WII) for species identification. We describe the identification of seized suspected tiger claws (n=18) using a combined approach of morphometric and DNA-based analysis. The differential keratin density, determined using X-ray radiographs, indicated that none of the 18 claws were of any large cat but were fake. We determined three claw measurements, viz. ac (from the external coronary dermo-epidermal interface to the epidermis of the skin fold connecting the palmar flanges of the coronary horn), bc (from the claw tip to the epidermis of the skin fold connecting the palmar flanges of the coronary horn) and the ratio bc/ac, for all the seized (n=18), tiger (n=23) and leopard (n=49) claws. Univariate and multivariate statistical analyses were performed using SPSS. A scatter plot generated using canonical discriminant function analysis revealed that of the 18 seized claws, 14 claws formed a cluster separate from the clusters of the tiger and leopard claws, whereas the remaining four claws were within the leopard cluster. Because a discrepancy was observed between the X-ray images and the measurements of these four claws, one of the claw that clustered with the leopard claws was chosen randomly and DNA analysis carried out using the cyt b (137bp) and 16S rRNA (410bp) genes. A BLAST search and comparison with the reference database at WII indicated that the keratin material of the claw was derived from Bos taurus (cattle). This is a pioneering discovery, and we suggest that a hierarchical combination of techniques be used for identifying claws involved in wildlife offences, i.e. that an X-ray, morphometric and DNA-based analysis be carried out, to ascertain whether the claws are of tigers or leopards. To identify species in the illegal wildlife trade morphometric and genetic reference database should be developed. Morphological features as well as DNA profiles need to be used for better implementation of the Wildlife (Protection) Act, 1972 of India and other laws/treaties in South-east Asia. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Aquifer test interpretation using derivative analysis and diagnostic plots

NASA Astrophysics Data System (ADS)

Hernández-Espriú, Antonio; Real-Rangel, Roberto; Cortés-Salazar, Iván; Castro-Herrera, Israel; Luna-Izazaga, Gabriela; Sánchez-León, Emilio

2017-04-01

Pumping tests remain a method of choice to deduce fundamental aquifer properties and to assess well condition. In the oil and gas (O&G) industry, well testing has been the core technique in examining reservoir behavior over the last 50 years. The pressure derivative by Bourdet, it is perhaps, the most significant single development in the history of well test analysis. Recently, the so-called diagnostics plots (e.g. drawdown and drawdown derivative in a log-log plot) have been successfully tested in aquifers. However, this procedure is still underutilized by groundwater professionals. This research illustrates the applicability range, advantages and drawbacks (e.g. smoothing procedures) of diagnostic plots using field examples from a wide spectrum of tests (short/long tests, constant/variable flow rates, drawdown/buildup stages, pumping well/observation well) in dissimilar geological conditions. We analyze new and pre-existent aquifer tests in Mexico, USA, Canada, Germany, France and Saudi Arabia. In constant flow rate tests, our results show that derivative analysis is an easy, robust and powerful tool to assess near-borehole damage effects, formation heterogeneity, boundaries, flow regimes, infinite-acting radial stages, i.e., valid Theisian framework, and fracture-driven flow. In step tests, the effectiveness relies on high-frequency drawdown measurements. Moreover, we adapt O&G analytical solutions to cater for the conditions in groundwater systems. In this context, further parameters can be computed analytically from the plots, such as skin factor, head losses, wellbore storage, distance to the boundary, channel-aquifer and/or fracture zone width, among others. Therefore, diagnostic plots should be considered a mandatory tool for pumping tests analysis among hydrogeologists. This project has been supported by DGAPA (UNAM) under the research project PAPIIT IN-112815.