Genetic structure of Cantharellus formosus populations in a second-growth temperate rain forest of the Pacific Northwest

USGS Publications Warehouse

Redman, Regina S.; Ranson, Judith; Rodriguez, Rusty J.

2006-01-01

Cantharellus formosus growing on the Olympic Peninsula of the Pacific Northwest was sampled from September – November 1995 for genetic analysis. A total of ninety-six basidiomes from five clusters separated from one another by 3 - 25 meters were genetically characterized by PCR analysis of 13 arbitrary loci and rDNA sequences. The number of basidiomes in each cluster varied from 15 to 25 and genetic analysis delineated 15 genets among the clusters. Analysis of variance utilizing thirteen apPCR generated genetic molecular markers and PCR amplification of the ribosomal ITS regions indicated that 81.41% of the genetic variation occurred between clusters and 18.59% within clusters. Proximity of the basidiomes within a cluster was not an indicator of genotypic similarity. The molecular profiles of each cluster were distinct and defined as unique populations containing 2 - 6 genets. The monitoring and analysis of this species through non-lethal sampling and future applications is discussed.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the Northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

NASA Astrophysics Data System (ADS)

Savage, J. C.; Simpson, R. W.

2013-09-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

USGS Publications Warehouse

Savage, James C.; Simpson, Robert W.

2013-01-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Clustering performance comparison using K-means and expectation maximization algorithms.

PubMed

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

Recognizing different tissues in human fetal femur cartilage by label-free Raman microspectroscopy

NASA Astrophysics Data System (ADS)

Kunstar, Aliz; Leijten, Jeroen; van Leuveren, Stefan; Hilderink, Janneke; Otto, Cees; van Blitterswijk, Clemens A.; Karperien, Marcel; van Apeldoorn, Aart A.

2012-11-01

Traditionally, the composition of bone and cartilage is determined by standard histological methods. We used Raman microscopy, which provides a molecular "fingerprint" of the investigated sample, to detect differences between the zones in human fetal femur cartilage without the need for additional staining or labeling. Raman area scans were made from the (pre)articular cartilage, resting, proliferative, and hypertrophic zones of growth plate and endochondral bone within human fetal femora. Multivariate data analysis was performed on Raman spectral datasets to construct cluster images with corresponding cluster averages. Cluster analysis resulted in detection of individual chondrocyte spectra that could be separated from cartilage extracellular matrix (ECM) spectra and was verified by comparing cluster images with intensity-based Raman images for the deoxyribonucleic acid/ribonucleic acid (DNA/RNA) band. Specific dendrograms were created using Ward's clustering method, and principal component analysis (PCA) was performed with the separated and averaged Raman spectra of cells and ECM of all measured zones. Overall (dis)similarities between measured zones were effectively visualized on the dendrograms and main spectral differences were revealed by PCA allowing for label-free detection of individual cartilaginous zones and for label-free evaluation of proper cartilaginous matrix formation for future tissue engineering and clinical purposes.

Patterns of glaucomatous visual field loss in sita fields automatically identified using independent component analysis.

PubMed

Goldbaum, Michael H; Jang, Gil-Jin; Bowd, Chris; Hao, Jiucang; Zangwill, Linda M; Liebmann, Jeffrey; Girkin, Christopher; Jung, Tzyy-Ping; Weinreb, Robert N; Sample, Pamela A

2009-12-01

To determine if the patterns uncovered with variational Bayesian-independent component analysis-mixture model (VIM) applied to a large set of normal and glaucomatous fields obtained with the Swedish Interactive Thresholding Algorithm (SITA) are distinct, recognizable, and useful for modeling the severity of the field loss. SITA fields were obtained with the Humphrey Visual Field Analyzer (Carl Zeiss Meditec, Inc, Dublin, California) on 1,146 normal eyes and 939 glaucoma eyes from subjects followed by the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. VIM modifies independent component analysis (ICA) to develop separate sets of ICA axes in the cluster of normal fields and the 2 clusters of abnormal fields. Of 360 models, the model with the best separation of normal and glaucomatous fields was chosen for creating the maximally independent axes. Grayscale displays of fields generated by VIM on each axis were compared. SITA fields most closely associated with each axis and displayed in grayscale were evaluated for consistency of pattern at all severities. The best VIM model had 3 clusters. Cluster 1 (1,193) was mostly normal (1,089, 95% specificity) and had 2 axes. Cluster 2 (596) contained mildly abnormal fields (513) and 2 axes; cluster 3 (323) held mostly moderately to severely abnormal fields (322) and 5 axes. Sensitivity for clusters 2 and 3 combined was 88.9%. The VIM-generated field patterns differed from each other and resembled glaucomatous defects (eg, nasal step, arcuate, temporal wedge). SITA fields assigned to an axis resembled each other and the VIM-generated patterns for that axis. Pattern severity increased in the positive direction of each axis by expansion or deepening of the axis pattern. VIM worked well on SITA fields, separating them into distinctly different yet recognizable patterns of glaucomatous field defects. The axis and pattern properties make VIM a good candidate as a preliminary process for detecting progression.

Systematic detection and classification of earthquake clusters in Italy

NASA Astrophysics Data System (ADS)

Poli, P.; Ben-Zion, Y.; Zaliapin, I. V.

2017-12-01

We perform a systematic analysis of spatio-temporal clustering of 2007-2017 earthquakes in Italy with magnitudes m>3. The study employs the nearest-neighbor approach of Zaliapin and Ben-Zion [2013a, 2013b] with basic data-driven parameters. The results indicate that seismicity in Italy (an extensional tectonic regime) is dominated by clustered events, with smaller proportion of background events than in California. Evaluation of internal cluster properties allows separation of swarm-like from burst-like seismicity. This classification highlights a strong geographical coherence of cluster properties. Swarm-like seismicity are dominant in regions characterized by relatively slow deformation with possible elevated temperature and/or fluids (e.g. Alto Tiberina, Pollino), while burst-like seismicity are observed in crystalline tectonic regions (Alps and Calabrian Arc) and in Central Italy where moderate to large earthquakes are frequent (e.g. L'Aquila, Amatrice). To better assess the variation of seismicity style across Italy, we also perform a clustering analysis with region-specific parameters. This analysis highlights clear spatial changes of the threshold separating background and clustered seismicity, and permits better resolution of different clusters in specific geological regions. For example, a large proportion of repeaters is found in the Etna region as expected for volcanic-induced seismicity. A similar behavior is observed in the northern Apennines with high pore pressure associated with mantle degassing. The observed variations of earthquakes properties highlight shortcomings of practices using large-scale average seismic properties, and points to connections between seismicity and local properties of the lithosphere. The observations help to improve the understanding of the physics governing the occurrence of earthquakes in different regions.

Preliminary Cluster Analysis For Several Representatives Of Genus Kerivoula (Chiroptera: Vespertilionidae) in Borneo

NASA Astrophysics Data System (ADS)

Hasan, Noor Haliza; Abdullah, M. T.

2008-01-01

The aim of the study is to use cluster analysis on morphometric parameters within the genus Kerivoula to produce a dendrogram and to determine the suitability of this method to describe the relationship among species within this genus. A total of 15 adult male individuals from genus Kerivoula taken from sampling trips around Borneo and specimens kept at the zoological museum of Universiti Malaysia Sarawak were examined. A total of 27 characters using dental, skull and external body measurements were recorded. Clustering analysis illustrated the grouping and morphometric relationships between the species of this genus. It has clearly separated each species from each other despite the overlapping of measurements of some species within the genus. Cluster analysis provides an alternative approach to make a preliminary identification of a species.

A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure.

PubMed

Hebels, Dennie G A J; Rasche, Axel; Herwig, Ralf; van Westen, Gerard J P; Jennen, Danyel G J; Kleinjans, Jos C S

2016-01-01

When evaluating compound similarity, addressing multiple sources of information to reach conclusions about common pharmaceutical and/or toxicological mechanisms of action is a crucial strategy. In this chapter, we describe a systems biology approach that incorporates analyses of hepatotoxicant data for 33 compounds from three different sources: a chemical structure similarity analysis based on the 3D Tanimoto coefficient, a chemical structure-based protein target prediction analysis, and a cross-study/cross-platform meta-analysis of in vitro and in vivo human and rat transcriptomics data derived from public resources (i.e., the diXa data warehouse). Hierarchical clustering of the outcome scores of the separate analyses did not result in a satisfactory grouping of compounds considering their known toxic mechanism as described in literature. However, a combined analysis of multiple data types may hypothetically compensate for missing or unreliable information in any of the single data types. We therefore performed an integrated clustering analysis of all three data sets using the R-based tool iClusterPlus. This indeed improved the grouping results. The compound clusters that were formed by means of iClusterPlus represent groups that show similar gene expression while simultaneously integrating a similarity in structure and protein targets, which corresponds much better with the known mechanism of action of these toxicants. Using an integrative systems biology approach may thus overcome the limitations of the separate analyses when grouping liver toxicants sharing a similar mechanism of toxicity.

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

Cluster Analysis of Downscaled and Explicitly Simulated North Atlantic Tropical Cyclone Tracks

DOE PAGES

Daloz, Anne S.; Camargo, S. J.; Kossin, J. P.; ...

2015-02-11

A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in U.S. landfalling systems. Here, the authors present a tentative study that examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1°–0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. Here, for both configurations, tracksmore » are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and subtropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity, and power dissipation index in each cluster are documented for both configurations. The authors’ results show that, except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. The authors also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Lastly, the authors examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.« less

StarBooster Demonstrator Cluster Configuration Analysis/Verification Program

NASA Technical Reports Server (NTRS)

DeTurris, Dianne J.

2003-01-01

In order to study the flight dynamics of the cluster configuration of two first stage boosters and upper-stage, flight-testing of subsonic sub-scale models has been undertaken using two glideback boosters launched on a center upper-stage. Three high power rockets clustered together were built and flown to demonstrate vertical launch, separation and horizontal recovery of the boosters. Although the boosters fly to conventional aircraft landing, the centerstage comes down separately under its own parachute. The goal of the project has been to collect data during separation and flight for comparison with a six degree of freedom simulation. The configuration for the delta wing canard boosters comes from a design by Starcraft Boosters, Inc. The subscale rockets were constructed of foam covered in carbon or fiberglass and were launched with commercially available solid rocket motors. The first set of boosters built were 3-ft tall with a 4-ft tall centerstage, and two additional sets of boosters were made that were each over 5-ft tall with a 7.5 ft centerstage. The rocket cluster is launched vertically, then after motor bum out the boosters are separated and flown to a horizontal landing under radio-control. An on-board data acquisition system recorded data during both the launch and glide phases of flight.

Pattern of clustering of menopausal problems: A study with a Bengali Hindu ethnic group.

PubMed

Dasgupta, Doyel; Pal, Baidyanath; Ray, Subha

2016-01-01

We attempted to find out how menopausal problems cluster with each other. The study was conducted among a group of women belonging to a Bengali-speaking Hindu ethnic group of West Bengal, a state located in Eastern India. We recruited 1,400 participants for the study. Information on sociodemographic aspects and menopausal problems were collected from these participants with the help of a pretested questionnaire. Results of cluster analysis showed that vasomotor, vaginal, and urinary problems cluster together, separately from physical and psychosomatic problems.

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

Valero-Mora, Pedro M.; Ledesma, Ruben D.

2011-01-01

This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the…

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

2008-07-01

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

Recognizing patterns of visual field loss using unsupervised machine learning

NASA Astrophysics Data System (ADS)

Yousefi, Siamak; Goldbaum, Michael H.; Zangwill, Linda M.; Medeiros, Felipe A.; Bowd, Christopher

2014-03-01

Glaucoma is a potentially blinding optic neuropathy that results in a decrease in visual sensitivity. Visual field abnormalities (decreased visual sensitivity on psychophysical tests) are the primary means of glaucoma diagnosis. One form of visual field testing is Frequency Doubling Technology (FDT) that tests sensitivity at 52 points within the visual field. Like other psychophysical tests used in clinical practice, FDT results yield specific patterns of defect indicative of the disease. We used Gaussian Mixture Model with Expectation Maximization (GEM), (EM is used to estimate the model parameters) to automatically separate FDT data into clusters of normal and abnormal eyes. Principal component analysis (PCA) was used to decompose each cluster into different axes (patterns). FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal (i.e., glaucomatous) FDT results, recruited from a university-based, longitudinal, multi-center, clinical study on glaucoma. The GEM input was the 52-point FDT threshold sensitivities for all eyes. The optimal GEM model separated the FDT fields into 3 clusters. Cluster 1 contained 94% normal fields (94% specificity) and clusters 2 and 3 combined, contained 77% abnormal fields (77% sensitivity). For clusters 1, 2 and 3 the optimal number of PCA-identified axes were 2, 2 and 5, respectively. GEM with PCA successfully separated FDT fields from healthy and glaucoma eyes and identified familiar glaucomatous patterns of loss.

Structures in the Great Attractor region

NASA Astrophysics Data System (ADS)

Radburn-Smith, D. J.; Lucey, J. R.; Woudt, P. A.; Kraan-Korteweg, R. C.; Watson, F. G.

2006-07-01

To further our understanding of the Great Attractor (GA), we have undertaken a redshift survey using the 2-degree Field (2dF) instrument on the Anglo-Australian Telescope (AAT). Clusters and filaments in the GA region were targeted with 25 separate pointings resulting in approximately 2600 new redshifts. Targets included poorly studied X-ray clusters from the Clusters in the Zone of Avoidance (CIZA) Catalogue as well as the Cen-Crux and PKS 1343-601 clusters, both of which lie close to the classic GA centre. For nine clusters in the region, we report velocity distributions as well as virial and projected mass estimates. The virial mass of CIZA J1324.7-5736, now identified as a separate structure from the Cen-Crux cluster, is found to be ˜3 × 1014-M⊙, in good agreement with the X-ray inferred mass. In the PKS 1343-601 field, five redshifts are measured of which four are new. An analysis of redshifts from this survey, in combination with those from the literature, reveals the dominant structure in the GA region to be a large filament, which appears to extend from Abell S0639 (l= 281°, b=+11°) to (l˜ 5°, b˜-50°), encompassing the Cen-Crux, CIZA J1324.7-5736, Norma and Pavo II clusters. Behind the Norma cluster at cz˜ 15-000-km-s-1, the masses of four rich clusters are calculated. These clusters (Triangulum Australis, Ara, CIZA J1514.6-4558 and CIZA J1410.4-4246) may contribute to a continued large-scale flow beyond the GA. The results of these observations will be incorporated into a subsequent analysis of the GA flow.

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features.

PubMed

Haakensen, Vilde D; Lingjaerde, Ole Christian; Lüders, Torben; Riis, Margit; Prat, Aleix; Troester, Melissa A; Holmen, Marit M; Frantzen, Jan Ole; Romundstad, Linda; Navjord, Dina; Bukholm, Ida K; Johannesen, Tom B; Perou, Charles M; Ursin, Giske; Kristensen, Vessela N; Børresen-Dale, Anne-Lise; Helland, Aslaug

2011-11-01

Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer.

Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support.

PubMed

Xia, Eryu; Liu, Haifeng; Li, Jing; Mei, Jing; Li, Xuejun; Xu, Enliang; Li, Xiang; Hu, Gang; Xie, Guotong; Xu, Meilin

2017-01-01

Clinical decision support systems are information technology systems that assist clinical decision-making tasks, which have been shown to enhance clinical performance. Cluster analysis, which groups similar patients together, aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses. Useful as it is, the application of cluster analysis in clinical decision support systems is less reported. Here, we describe the usage of cluster analysis in clinical decision support systems, by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles. This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians. We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes. These efforts represent a step toward promoting patient-centered care and enabling precision medicine.

Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies

NASA Astrophysics Data System (ADS)

Deshmukh, Atul; Singh, S. P.; Chaturvedi, Pankaj; Krishna, C. Murali

2011-12-01

Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.

Correlation and network analysis of global financial indices

NASA Astrophysics Data System (ADS)

Kumar, Sunil; Deo, Nivedita

2012-08-01

Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.

Correlation and network analysis of global financial indices.

PubMed

Kumar, Sunil; Deo, Nivedita

2012-08-01

Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.

Glaucomatous patterns in Frequency Doubling Technology (FDT) perimetry data identified by unsupervised machine learning classifiers.

PubMed

Bowd, Christopher; Weinreb, Robert N; Balasubramanian, Madhusudhanan; Lee, Intae; Jang, Giljin; Yousefi, Siamak; Zangwill, Linda M; Medeiros, Felipe A; Girkin, Christopher A; Liebmann, Jeffrey M; Goldbaum, Michael H

2014-01-01

The variational Bayesian independent component analysis-mixture model (VIM), an unsupervised machine-learning classifier, was used to automatically separate Matrix Frequency Doubling Technology (FDT) perimetry data into clusters of healthy and glaucomatous eyes, and to identify axes representing statistically independent patterns of defect in the glaucoma clusters. FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal FDT results from the UCSD-based Diagnostic Innovations in Glaucoma Study (DIGS) and African Descent and Glaucoma Evaluation Study (ADAGES). For all eyes, VIM input was 52 threshold test points from the 24-2 test pattern, plus age. FDT mean deviation was -1.00 dB (S.D. = 2.80 dB) and -5.57 dB (S.D. = 5.09 dB) in FDT-normal eyes and FDT-abnormal eyes, respectively (p<0.001). VIM identified meaningful clusters of FDT data and positioned a set of statistically independent axes through the mean of each cluster. The optimal VIM model separated the FDT fields into 3 clusters. Cluster N contained primarily normal fields (1109/1190, specificity 93.1%) and clusters G1 and G2 combined, contained primarily abnormal fields (651/786, sensitivity 82.8%). For clusters G1 and G2 the optimal number of axes were 2 and 5, respectively. Patterns automatically generated along axes within the glaucoma clusters were similar to those known to be indicative of glaucoma. Fields located farther from the normal mean on each glaucoma axis showed increasing field defect severity. VIM successfully separated FDT fields from healthy and glaucoma eyes without a priori information about class membership, and identified familiar glaucomatous patterns of loss.

Potential Environmental Justice (EJ) areas in Region 2 based on 2000 Census [EPA.EJAREAS_2000

EPA Pesticide Factsheets

Potential Environmental Justice (EJ) areas in Region 2 . This dataset was derived from 2000 census data and based on the criteria setforth in the Region 2 Interim Environmental Justice Policy. The two criteria for Region 2's EJ demographic analysis are percent poverty and percent minority. The percent minority and percent poverty numbers for each blockgroup are compared to the benchmark value for the state. Census blockgroups with percent poverty or percent minority higher than the state threshold are considered potential EJ areas. The cutoffs for each state were derived by using the statistical method - cluster analysis.Cluster analysis was chosen as the most objective way of evaluating the demographic data and determining cutoff values for minority and low income. With cluster analysis, data are divided into two distinct groups (e.g., minority and non-minority, and low income and non-low income). Cluster analysis examines natural breaks of the data. Separate analyses were conducted for minority and low income, respectively, for each State. All census block groups within a State were ranked in descending order according to the demographic factor under evaluation. This resulted in a ranking for percent minority by block group and a separate ranking for percent low income by block group. An iterative process was employed where the data were (1) split into two groups; (2) the means for each of the two groups were calculated; (3) the difference between the

Classification of Forefoot Plantar Pressure Distribution in Persons with Diabetes: A Novel Perspective for the Mechanical Management of Diabetic Foot?

PubMed Central

Deschamps, Kevin; Matricali, Giovanni Arnoldo; Roosen, Philip; Desloovere, Kaat; Bruyninckx, Herman; Spaepen, Pieter; Nobels, Frank; Tits, Jos; Flour, Mieke; Staes, Filip

2013-01-01

Background The aim of this study was to identify groups of subjects with similar patterns of forefoot loading and verify if specific groups of patients with diabetes could be isolated from non-diabetics. Methodology/Principal Findings Ninety-seven patients with diabetes and 33 control participants between 45 and 70 years were prospectively recruited in two Belgian Diabetic Foot Clinics. Barefoot plantar pressure measurements were recorded and subsequently analysed using a semi-automatic total mapping technique. Kmeans cluster analysis was applied on relative regional impulses of six forefoot segments in order to pursue a classification for the control group separately, the diabetic group separately and both groups together. Cluster analysis led to identification of three distinct groups when considering only the control group. For the diabetic group, and the computation considering both groups together, four distinct groups were isolated. Compared to the cluster analysis of the control group an additional forefoot loading pattern was identified. This group comprised diabetic feet only. The relevance of the reported clusters was supported by ANOVA statistics indicating significant differences between different regions of interest and different clusters. Conclusion/s Significance There seems to emerge a new era in diabetic foot medicine which embraces the classification of diabetic patients according to their biomechanical profile. Classification of the plantar pressure distribution has the potential to provide a means to determine mechanical interventions for the prevention and/or treatment of the diabetic foot. PMID:24278219

Development of Wien filter for small ion gun of surface analysis

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

Bahng, Jungbae; Busan Center, Korea Basic Science Institute, Busan 609-735; Hong, Jonggi

The gas cluster ion beam (GCIB) and liquid metal ion beam have been studied in the context of ion beam usage for analytical equipment in applications such as X-ray photoelectron spectroscopy and secondary ion mass spectroscopy (SIMS). In particular, small ion sources are used for the secondary ion generation and ion etching. To set the context to this study, the SIMS project has been launched to develop ion-gun based analytical equipment for the Korea Basic Science Institute. The objective of the first stage of the project is the generation of argon beams with a GCIB system [A. Kirkpatrick, Nucl. Instrum.more » Methods Phys. Res., Sect. B 206, 830–837 (2003)] that consists of a nozzle, skimmer, ionizer, acceleration tube, separation system, transport system, and target. The Wien filter directs the selected cluster beam to the target system by exploiting the velocity difference of the generated particles from GCIB. In this paper, we present the theoretical modeling and three-dimensional electromagnetic analysis of the Wien filter, which can separate Ar{sup +}{sub 2500} clusters from Ar{sup +}{sub 2400} to Ar{sup +}{sub 2600} clusters with a 1-mm collimator.« less

Cytologic separation of branchial cleft cyst from metastatic cystic squamous cell carcinoma: A multivariate analysis of nineteen cytomorphologic features.

PubMed

Layfield, Lester J; Esebua, Magda; Schmidt, Robert L

2016-07-01

The separation of branchial cleft cysts from metastatic cystic squamous cell carcinomas in adults can be clinically and cytologically challenging. Diagnostic accuracy for separation is reported to be as low as 75% prompting some authors to recommend frozen section evaluation of suspected branchial cleft cysts before resection. We evaluated 19 cytologic features to determine which were useful in this distinction. Thirty-three cases (21 squamous carcinoma and 12 branchial cysts) of histologically confirmed cystic lesions of the lateral neck were graded for the presence or absence of 19 cytologic features by two cytopathologists. The cytologic features were analyzed for agreement between observers and underwent multivariate analysis for correlation with the diagnosis of carcinoma. Interobserver agreement was greatest for increased nuclear/cytoplasmic (N/C) ratio, pyknotic nuclei, and irregular nuclear membranes. Recursive partitioning analysis showed increased N/C ratio, small clusters of cells, and irregular nuclear membranes were the best discriminators. The distinction of branchial cleft cysts from cystic squamous cell carcinoma is cytologically difficult. Both digital image analysis and p16 testing have been suggested as aids in this separation, but analysis of cytologic features remains the main method for diagnosis. In an analysis of 19 cytologic features, we found that high nuclear cytoplasmic ratio, irregular nuclear membranes, and small cell clusters were most helpful in their distinction. Diagn. Cytopathol. 2016;44:561-567. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty

NASA Astrophysics Data System (ADS)

Ross, Ashley J.; Banik, Nilanjan; Avila, Santiago; Percival, Will J.; Dodelson, Scott; Garcia-Bellido, Juan; Crocce, Martin; Elvin-Poole, Jack; Giannantonio, Tommaso; Manera, Marc; Sevilla-Noarbe, Ignacio

2017-12-01

We determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the baryon acoustic oscillation (BAO) information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line of sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertainty σz ≥ 0.02(1 + z), we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for σz ≥ 0.02(1 + z). For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations (combining two separate sets) of galaxy simulations mimicking the Dark Energy Survey Year 1 (DES Y1) sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.

Taxonomic Identity of the Invasive Fruit Fly Pest, Bactrocera invadens: Concordance in Morphometry and DNA Barcoding

PubMed Central

Khamis, Fathiya M.; Masiga, Daniel K.; Mohamed, Samira A.; Salifu, Daisy; de Meyer, Marc; Ekesi, Sunday

2012-01-01

In 2003, a new fruit fly pest species was recorded for the first time in Kenya and has subsequently been found in 28 countries across tropical Africa. The insect was described as Bactrocera invadens, due to its rapid invasion of the African continent. In this study, the morphometry and DNA Barcoding of different populations of B. invadens distributed across the species range of tropical Africa and a sample from the pest's putative aboriginal home of Sri Lanka was investigated. Morphometry using wing veins and tibia length was used to separate B. invadens populations from other closely related Bactrocera species. The Principal component analysis yielded 15 components which correspond to the 15 morphometric measurements. The first two principal axes contributed to 90.7% of the total variance and showed partial separation of these populations. Canonical discriminant analysis indicated that only the first five canonical variates were statistically significant. The first two canonical variates contributed a total of 80.9% of the total variance clustering B. invadens with other members of the B. dorsalis complex while distinctly separating B. correcta, B. cucurbitae, B. oleae and B. zonata. The largest Mahalanobis squared distance (D2 = 122.9) was found to be between B. cucurbitae and B. zonata, while the lowest was observed between B. invadens populations against B. kandiensis (8.1) and against B. dorsalis s.s (11.4). Evolutionary history inferred by the Neighbor-Joining method clustered the Bactrocera species populations into four clusters. First cluster consisted of the B. dorsalis complex (B. invadens, B. kandiensis and B. dorsalis s. s.), branching from the same node while the second group was paraphyletic clades of B. correcta and B. zonata. The last two are monophyletic clades, consisting of B. cucurbitae and B. oleae, respectively. Principal component analysis using the genetic distances confirmed the clustering inferred by the NJ tree. PMID:23028649

Active microbial soil communities in different agricultural managements

NASA Astrophysics Data System (ADS)

Landi, S.; Pastorelli, R.

2009-04-01

We studied the composition of active eubacterial microflora by RNA extraction from soil (bulk and rhizosphere) under different environmental impact managements, in a hilly basin in Gallura (Sardinia). We contrasted grassy vineyard, in which the soil had been in continuous contact with plant roots for a long period of time, with traditional tilled vineyard. Moreover, we examined permanent grassland, in which plants had been present for some years, with temporary grassland, in which varying plants had been present only during the respective growing seasons. Molecular analysis of total population was carried out by electrophoretic separation by Denaturing Gradient Gel Electrophoresis (DGGE) of amplified cDNA fragments obtained from 16S rRNA. In vineyards UPGMA (Unweighted Pair Group Mathematical Average) analysis made up separate clusters depending on soil management. In spring both clusters showed similarity over 70%, while in autumn the similarity increased, 84% and 90% for grassy and conventional tilled vineyard respectively. Permanent and temporary grassland joined in a single cluster in spring, while in autumn a partial separation was evidenced. The grassy vineyard, permanent and temporary grassland showed higher richness and diversity Shannon-Weiner index values than vineyard with conventional tillage although no significant. In conclusion the expected effect of the rhizosphere was visible: the grass cover influenced positively the diversity of active microbial population.

A graph-Laplacian-based feature extraction algorithm for neural spike sorting.

PubMed

Ghanbari, Yasser; Spence, Larry; Papamichalis, Panos

2009-01-01

Analysis of extracellular neural spike recordings is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering which is performed in the feature space. This paper proposes a new feature extraction method (which we call Graph Laplacian Features, GLF) based on minimizing the graph Laplacian and maximizing the weighted variance. The algorithm is compared with Principal Components Analysis (PCA, the most commonly-used feature extraction method) using simulated neural data. The results show that the proposed algorithm produces more compact and well-separated clusters compared to PCA. As an added benefit, tentative cluster centers are output which can be used to initialize a subsequent clustering stage.

Characterization of limes (Citrus aurantifolia) grown in Bhutan and Indonesia using high-throughput sequencing

PubMed Central

Penjor, Tshering; Mimura, Takashi; Matsumoto, Ryoji; Yamamoto, Masashi; Nagano, Yukio

2014-01-01

Lime [Citrus aurantifolia (Cristm.) Swingle] is a Citrus species that is a popular ingredient in many cuisines. Some citrus plants are known to originate in the area ranging from northeastern India to southwestern China. In the current study, we characterized and compared limes grown in Bhutan (n = 5 accessions) and Indonesia (n = 3 accessions). The limes were separated into two groups based on their morphology. Restriction site-associated DNA sequencing (RAD-seq) separated the eight accessions into two clusters. One cluster contained four accessions from Bhutan, whereas the other cluster contained one accession from Bhutan and the three accessions from Indonesia. This genetic classification supported the morphological classification of limes. The analysis suggests that the properties associated with asexual reproduction, and somatic homologous recombination, have contributed to the genetic diversification of limes. PMID:24781859

Scoring clustering solutions by their biological relevance.

PubMed

Gat-Viks, I; Sharan, R; Shamir, R

2003-12-12

A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering gene expression data into homogeneous groups was shown to be instrumental in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on clustering algorithms for gene expression analysis, very few works addressed the systematic comparison and evaluation of clustering results. Typically, different clustering algorithms yield different clustering solutions on the same data, and there is no agreed upon guideline for choosing among them. We developed a novel statistically based method for assessing a clustering solution according to prior biological knowledge. Our method can be used to compare different clustering solutions or to optimize the parameters of a clustering algorithm. The method is based on projecting vectors of biological attributes of the clustered elements onto the real line, such that the ratio of between-groups and within-group variance estimators is maximized. The projected data are then scored using a non-parametric analysis of variance test, and the score's confidence is evaluated. We validate our approach using simulated data and show that our scoring method outperforms several extant methods, including the separation to homogeneity ratio and the silhouette measure. We apply our method to evaluate results of several clustering methods on yeast cell-cycle gene expression data. The software is available from the authors upon request.

Inferring Phylogenetic Relationships of Indian Citron (Citrus medica L.) based on rbcL and matK Sequences of Chloroplast DNA.

PubMed

Uchoi, Ajit; Malik, Surendra Kumar; Choudhary, Ravish; Kumar, Susheel; Rohini, M R; Pal, Digvender; Ercisli, Sezai; Chaudhury, Rekha

2016-06-01

Phylogenetic relationships of Indian Citron (Citrus medica L.) with other important Citrus species have been inferred through sequence analyses of rbcL and matK gene region of chloroplast DNA. The study was based on 23 accessions of Citrus genotypes representing 15 taxa of Indian Citrus, collected from wild, semi-wild, and domesticated stocks. The phylogeny was inferred using the maximum parsimony (MP) and neighbor-joining (NJ) methods. Both MP and NJ trees separated all the 23 accessions of Citrus into five distinct clusters. The chloroplast DNA (cpDNA) analysis based on rbcL and matK sequence data carried out in Indian taxa of Citrus was useful in differentiating all the true species and species/varieties of probable hybrid origin in distinct clusters or groups. Sequence analysis based on rbcL and matK gene provided unambiguous identification and disposition of true species like C. maxima, C. medica, C. reticulata, and related hybrids/cultivars. The separation of C. maxima, C. medica, and C. reticulata in distinct clusters or sub-clusters supports their distinctiveness as the basic species of edible Citrus. However, the cpDNA sequence analysis of rbcL and matK gene could not find any clear cut differentiation between subgenera Citrus and Papeda as proposed in Swingle's system of classification.

Nearest clusters based partial least squares discriminant analysis for the classification of spectral data.

PubMed

Song, Weiran; Wang, Hui; Maguire, Paul; Nibouche, Omar

2018-06-07

Partial Least Squares Discriminant Analysis (PLS-DA) is one of the most effective multivariate analysis methods for spectral data analysis, which extracts latent variables and uses them to predict responses. In particular, it is an effective method for handling high-dimensional and collinear spectral data. However, PLS-DA does not explicitly address data multimodality, i.e., within-class multimodal distribution of data. In this paper, we present a novel method termed nearest clusters based PLS-DA (NCPLS-DA) for addressing the multimodality and nonlinearity issues explicitly and improving the performance of PLS-DA on spectral data classification. The new method applies hierarchical clustering to divide samples into clusters and calculates the corresponding centre of every cluster. For a given query point, only clusters whose centres are nearest to such a query point are used for PLS-DA. Such a method can provide a simple and effective tool for separating multimodal and nonlinear classes into clusters which are locally linear and unimodal. Experimental results on 17 datasets, including 12 UCI and 5 spectral datasets, show that NCPLS-DA can outperform 4 baseline methods, namely, PLS-DA, kernel PLS-DA, local PLS-DA and k-NN, achieving the highest classification accuracy most of the time. Copyright © 2018 Elsevier B.V. All rights reserved.

Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

PubMed Central

Blecha, Kevin A.; Alldredge, Mat W.

2015-01-01

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores. PMID:26398546

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm

PubMed Central

Xu, Yaofang; Wu, Jiayi; Yin, Chang-Cheng; Mao, Youdong

2016-01-01

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis. PMID:27959895

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm.

PubMed

Xu, Yaofang; Wu, Jiayi; Yin, Chang-Cheng; Mao, Youdong

2016-01-01

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.

Fuzzy cluster analysis of high-field functional MRI data.

PubMed

Windischberger, Christian; Barth, Markus; Lamm, Claus; Schroeder, Lee; Bauer, Herbert; Gur, Ruben C; Moser, Ewald

2003-11-01

Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may help to identify artifacts and add novel and unexpected information valuable for interpretation, classification and characterization of functional MRI data which can be used to design new data acquisition schemes, stimulus presentations, neuro(physio)logical paradigms, as well as to improve quantitative biophysical models.

Assessment of repeatability of composition of perfumed waters by high-performance liquid chromatography combined with numerical data analysis based on cluster analysis (HPLC UV/VIS - CA).

PubMed

Ruzik, L; Obarski, N; Papierz, A; Mojski, M

2015-06-01

High-performance liquid chromatography (HPLC) with UV/VIS spectrophotometric detection combined with the chemometric method of cluster analysis (CA) was used for the assessment of repeatability of composition of nine types of perfumed waters. In addition, the chromatographic method of separating components of the perfume waters under analysis was subjected to an optimization procedure. The chromatograms thus obtained were used as sources of data for the chemometric method of cluster analysis (CA). The result was a classification of a set comprising 39 perfumed water samples with a similar composition at a specified level of probability (level of agglomeration). A comparison of the classification with the manufacturer's declarations reveals a good degree of consistency and demonstrates similarity between samples in different classes. A combination of the chromatographic method with cluster analysis (HPLC UV/VIS - CA) makes it possible to quickly assess the repeatability of composition of perfumed waters at selected levels of probability. © 2014 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images.

PubMed

Chin Neoh, Siew; Srisukkham, Worawut; Zhang, Li; Todryk, Stephen; Greystoke, Brigit; Peng Lim, Chee; Alamgir Hossain, Mohammed; Aslam, Nauman

2015-10-09

This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster scatter variances is proposed to produce robust segmentation of nucleus and cytoplasm of lymphocytes/lymphoblasts. Specifically, the proposed between-cluster evaluation is formulated based on the trade-off of several between-cluster measures of well-known feature extraction methods. The SDM measures are used in conjuction with Genetic Algorithm for clustering nucleus, cytoplasm, and background regions. Subsequently, a total of eighty features consisting of shape, texture, and colour information of the nucleus and cytoplasm sub-images are extracted. A number of classifiers (multi-layer perceptron, Support Vector Machine (SVM) and Dempster-Shafer ensemble) are employed for lymphocyte/lymphoblast classification. Evaluated with the ALL-IDB2 database, the proposed SDM-based clustering overcomes the shortcomings of Fuzzy C-means which focuses purely on within-cluster scatter variance. It also outperforms Linear Discriminant Analysis and Fuzzy Compactness and Separation for nucleus-cytoplasm separation. The overall system achieves superior recognition rates of 96.72% and 96.67% accuracies using bootstrapping and 10-fold cross validation with Dempster-Shafer and SVM, respectively. The results also compare favourably with those reported in the literature, indicating the usefulness of the proposed SDM-based clustering method.

An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images

PubMed Central

Chin Neoh, Siew; Srisukkham, Worawut; Zhang, Li; Todryk, Stephen; Greystoke, Brigit; Peng Lim, Chee; Alamgir Hossain, Mohammed; Aslam, Nauman

2015-01-01

This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster scatter variances is proposed to produce robust segmentation of nucleus and cytoplasm of lymphocytes/lymphoblasts. Specifically, the proposed between-cluster evaluation is formulated based on the trade-off of several between-cluster measures of well-known feature extraction methods. The SDM measures are used in conjuction with Genetic Algorithm for clustering nucleus, cytoplasm, and background regions. Subsequently, a total of eighty features consisting of shape, texture, and colour information of the nucleus and cytoplasm sub-images are extracted. A number of classifiers (multi-layer perceptron, Support Vector Machine (SVM) and Dempster-Shafer ensemble) are employed for lymphocyte/lymphoblast classification. Evaluated with the ALL-IDB2 database, the proposed SDM-based clustering overcomes the shortcomings of Fuzzy C-means which focuses purely on within-cluster scatter variance. It also outperforms Linear Discriminant Analysis and Fuzzy Compactness and Separation for nucleus-cytoplasm separation. The overall system achieves superior recognition rates of 96.72% and 96.67% accuracies using bootstrapping and 10-fold cross validation with Dempster-Shafer and SVM, respectively. The results also compare favourably with those reported in the literature, indicating the usefulness of the proposed SDM-based clustering method. PMID:26450665

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

PubMed Central

2011-01-01

Background Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Methods Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Results Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. Conclusion This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer. PMID:22044755

Analysis of candidates for interacting galaxy clusters. I. A1204 and A2029/A2033

NASA Astrophysics Data System (ADS)

Gonzalez, Elizabeth Johana; de los Rios, Martín; Oio, Gabriel A.; Lang, Daniel Hernández; Tagliaferro, Tania Aguirre; Domínguez R., Mariano J.; Castellón, José Luis Nilo; Cuevas L., Héctor; Valotto, Carlos A.

2018-04-01

Context. Merging galaxy clusters allow for the study of different mass components, dark and baryonic, separately. Also, their occurrence enables to test the ΛCDM scenario, which can be used to put constraints on the self-interacting cross-section of the dark-matter particle. Aim. It is necessary to perform a homogeneous analysis of these systems. Hence, based on a recently presented sample of candidates for interacting galaxy clusters, we present the analysis of two of these cataloged systems. Methods: In this work, the first of a series devoted to characterizing galaxy clusters in merger processes, we perform a weak lensing analysis of clusters A1204 and A2029/A2033 to derive the total masses of each identified interacting structure together with a dynamical study based on a two-body model. We also describe the gas and the mass distributions in the field through a lensing and an X-ray analysis. This is the first of a series of works which will analyze these type of system in order to characterize them. Results: Neither merging cluster candidate shows evidence of having had a recent merger event. Nevertheless, there is dynamical evidence that these systems could be interacting or could interact in the future. Conclusions: It is necessary to include more constraints in order to improve the methodology of classifying merging galaxy clusters. Characterization of these clusters is important in order to properly understand the nature of these systems and their connection with dynamical studies.

Clustering of diet- and activity-related parenting practices: cross-sectional findings of the INPACT study

PubMed Central

2013-01-01

Background Various diet- and activity-related parenting practices are positive determinants of child dietary and activity behaviour, including home availability, parental modelling and parental policies. There is evidence that parenting practices cluster within the dietary domain and within the activity domain. This study explores whether diet- and activity-related parenting practices cluster across the dietary and activity domain. Also examined is whether the clusters are related to child and parental background characteristics. Finally, to indicate the relevance of the clusters in influencing child dietary and activity behaviour, we examined whether clusters of parenting practices are related to these behaviours. Methods Data were used from 1480 parent–child dyads participating in the Dutch IVO Nutrition and Physical Activity Child cohorT (INPACT). Parents of children aged 8–11 years completed questionnaires at home assessing their diet- and activity-related parenting practices, child and parental background characteristics, and child dietary and activity behaviours. Principal component analysis (PCA) was used to identify clusters of parenting practices. Backward regression analysis was used to examine the relationship between child and parental background characteristics with cluster scores, and partial correlations to examine associations between cluster scores and child dietary and activity behaviours. Results PCA revealed five clusters of parenting practices: 1) high visibility and accessibility of screens and unhealthy food, 2) diet- and activity-related rules, 3) low availability of unhealthy food, 4) diet- and activity-related positive modelling, and 5) positive modelling on sports and fruit. Low parental education was associated with unhealthy cluster 1, while high(er) education was associated with healthy clusters 2, 3 and 5. Separate clusters were related to both child dietary and activity behaviour in the hypothesized directions: healthy clusters were positively related to obesity-reducing behaviours and negatively to obesity-inducing behaviours. Conclusion Parenting practices cluster across the dietary and activity domain. Parental education can be seen as an indicator of a broader parental context in which clusters of parenting practices operate. Separate clusters are related to both child dietary and activity behaviour. Interventions that focus on clusters of parenting practices to assist parents (especially low-educated parents) in changing their child’s dietary and activity behaviour seems justified. PMID:23531232

Gene signatures and expression of miRNAs associated with efficacy of panitumumab in a head and neck cancer phase II trial.

PubMed

Siano, Marco; Espeli, Vittoria; Mach, Nicolas; Bossi, Paolo; Licitra, Lisa; Ghielmini, Michele; Frattini, Milo; Canevari, Silvana; De Cecco, Loris

2018-07-01

Platinum-based chemotherapy plus the anti-EGFR monoclonal antibody (mAb) cetuximab is used to treat recurrent/metastatic (RM) head-neck squamous cell carcinoma (HNSCC). Recently, we defined Cluster3 gene-expression signature as a potential predictor of favorable progression-free survival (PFS) in cetuximab-treated RM-HNSCC patients and predictor of partial metabolic FDG-PET response in an afatinib window-of-opportunity trial. Another anti-EGFR-mAb (panitumumab) was used as the treatment agent in RM-HNSCC patients in the phase II PANI01trial. PANI01 tumor samples were analyzed using functional genomics to explore response predictors to anti-EGFR therapy. Whole-gene expression and real-time PCR analyses were applied to pre-treatment samples from 25 PANI01 patients. Three gene signatures (Cluster3 score, RAS onco-signature, microenvironment score) and seven selected miRNAs were separately analyzed for association with panitumumab efficacy. Cluster3 expression levels had a profile with a significant bimodal separation of samples (P =  3.08 E-13). Higher RAS activation, microenvironment score, and miRNA expression were associated with low-Cluster3 patients. The same biomarkers were separately associated with PFS. Patients with high-Cluster3 had significantly longer PFS than patients with low-Cluster3 (median PFS: 174 versus 51 days; log-rank P = 0.0021). ROC analysis demonstrated accuracy in predicting PFS (AUC = 0.877). Despite differences in clinical settings and anti-EGFR inhibitors used for treatment, response prediction by the Cluster3 signature and selected miRNAs was essentially the same. Translation into a useful clinical assay requires validation in a broader setting. Copyright © 2018 Elsevier Ltd. All rights reserved.

Gravitational lensing by clusters of galaxies - Constraining the mass distribution

NASA Technical Reports Server (NTRS)

Miralda-Escude, Jordi

1991-01-01

The possibility of placing constraints on the mass distribution of a cluster of galaxies by analyzing the cluster's gravitational lensing effect on the images of more distant galaxies is investigated theoretically in the limit of weak distortion. The steps in the proposed analysis are examined in detail, and it is concluded that detectable distortion can be produced by clusters with line-of-sight velocity dispersions of over 500 km/sec. Hence it should be possible to determine (1) the cluster center position (with accuracy equal to the mean separation of the background galaxies), (2) the cluster-potential quadrupole moment (to within about 20 percent of the total potential if velocity dispersion is 1000 km/sec), and (3) the power law for the outer-cluster density profile (if enough background galaxies in the surrounding region are observed).

Weak Lensing Results of the Merging Cluster A1758

NASA Technical Reports Server (NTRS)

Markevitch, M.; Gonzalez, A. H.; Bradac, M.

2011-01-01

Here we present the weak lensing results of A1758, which is known to have four cluster members undergoing two separate mergers, A1758N and A1758S. Weak lensing results of A1758N agree with previous weak lensing results of clusters lE0657-558 (Bullet cluster) and MACS J0025.4-1222, whose X-ray gas components were found to be largely separated from their clusters' gravitational potentials. A1758N has a geometry that is different from previously published mergers in that one of its X-ray peaks overlays the corresponding gravitational potential and the other X-ray peak is well separated from its cluster's gravitational potential.

Effect of Stagger on the Vibroacoustic Loads from Clustered Rockets

NASA Technical Reports Server (NTRS)

Rojo, Raymundo; Tinney, Charles E.; Ruf, Joseph H.

2016-01-01

The effect of stagger startup on the vibro-acoustic loads that form during the end- effects-regime of clustered rockets is studied using both full-scale (hot-gas) and laboratory scale (cold gas) data. Both configurations comprise three nozzles with thrust optimized parabolic contours that undergo free shock separated flow and restricted shock separated flow as well as an end-effects regime prior to flowing full. Acoustic pressure waveforms recorded at the base of the nozzle clusters are analyzed using various statistical metrics as well as time-frequency analysis. The findings reveal a significant reduction in end- effects-regime loads when engine ignition is staggered. However, regardless of stagger, both the skewness and kurtosis of the acoustic pressure time derivative elevate to the same levels during the end-effects-regime event thereby demonstrating the intermittence and impulsiveness of the acoustic waveforms that form during engine startup.

Are Binary Separations related to their System Mass?

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.

2004-08-01

We compile most recent multiplicity fractions and binary separation distributions for different primary masses, including very low-mass and brown dwarf primaries, and compare them with dynamical decay models of small-N clusters. The model predictions are based on detailed numerical calculations of the internal cluster dynamics, as well as on Monte-Carlo methods. Both observations and models reflect the same trends: (1) The multiplicity fraction is an increasing function of the primary mass. (2) The mean binary separations are increasing with the system mass in the sense that very low-mass binaries have average separations around ≈ 4AU, while the binary separation distribution for solar-type primaries peaks at ≈ 40AU. M-type binary systems apparently preferentially populate intermediate separations. Similar specific energy at the time of cluster formation for all cluster masses can possibly explain this trend.

Facial Structure Analysis Separates Autism Spectrum Disorders into Meaningful Clinical Subgroups

ERIC Educational Resources Information Center

Obafemi-Ajayi, Tayo; Miles, Judith H.; Takahashi, T. Nicole; Qi, Wenchuan; Aldridge, Kristina; Zhang, Minqi; Xin, Shi-Qing; He, Ying; Duan, Ye

2015-01-01

Varied cluster analysis were applied to facial surface measurements from 62 prepubertal boys with essential autism to determine whether facial morphology constitutes viable biomarker for delineation of discrete Autism Spectrum Disorders (ASD) subgroups. Earlier study indicated utility of facial morphology for autism subgrouping (Aldridge et al. in…

Cluster analysis and prediction of treatment outcomes for chronic rhinosinusitis.

PubMed

Soler, Zachary M; Hyer, J Madison; Rudmik, Luke; Ramakrishnan, Viswanathan; Smith, Timothy L; Schlosser, Rodney J

2016-04-01

Current clinical classifications of chronic rhinosinusitis (CRS) have weak prognostic utility regarding treatment outcomes. Simplified discriminant analysis based on unsupervised clustering has identified novel phenotypic subgroups of CRS, but prognostic utility is unknown. We sought to determine whether discriminant analysis allows prognostication in patients choosing surgery versus continued medical management. A multi-institutional prospective study of patients with CRS in whom initial medical therapy failed who then self-selected continued medical management or surgical treatment was used to separate patients into 5 clusters based on a previously described discriminant analysis using total Sino-Nasal Outcome Test-22 (SNOT-22) score, age, and missed productivity. Patients completed the SNOT-22 at baseline and for 18 months of follow-up. Baseline demographic and objective measures included olfactory testing, computed tomography, and endoscopy scoring. SNOT-22 outcomes for surgical versus continued medical treatment were compared across clusters. Data were available on 690 patients. Baseline differences in demographics, comorbidities, objective disease measures, and patient-reported outcomes were similar to previous clustering reports. Three of 5 clusters identified by means of discriminant analysis had improved SNOT-22 outcomes with surgical intervention when compared with continued medical management (surgery was a mean of 21.2 points better across these 3 clusters at 6 months, P < .05). These differences were sustained at 18 months of follow-up. Two of 5 clusters had similar outcomes when comparing surgery with continued medical management. A simplified discriminant analysis based on 3 common clinical variables is able to cluster patients and provide prognostic information regarding surgical treatment versus continued medical management in patients with CRS. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Cluster size resolving analysis of CH3F-(ortho-H2)n in solid para-hydrogen using FTIR absorption spectroscopy at 3 μm region.

PubMed

Miyamoto, Yuki; Momose, Takamasa; Kanamori, Hideto

2012-11-21

Infrared absorption spectra of methyl fluoride with ortho-hydrogen (ortho-H(2)) clusters in a solid para-hydrogen (para-H(2)) crystal at 3.6 K were studied in the C-H stretching fundamental region (~3000 cm(-1)) using an FTIR spectrometer. As shown previously, the ν(3) C-F stretching fundamental band of CH(3)F-(ortho-H(2))(n) (n = 0, 1, 2, ...) clusters at 1040 cm(-1) shows a series of n discrete absorption lines, which correspond to different-sized clusters. We observed three unresolved broad peaks in the C-H stretching region and applied this cluster model to them assuming the same intensity distribution function as the ν(3) band. A fitting analysis successfully gave us the linewidth and lineshift of the components in each vibrational band. It was found that the separately determined linewidth, matrix shift of the band origin, and cluster shift are dependent on the vibrational mode. From the transition intensities of the monomer component derived from the fitting analysis, we discuss the mixing ratio of the vibrational modes due to Fermi resonance.

Psychometric properties of the Social Interaction Anxiety Scale and separation criterion between Spanish youths with and without subtypes of social anxiety.

PubMed

Zubeidat, Ihab; Salinas, José María; Sierra, Juan Carlos; Fernández-Parra, Antonio

2007-01-01

In this study, we analyzed the reliability and validity of the Social Interaction Anxiety Scale (SIAS) and propose a separation criterion between youths with specific and generalized social anxiety and youths without social anxiety. A sample of 1012 Spanish youths attending school completed the SIAS, the Liebowitz Social Anxiety Scale, the Social Avoidance and Distress Scale, the Fear of Negative Evaluation Scale, the Youth Self-Report for Ages 11-18 and the Minnesota Multiphasic Personality Inventory-Adolescent. The factor analysis suggests the existence of three factors in the SIAS, the first two of which explain most of the variance of the construct assessed. Internal consistency is adequate in the first two factors. The SIAS features an adequate theoretical validity with the scores of different variables related to social interaction. Analysis of the criterion scores yields three groups pertaining to three clearly differentiated clusters. In the third cluster, two of social anxiety groups - specific and generalized - have been identified by means of a quantitative separation criterion.

Weighted graph cuts without eigenvectors a multilevel approach.

PubMed

Dhillon, Inderjit S; Guan, Yuqiang; Kulis, Brian

2007-11-01

A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods. In this paper, we discuss an equivalence between the objective functions used in these seemingly different methods--in particular, a general weighted kernel k-means objective is mathematically equivalent to a weighted graph clustering objective. We exploit this equivalence to develop a fast, high-quality multilevel algorithm that directly optimizes various weighted graph clustering objectives, such as the popular ratio cut, normalized cut, and ratio association criteria. This eliminates the need for any eigenvector computation for graph clustering problems, which can be prohibitive for very large graphs. Previous multilevel graph partitioning methods, such as Metis, have suffered from the restriction of equal-sized clusters; our multilevel algorithm removes this restriction by using kernel k-means to optimize weighted graph cuts. Experimental results show that our multilevel algorithm outperforms a state-of-the-art spectral clustering algorithm in terms of speed, memory usage, and quality. We demonstrate that our algorithm is applicable to large-scale clustering tasks such as image segmentation, social network analysis and gene network analysis.

Atlas-guided cluster analysis of large tractography datasets.

PubMed

Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer

2013-01-01

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment.

Traveling around Cape Horn: Otolith chemistry reveals a mixed stock of Patagonian hoki with separate Atlantic and Pacific spawning grounds

USGS Publications Warehouse

Schuchert, P.C.; Arkhipkin, A.I.; Koenig, A.E.

2010-01-01

Trace element fingerprints of edge and core regions in otoliths from 260 specimens of Patagonian hoki, Macruronus magellanicus L??nnberg, 1907, were analyzed by LA-ICPMS to reveal whether this species forms one or more population units (stocks) in the Southern Oceans. Fish were caught on their spawning grounds in Chile and feeding grounds in Chile and the Falkland Islands. Univariate and multivariate analyses of trace element concentrations in the otolith edges, which relate to the adult life of fish, could not distinguish between Atlantic (Falkland) and Pacific (Chile) hoki. Cluster analyses of element concentrations in the otolith edges produced three different clusters in all sample areas indicating high mixture of the stocks. Cluster analysis of trace element concentrations in the otolith cores, relating to juvenile and larval life stages, produced two separate clusters mainly distinguished by 137Ba concentrations. The results suggest that Patagonian hoki is a highly mixed fish stock with at least two spawning grounds around South America. ?? 2009 Elsevier B.V.

High-Resolution Analysis by Whole-Genome Sequencing of an International Lineage (Sequence Type 111) of Pseudomonas aeruginosa Associated with Metallo-Carbapenemases in the United Kingdom.

PubMed

Turton, Jane F; Wright, Laura; Underwood, Anthony; Witney, Adam A; Chan, Yuen-Ting; Al-Shahib, Ali; Arnold, Catherine; Doumith, Michel; Patel, Bharat; Planche, Timothy D; Green, Jonathan; Holliman, Richard; Woodford, Neil

2015-08-01

Whole-genome sequencing (WGS) was carried out on 87 isolates of sequence type 111 (ST-111) of Pseudomonas aeruginosa collected between 2005 and 2014 from 65 patients and 12 environmental isolates from 24 hospital laboratories across the United Kingdom on an Illumina HiSeq instrument. Most isolates (73) carried VIM-2, but others carried IMP-1 or IMP-13 (5) or NDM-1 (1); one isolate had VIM-2 and IMP-18, and 7 carried no metallo-beta-lactamase (MBL) gene. Single nucleotide polymorphism analysis divided the isolates into distinct clusters; the NDM-1 isolate was an outlier, and the IMP isolates and 6/7 MBL-negative isolates clustered separately from the main set of 73 VIM-2 isolates. Within the VIM-2 set, there were at least 3 distinct clusters, including a tightly clustered set of isolates from 3 hospital laboratories consistent with an outbreak from a single introduction that was quickly brought under control and a much broader set dominated by isolates from a long-running outbreak in a London hospital likely seeded from an environmental source, requiring different control measures; isolates from 7 other hospital laboratories in London and southeast England were also included. Bayesian evolutionary analysis indicated that all the isolates shared a common ancestor dating back ∼50 years (1960s), with the main VIM-2 set separating approximately 20 to 30 years ago. Accessory gene profiling revealed blocks of genes associated with particular clusters, with some having high similarity (≥95%) to bacteriophage genes. WGS of widely found international lineages such as ST-111 provides the necessary resolution to inform epidemiological investigations and intervention policies. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

PubMed Central

Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

2015-01-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

Convex clustering: an attractive alternative to hierarchical clustering.

PubMed

Chen, Gary K; Chi, Eric C; Ranola, John Michael O; Lange, Kenneth

2015-05-01

The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/.

Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering.

PubMed

Yang, Guang; Raschke, Felix; Barrick, Thomas R; Howe, Franklyn A

2015-09-01

To investigate whether nonlinear dimensionality reduction improves unsupervised classification of (1) H MRS brain tumor data compared with a linear method. In vivo single-voxel (1) H magnetic resonance spectroscopy (55 patients) and (1) H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With (1) H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of (1) H MRSI data after cluster analysis. © 2014 Wiley Periodicals, Inc.

Application of Geostatistical Methods and Machine Learning for spatio-temporal Earthquake Cluster Analysis

NASA Astrophysics Data System (ADS)

Schaefer, A. M.; Daniell, J. E.; Wenzel, F.

2014-12-01

Earthquake clustering tends to be an increasingly important part of general earthquake research especially in terms of seismic hazard assessment and earthquake forecasting and prediction approaches. The distinct identification and definition of foreshocks, aftershocks, mainshocks and secondary mainshocks is taken into account using a point based spatio-temporal clustering algorithm originating from the field of classic machine learning. This can be further applied for declustering purposes to separate background seismicity from triggered seismicity. The results are interpreted and processed to assemble 3D-(x,y,t) earthquake clustering maps which are based on smoothed seismicity records in space and time. In addition, multi-dimensional Gaussian functions are used to capture clustering parameters for spatial distribution and dominant orientations. Clusters are further processed using methodologies originating from geostatistics, which have been mostly applied and developed in mining projects during the last decades. A 2.5D variogram analysis is applied to identify spatio-temporal homogeneity in terms of earthquake density and energy output. The results are mitigated using Kriging to provide an accurate mapping solution for clustering features. As a case study, seismic data of New Zealand and the United States is used, covering events since the 1950s, from which an earthquake cluster catalogue is assembled for most of the major events, including a detailed analysis of the Landers and Christchurch sequences.

THE EVOLUTION OF PRIMORDIAL BINARY OPEN STAR CLUSTERS: MERGERS, SHREDDED SECONDARIES, AND SEPARATED TWINS

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

De la Fuente Marcos, R.; De la Fuente Marcos, C., E-mail: raul@galaxy.suffolk.e

2010-08-10

The properties of the candidate binary star cluster population in the Magellanic Clouds and Milky Way are similar. The fraction of candidate binaries is {approx}10% and the pair separation histogram exhibits a bimodal distribution commonly attributed to their transient nature. However, if primordial pairs cannot survive for long as recognizable bound systems, how are they ending up? Here, we use simulations to confirm that merging, extreme tidal distortion, and ionization are possible depending on the initial orbital elements and mass ratio of the cluster pair. Merging is observed for initially close pairs but also for wider systems in nearly parabolicmore » orbits. Its characteristic timescale depends on the initial orbital semi-major axis, eccentricity, and cluster pair mass ratio, becoming shorter for closer, more eccentric equal mass pairs. Shredding of the less massive cluster and subsequent separation is observed in all pairs with appreciably different masses. Wide pairs evolve into separated twins characterized by the presence of tidal bridges and separations of 200-500 pc after one Galactic orbit. Most observed binary candidates appear to be following this evolutionary path which translates into the dominant peak (25-30 pc) in the observed pair separation distribution. The secondary peak at smaller separations (10-15 pc) can be explained as due to close pairs in almost circular orbits and/or undergoing merging. Merged clusters exhibit both peculiar radial density and velocity dispersion profiles shaped by synchronization and gravogyro instabilities. Simulations and observations show that long-term binary open cluster stability is unlikely.« less

On hierarchical solutions to the BBGKY hierarchy

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1988-01-01

It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.

A QUANTITATIVE ANALYSIS OF DISTANT OPEN CLUSTERS

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

Janes, Kenneth A.; Hoq, Sadia

2011-03-15

The oldest open star clusters are important for tracing the history of the Galactic disk, but many of the more distant clusters are heavily reddened and projected against the rich stellar background of the Galaxy. We have undertaken an investigation of several distant clusters (Berkeley 19, Berkeley 44, King 25, NGC 6802, NGC 6827, Berkeley 52, Berkeley 56, NGC 7142, NGC 7245, and King 9) to develop procedures for separating probable cluster members from the background field. We next created a simple quantitative approach for finding approximate cluster distances, reddenings, and ages. We first conclude that with the possible exceptionmore » of King 25 they are probably all physical clusters. We also find that for these distant clusters our typical errors are about {+-}0.07 in E(B - V), {+-}0.15 in log(age), and {+-}0.25 in (m - M){sub o}. The clusters range in age from 470 Myr to 7 Gyr and range from 7.1 to 16.4 kpc from the Galactic center.« less

a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

NASA Astrophysics Data System (ADS)

Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

2017-09-01

Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

Country clustering applied to the water & sanitation sector: a new tool with potential applications in research & policy

PubMed Central

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2013-01-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were unique from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. PMID:24054545

Aqueous sulfate separation by crystallization of sulfate–water clusters

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

Custelcean, Radu; Williams, Neil J.; Seipp, Charles A.

An effective approach to separating sulfates from aqueous solutions is based on the crystallization of extended [SO 4(H 2O) 5 2-] n sulfate–water clusters with a bis(guanidinium) ligand. The ligand was generated in situ by hydrazone condensation in water, thus avoiding elaborate syntheses, tedious purifications, and organic solvents. Crystallization of sulfate–water clusters represents an alternative to the now established sulfate separation strategies that involve encapsulating the “naked” anion.

Aqueous sulfate separation by crystallization of sulfate–water clusters

DOE PAGES

Custelcean, Radu; Williams, Neil J.; Seipp, Charles A.

2015-08-07

An effective approach to separating sulfates from aqueous solutions is based on the crystallization of extended [SO 4(H 2O) 5 2-] n sulfate–water clusters with a bis(guanidinium) ligand. The ligand was generated in situ by hydrazone condensation in water, thus avoiding elaborate syntheses, tedious purifications, and organic solvents. Crystallization of sulfate–water clusters represents an alternative to the now established sulfate separation strategies that involve encapsulating the “naked” anion.

Genetic characterization of Uruguayan Pampa Rocha pigs with microsatellite markers

PubMed Central

Montenegro, M; Llambí, S; Castro, G; Barlocco, N; Vadell, A; Landi, V; Delgado, JV; Martínez, A

2015-01-01

In this study, we genetically characterized the Uruguayan pig breed Pampa Rocha. Genetic variability was assessed by analyzing a panel of 25 microsatellite markers from a sample of 39 individuals. Pampa Rocha pigs showed high genetic variability with observed and expected heterozygosities of 0.583 and 0.603, respectively. The mean number of alleles was 5.72. Twenty-four markers were polymorphic, with 95.8% of them in Hardy Weinberg equilibrium. The level of endogamy was low (FIS = 0.0475). A factorial analysis of correspondence was used to assess the genetic differences between Pampa Rocha and other pig breeds; genetic distances were calculated, and a tree was designed to reflect the distance matrix. Individuals were also allocated into clusters. This analysis showed that the Pampa Rocha breed was separated from the other breeds along the first and second axes. The neighbour-joining tree generated by the genetic distances DA showed clustering of Pampa Rocha with the Meishan breed. The allocation of individuals to clusters showed a clear separation of Pampa Rocha pigs. These results provide insights into the genetic variability of Pampa Rocha pigs and indicate that this breed is a well-defined genetic entity. PMID:25983624

Pattern Selection and Super-Patterns in Opinion Dynamics

NASA Astrophysics Data System (ADS)

Ben-Naim, Eli; Scheel, Arnd

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

Modem Signature Analysis.

DTIC Science & Technology

1982-10-01

AD-A127 993 MODEM SIGNATURE ANALISIS (U) PAR TECHNOLOGY CORP NEW / HARTFORD NY V EDWARDS ET AL. OCT 82 RADC-TR-82-269 F30602-80-C-0264 NCLASSIFIED F/G...as an indication of the class clustering and separation between different classes in the modem data base. It is apparent from the projection that the...that as the clusters disperse, the likelihood of a sample crossing the boundary into an adjacent region and causing a symbol decision error increases. As

Stable Isotope Quantitative N-Glycan Analysis by Liquid Separation Techniques and Mass Spectrometry.

PubMed

Mittermayr, Stefan; Albrecht, Simone; Váradi, Csaba; Millán-Martín, Silvia; Bones, Jonathan

2017-01-01

Liquid phase separation analysis and subsequent quantitation remains a challenging task for protein-derived oligosaccharides due to their inherent structural complexity and diversity. Incomplete resolution or co-detection of multiple glycan species complicates peak area-based quantitation and associated statistical analysis when optical detection methods are used. The approach outlined herein describes the utilization of stable isotope variants of commonly used fluorescent tags that allow for mass-based glycan identification and relative quantitation following separation by liquid chromatography (LC) or capillary electrophoresis (CE). Comparability assessment of glycoprotein-derived oligosaccharides is performed by derivatization with commercially available isotope variants of 2-aminobenzoic acid or aniline and analysis by LC- and CE-mass spectrometry. Quantitative information is attained from the extracted ion chromatogram/electropherogram ratios generated from the light and heavy isotope clusters.

Dynamic multifactor clustering of financial networks

NASA Astrophysics Data System (ADS)

Ross, Gordon J.

2014-02-01

We investigate the tendency for financial instruments to form clusters when there are multiple factors influencing the correlation structure. Specifically, we consider a stock portfolio which contains companies from different industrial sectors, located in several different countries. Both sector membership and geography combine to create a complex clustering structure where companies seem to first be divided based on sector, with geographical subclusters emerging within each industrial sector. We argue that standard techniques for detecting overlapping clusters and communities are not able to capture this type of structure and show how robust regression techniques can instead be used to remove the influence of both sector and geography from the correlation matrix separately. Our analysis reveals that prior to the 2008 financial crisis, companies did not tend to form clusters based on geography. This changed immediately following the crisis, with geography becoming a more important determinant of clustering structure.

Atlas-Guided Cluster Analysis of Large Tractography Datasets

PubMed Central

Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer

2013-01-01

Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment. PMID:24386292

Unsupervised classification of remote multispectral sensing data

NASA Technical Reports Server (NTRS)

Su, M. Y.

1972-01-01

The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement.

Full genome analysis of bovine astrovirus from fecal samples of cattle in Japan: identification of possible interspecies transmission of bovine astrovirus.

PubMed

Nagai, Makoto; Omatsu, Tsutomu; Aoki, Hiroshi; Otomaru, Konosuke; Uto, Takehiko; Koizumi, Motoya; Minami-Fukuda, Fujiko; Takai, Hikaru; Murakami, Toshiaki; Masuda, Tsuneyuki; Yamasato, Hiroshi; Shiokawa, Mai; Tsuchiaka, Shinobu; Naoi, Yuki; Sano, Kaori; Okazaki, Sachiko; Katayama, Yukie; Oba, Mami; Furuya, Tetsuya; Shirai, Junsuke; Mizutani, Tetsuya

2015-10-01

A viral metagenomics approach was used to investigate fecal samples of Japanese calves with and without diarrhea. Of the different viral pathogens detected, read counts gave nearly complete astrovirus-related RNA sequences in 15 of the 146 fecal samples collected in three distinct areas (Hokkaido, Ishikawa, and Kagoshima Prefectures) between 2009 and 2015. Due to the lack of genetic information about bovine astroviruses (BoAstVs) in Japan, these sequences were analyzed in this study. Nine of the 15 Japanese BoAstVs were closely related to Chinese BoAstVs and clustered into a lineage (tentatively named lineage 1) in all phylogenetic trees. Three of 15 strains were phylogenetically separate from lineage 1, showing low sequence identities, and clustered instead with an American strain isolated from cattle with respiratory disease (tentatively named lineage 2). Interestingly, two of 15 strains clustered with lineage 1 in the open reading frame (ORF)1a and ORF1b regions, while they clustered with lineage 2 in the ORF2 region. Remarkably, one of 15 strains exhibited low amino acid sequence similarity to other BoAstVs and was clustered separately with porcine astrovirus type 5 in all trees, and ovine astrovirus in the ORF2 region, suggesting past interspecies transmission.

Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method.

PubMed

Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

2014-07-01

The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous studies. We also compared pairwise distances (between geographically separated samples) with those obtained using the AMOVA method and found good agreement. Further analyses that are impossible with AMOVA were made using the discrete Laplace method: analysis of the homogeneity in two different ways and calculating marginal STR distributions. We found that the Y-STR haplotypes from e.g. Finland were relatively homogeneous as opposed to the relatively heterogeneous Y-STR haplotypes from e.g. Lublin, Eastern Poland and Berlin, Germany. We demonstrated that the observed distributions of alleles at each locus were similar to the expected ones. We also compared pairwise distances between geographically separated samples from Africa with those obtained using the AMOVA method and found good agreement. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The Technical and Biological Reproducibility of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Based Typing: Employment of Bioinformatics in a Multicenter Study.

PubMed

Oberle, Michael; Wohlwend, Nadia; Jonas, Daniel; Maurer, Florian P; Jost, Geraldine; Tschudin-Sutter, Sarah; Vranckx, Katleen; Egli, Adrian

2016-01-01

The technical, biological, and inter-center reproducibility of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI TOF MS) typing data has not yet been explored. The aim of this study is to compare typing data from multiple centers employing bioinformatics using bacterial strains from two past outbreaks and non-related strains. Participants received twelve extended spectrum betalactamase-producing E. coli isolates and followed the same standard operating procedure (SOP) including a full-protein extraction protocol. All laboratories provided visually read spectra via flexAnalysis (Bruker, Germany). Raw data from each laboratory allowed calculating the technical and biological reproducibility between centers using BioNumerics (Applied Maths NV, Belgium). Technical and biological reproducibility ranged between 96.8-99.4% and 47.6-94.4%, respectively. The inter-center reproducibility showed a comparable clustering among identical isolates. Principal component analysis indicated a higher tendency to cluster within the same center. Therefore, we used a discriminant analysis, which completely separated the clusters. Next, we defined a reference center and performed a statistical analysis to identify specific peaks to identify the outbreak clusters. Finally, we used a classifier algorithm and a linear support vector machine on the determined peaks as classifier. A validation showed that within the set of the reference center, the identification of the cluster was 100% correct with a large contrast between the score with the correct cluster and the next best scoring cluster. Based on the sufficient technical and biological reproducibility of MALDI-TOF MS based spectra, detection of specific clusters is possible from spectra obtained from different centers. However, we believe that a shared SOP and a bioinformatics approach are required to make the analysis robust and reliable.

Aqueous Sulfate Separation by Sequestration of [(SO 4) 2(H 2O) 4] 4 Clusters within Highly Insoluble Imine-Linked Bis-Guanidinium Crystals

DOE PAGES

Custelcean, Radu; Williams, Neil J.; Seipp, Charles A.; ...

2015-12-18

Quantitative removal of sulfate from seawater was achieved by selective crystallization of the anion with a bis(guanidinium) ligand self-assembled in situ through imine condensation of simple components. The resulting crystalline salt has an exceptionally low aqueous solubility, on a par with BaSO 4. Single-crystal X-ray diffraction analysis revealed pairs of sulfate anions clustered together with four water molecules within the crystals.

Classification of plant trypanosomatids (Phytomonas spp.): parity between random-primer DNA typing and multilocus enzyme electrophoresis.

PubMed

Muller, E; Gargani, D; Banuls, A L; Tibayrenc, M; Dollet, M

1997-10-01

The genetic polymorphism of 30 isolates of plant trypanosomatids colloquially referred to as plant trypanosomes was assayed by means of RAPD. The principle objectives of this study were to assess the discriminative power of RAPD analysis for studying plant trypanosomes and to determine whether the results obtained were comparable with those from a previous isoenzyme (MLEE) study. The principle groups of plant trypanosomes identified previously by isoenzyme analysis--intraphloemic trypanosomes, intralaticiferous trypanosomes and trypanosomes isolated from fruits--were also clearly separated by the RAPD technique. Moreover, the results showed a fair parity between MLEE and RAPD data (coefficient of correlation = 0.84) and the two techniques have comparable discriminative ability. Most of the separation revealed by the two techniques between the clusters was associated with major biological properties. However, the RAPD technique gave a more coherent separation than MLEE because the intraphloemic isolates, which were biologically similar in terms of their specific localization in the sieve tubes of the plant, were found to be in closer groups by the RAPD. For both techniques, the existence of the main clusters was correlated with the existence of synapomorphic characters, which could be used as powerful tools in taxonomy and epidemiology.

Genetic diversity of Rhizobia isolates from Amazon soils using cowpea (Vigna unguiculata) as trap plant

PubMed Central

Silva, F.V.; Simões-Araújo, J.L.; Silva Júnior, J.P.; Xavier, G.R.; Rumjanek, N.G.

2012-01-01

The aim of this work was to characterize rhizobia isolated from the root nodules of cowpea (Vigna unguiculata) plants cultivated in Amazon soils samples by means of ARDRA (Amplified rDNA Restriction Analysis) and sequencing analysis, to know their phylogenetic relationships. The 16S rRNA gene of rhizobia was amplified by PCR (polymerase chain reaction) using universal primers Y1 and Y3. The amplification products were analyzed by the restriction enzymes HinfI, MspI and DdeI and also sequenced with Y1, Y3 and six intermediate primers. The clustering analysis based on ARDRA profiles separated the Amazon isolates in three subgroups, which formed a group apart from the reference isolates of Bradyrhizobium japonicum and Bradyrhizobium elkanii. The clustering analysis of 16S rRNA gene sequences showed that the fast-growing isolates had similarity with Enterobacter, Rhizobium, Klebsiella and Bradyrhizobium and all the slow-growing clustered close to Bradyrhizobium. PMID:24031880

Population genetics of Vibrio vulnificus: identification of two divisions and a distinct eel-pathogenic clone.

PubMed

Gutacker, Michaela; Conza, Nadine; Benagli, Cinzia; Pedroli, Ambra; Bernasconi, Marco Valerio; Permin, Lise; Aznar, Rosa; Piffaretti, Jean-Claude

2003-06-01

Genetic relationships among 62 Vibrio vulnificus strains of different geographical and host origins were analyzed by multilocus enzyme electrophoresis (MLEE), random amplification of polymorphic DNA (RAPD), and sequence analyses of the recA and glnA genes. Out of 15 genetic loci analyzed by MLEE, 11 were polymorphic. Cluster analysis identified 43 distinct electrophoretic types (ETs) separating the V. vulnificus population into two divisions (divisions I and II). One ET (ET 35) included all indole-negative isolates from diseased eels worldwide (biotype 2). A second ET (ET 2) marked all of the strains from Israel isolated from patients who handled St. Peter's fish (biotype 3). RAPD analysis of the 62 V. vulnificus isolates identified 26 different profiles separated into two divisions as well. In general, this subdivision was comparable (but not identical) to that observed by MLEE. Phylogenetic analysis of 543 bp of the recA gene and of 402 bp of the glnA gene also separated the V. vulnificus population into two major divisions in a manner similar to that by MLEE and RAPD. Sequence data again indicated the overall subdivision of the V. vulnificus population into different biotypes. In particular, indole-negative eel-pathogenic isolates (biotype 2) on one hand and the Israeli isolates (biotype 3) on the other tended to cluster together in both gene trees. None of the methods showed an association between distinct clones and human clinical manifestations. Furthermore, except for the Israeli strains, only minor clusters comprising geographically related isolates were observed. In conclusion, all three approaches (MLEE, RAPD, and DNA sequencing) generated comparable but not always equivalent results. The significance of the two divisions (divisions I and II) still remains to be clarified, and a reevaluation of the definition of the biotypes is also needed.

Metabolomic comparison between wild Ophiocordyceps sinensis and artificial cultured Cordyceps militaris.

PubMed

Chen, Lin; Liu, Yuetao; Guo, Qingfeng; Zheng, Qingxia; Zhang, Wancun

2018-05-11

A systematic study on the metabolome differences between wild Ophiocordyceps sinensis and artificial cultured Cordyceps militaris was conducted using liquid chromatography-mass spectrometry. Principal component analysis and orthogonal projection on latent structure-discriminant analysis results showed that C. militaris grown on solid rice medium (R-CM) and C. militaris grown on tussah pupa (T-CM) evidently separated and individually separated from wild O. sinensis, indicating metabolome difference among wild O. sinensis, R-CM and T-CM. The metabolome differences between R-CM and T-CM indicated that C. militaris could accommodate to culture medium by differential metabolic regulation. Hierarchical clustering analysis was further performed to cluster the differential metabolites and samples based on their metabolic similarity. The higher content of amino acids (pyroglutamic acid, glutamic acid, histidine, phenylalanine and arginine), unsaturated fatty acid (linolenic acid and linoleic acid), peptides, mannitol, adenosine and succinoadenosine in O. sinensis make it as an excellent choice as a traditional Chinese medicine for invigoration or nutritional supplementation. Similar compositions with O. sinensis and easy cultivation make artificially cultured C. militaris a possible alternative to O. sinensis. Copyright © 2018 John Wiley & Sons, Ltd.

Characterization of Erwinia chrysanthemi by pectinolytic isozyme polymorphism and restriction fragment length polymorphism analysis of PCR-amplified fragments of pel genes.

PubMed Central

Nassar, A; Darrasse, A; Lemattre, M; Kotoujansky, A; Dervin, C; Vedel, R; Bertheau, Y

1996-01-01

Conserved regions about 420 bp long of the pelADE cluster specific to Erwinia chrysanthemi were amplified by PCR and used to differentiate 78 strains of E. chrysanthemi that were obtained from different hosts and geographical areas. No PCR products were obtained from DNA samples extracted from other pectinolytic and nonpectinolytic species and genera. The pel fragments amplified from the E. chrysanthemi strains studied were compared by performing a restriction fragment length polymorphism (RFLP) analysis. On the basis of similarity coefficients derived from the RFLP analysis, the strains were separated into 16 PCR RFLP patterns grouped in six clusters, These clusters appeared to be correlated with other infraspecific levels of E. chrysanthemi classification, such as pathovar and biovar, and occasionally with geographical origin. Moreover, the clusters correlated well with the polymorphism of pectate lyase and pectin methylesterase isoenzymes. While the pectin methylesterase profiles correlated with host monocot-dicot classification, the pectate lyase polymorphism might reflect the cell wall microdomains of the plants belonging to these classes. PMID:8779560

Country clustering applied to the water and sanitation sector: a new tool with potential applications in research and policy.

PubMed

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2014-03-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were distinct from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. Copyright © 2013 Elsevier GmbH. All rights reserved.

Multivariate Statistical Analysis of MSL APXS Bulk Geochemical Data

NASA Astrophysics Data System (ADS)

Hamilton, V. E.; Edwards, C. S.; Thompson, L. M.; Schmidt, M. E.

2014-12-01

We apply cluster and factor analyses to bulk chemical data of 130 soil and rock samples measured by the Alpha Particle X-ray Spectrometer (APXS) on the Mars Science Laboratory (MSL) rover Curiosity through sol 650. Multivariate approaches such as principal components analysis (PCA), cluster analysis, and factor analysis compliment more traditional approaches (e.g., Harker diagrams), with the advantage of simultaneously examining the relationships between multiple variables for large numbers of samples. Principal components analysis has been applied with success to APXS, Pancam, and Mössbauer data from the Mars Exploration Rovers. Factor analysis and cluster analysis have been applied with success to thermal infrared (TIR) spectral data of Mars. Cluster analyses group the input data by similarity, where there are a number of different methods for defining similarity (hierarchical, density, distribution, etc.). For example, without any assumptions about the chemical contributions of surface dust, preliminary hierarchical and K-means cluster analyses clearly distinguish the physically adjacent rock targets Windjana and Stephen as being distinctly different than lithologies observed prior to Curiosity's arrival at The Kimberley. In addition, they are separated from each other, consistent with chemical trends observed in variation diagrams but without requiring assumptions about chemical relationships. We will discuss the variation in cluster analysis results as a function of clustering method and pre-processing (e.g., log transformation, correction for dust cover) and implications for interpreting chemical data. Factor analysis shares some similarities with PCA, and examines the variability among observed components of a dataset so as to reveal variations attributable to unobserved components. Factor analysis has been used to extract the TIR spectra of components that are typically observed in mixtures and only rarely in isolation; there is the potential for similar results with data from APXS. These techniques offer new ways to understand the chemical relationships between the materials interrogated by Curiosity, and potentially their relation to materials observed by APXS instruments on other landed missions.

Pattern selection and super-patterns in the bounded confidence model

DOE PAGES

Ben-Naim, E.; Scheel, A.

2015-10-26

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes ofmore » the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. Furthermore, the spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.« less

Pattern selection and super-patterns in the bounded confidence model

NASA Astrophysics Data System (ADS)

Ben-Naim, E.; Scheel, A.

2015-10-01

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued-fraction representation of the irrational average separation L.

Children's loneliness, sense of coherence, family climate, and hope: developmental risk and protective factors.

PubMed

Sharabi, Adi; Levi, Uzi; Margalit, Malka

2012-01-01

The study examined the contributions of individual and familial variables for the prediction of loneliness as a developmental risk and the sense of coherence as a protective factor. The sample consisted of 287 children from grades 5-6. Their loneliness, sense of coherence, hope, effort, and family climate were assessed. Separate hierarchical multiple regression analyses revealed that family cohesion and children's hope contributed to the explanation of the risk and protective outcomes. Yet, the contribution of the family adaptability was not significant. Cluster analysis of the family climate dimensions (i.e., cohesion and adaptability) was performed to clarify the interactive roles of family adaptability together with family cohesion. The authors identified 4 separate family profiles: Children in the 2 cohesive families' clusters (Cohesive Structured Families and Cohesive Adaptable Families) reported the lowest levels of loneliness and the highest levels of personal strengths. Children within rigid and noncohesive family cluster reported the highest levels of loneliness and the lowest levels of children's sense of coherence. The unique role of the family flexibility within nonsupportive family systems was demonstrated. The results further clarified the unique profiles' characteristics of the different family clusters and their adjustment indexes in terms of loneliness and personal strengths.

The fine-scale genetic structure and evolution of the Japanese population.

PubMed

Takeuchi, Fumihiko; Katsuya, Tomohiro; Kimura, Ryosuke; Nabika, Toru; Isomura, Minoru; Ohkubo, Takayoshi; Tabara, Yasuharu; Yamamoto, Ken; Yokota, Mitsuhiro; Liu, Xuanyao; Saw, Woei-Yuh; Mamatyusupu, Dolikun; Yang, Wenjun; Xu, Shuhua; Teo, Yik-Ying; Kato, Norihiro

2017-01-01

The contemporary Japanese populations largely consist of three genetically distinct groups-Hondo, Ryukyu and Ainu. By principal-component analysis, while the three groups can be clearly separated, the Hondo people, comprising 99% of the Japanese, form one almost indistinguishable cluster. To understand fine-scale genetic structure, we applied powerful haplotype-based statistical methods to genome-wide single nucleotide polymorphism data from 1600 Japanese individuals, sampled from eight distinct regions in Japan. We then combined the Japanese data with 26 other Asian populations data to analyze the shared ancestry and genetic differentiation. We found that the Japanese could be separated into nine genetic clusters in our dataset, showing a marked concordance with geography; and that major components of ancestry profile of Japanese were from the Korean and Han Chinese clusters. We also detected and dated admixture in the Japanese. While genetic differentiation between Ryukyu and Hondo was suggested to be caused in part by positive selection, genetic differentiation among the Hondo clusters appeared to result principally from genetic drift. Notably, in Asians, we found the possibility that positive selection accentuated genetic differentiation among distant populations but attenuated genetic differentiation among close populations. These findings are significant for studies of human evolution and medical genetics.

Estimating global distribution of boreal, temperate, and tropical tree plant functional types using clustering techniques

NASA Astrophysics Data System (ADS)

Wang, Audrey; Price, David T.

2007-03-01

A simple integrated algorithm was developed to relate global climatology to distributions of tree plant functional types (PFT). Multivariate cluster analysis was performed to analyze the statistical homogeneity of the climate space occupied by individual tree PFTs. Forested regions identified from the satellite-based GLC2000 classification were separated into tropical, temperate, and boreal sub-PFTs for use in the Canadian Terrestrial Ecosystem Model (CTEM). Global data sets of monthly minimum temperature, growing degree days, an index of climatic moisture, and estimated PFT cover fractions were then used as variables in the cluster analysis. The statistical results for individual PFT clusters were found consistent with other global-scale classifications of dominant vegetation. As an improvement of the quantification of the climatic limitations on PFT distributions, the results also demonstrated overlapping of PFT cluster boundaries that reflected vegetation transitions, for example, between tropical and temperate biomes. The resulting global database should provide a better basis for simulating the interaction of climate change and terrestrial ecosystem dynamics using global vegetation models.

Diversity in aconitine alkaloid profile of Aconitum plants in Hokkaido contrasts with their genetic similarity.

PubMed

Kakiuchi, Nobuko; Atsumi, Toshiyuki; Higuchi, Mari; Kamikawa, Shohei; Miyako, Haruka; Wakita, Yuriko; Ohtsuka, Isao; Hayashi, Shigeki; Hishida, Atsuyuki; Kawahara, Nobuo; Nishizawa, Makoto; Yamagishi, Takashi; Kadota, Yuichi

2015-01-01

Aconite tuber is a representative crude drug for warming the body internally in Japanese Kampo medicine and Chinese traditional medicine. The crude drug is used in major prescriptions for the aged. Varieties of Aconitum plants are distributed throughout the Japanese Islands, especially Hokkaido. With the aim of identifying the medicinal potential of Aconitum plants from Hokkaido, 107 specimens were collected from 36 sites in the summer of 2011 and 2012. Their nuclear DNA region, internal transcribed spacer (ITS), and aconitine alkaloid contents were analyzed. Phylogenic analysis of ITS by maximum parsimony analysis showed that the majority of the specimens were grouped into one cluster (cluster I), separated from the other cluster (cluster II) consisting of alpine specimens. The aconitine alkaloid content of the tuberous roots of 76 specimens showed 2 aspects-specimens from the same collection site showed similar aconitine alkaloid profiles, and cluster I specimens from different habitats showed various alkaloid profiles. Environmental pressure of each habitat is presumed to have caused the morphology and aconitine alkaloid profile of these genetically similar specimens to diversify.

Pathological and non-pathological variants of restrictive eating behaviors in middle childhood: A latent class analysis.

PubMed

Schmidt, Ricarda; Vogel, Mandy; Hiemisch, Andreas; Kiess, Wieland; Hilbert, Anja

2018-08-01

Although restrictive eating behaviors are very common during early childhood, their precise nature and clinical correlates remain unclear. Especially, there is little evidence on restrictive eating behaviors in older children and their associations with children's shape concern. The present population-based study sought to delineate subgroups of restrictive eating patterns in N = 799 7-14 year old children. Using Latent Class Analysis, children were classified based on six restrictive eating behaviors (for example, picky eating, food neophobia, and eating-related anxiety) and shape concern, separately in three age groups. For cluster validation, sociodemographic and objective anthropometric data, parental feeding practices, and general and eating disorder psychopathology were used. The results showed a 3-cluster solution across all age groups: an asymptomatic class (Cluster 1), a class with restrictive eating behaviors without shape concern (Cluster 2), and a class showing restrictive eating behaviors with prominent shape concern (Cluster 3). The clusters differed in all variables used for validation. Particularly, the proportion of children with symptoms of avoidant/restrictive food intake disorder was greater in Cluster 2 than Clusters 1 and 3. The study underlined the importance of considering shape concern to distinguish between different phenotypes of children's restrictive eating patterns. Longitudinal data are needed to evaluate the clusters' predictive effects on children's growth and development of clinical eating disorders. Copyright © 2018 Elsevier Ltd. All rights reserved.

Classification of Marital Relationships: An Empirical Approach.

ERIC Educational Resources Information Center

Snyder, Douglas K.; Smith, Gregory T.

1986-01-01

Derives an empirically based classification system of marital relationships, employing a multidimensional self-report measure of marital interaction. Spouses' profiles on the Marital Satisfaction Inventory for samples of clinic and nonclinic couples were subjected to cluster analysis, resulting in separate five-group typologies for husbands and…

Neuro- and social-cognitive clustering highlights distinct profiles in adults with anorexia nervosa.

PubMed

Renwick, Beth; Musiat, Peter; Lose, Anna; DeJong, Hannah; Broadbent, Hannah; Kenyon, Martha; Loomes, Rachel; Watson, Charlotte; Ghelani, Shreena; Serpell, Lucy; Richards, Lorna; Johnson-Sabine, Eric; Boughton, Nicky; Treasure, Janet; Schmidt, Ulrike

2015-01-01

This study aimed to explore the neuro- and social-cognitive profile of a consecutive series of adult outpatients with anorexia nervosa (AN) when compared with widely available age and gender matched historical control data. The relationship between performance profiles, clinical characteristics, service utilization, and treatment adherence was also investigated. Consecutively recruited outpatients with a broad diagnosis of AN (restricting subtype AN-R: n = 44, binge-purge subtype AN-BP: n = 33 or Eating Disorder Not Otherwise Specified-AN subtype EDNOS-AN: n = 23) completed a comprehensive set of neurocognitive (set-shifting, central coherence) and social-cognitive measures (Emotional Theory of Mind). Data were subjected to hierarchical cluster analysis and a discriminant function analysis. Three separate, meaningful clusters emerged. Cluster 1 (n = 45) showed overall average to high average neuro- and social- cognitive performance, Cluster 2 (n = 38) showed mixed performance characterized by distinct strengths and weaknesses, and Cluster 3 (n = 17) showed poor overall performance (Autism Spectrum disorder (ASD) like cluster). The three clusters did not differ in terms of eating disorder symptoms, comorbid features or service utilization and treatment adherence. A discriminant function analysis confirmed that the clusters were best characterized by performance in perseveration and set-shifting measures. The findings suggest that considerable neuro- and social-cognitive heterogeneity exists in patients with AN, with a subset showing ASD-like features. The value of this method of profiling in predicting longer term patient outcomes and in guiding development of etiologically targeted treatments remains to be seen. © 2014 Wiley Periodicals, Inc.

Discrete Wavelet Transform-Based Whole-Spectral and Subspectral Analysis for Improved Brain Tumor Clustering Using Single Voxel MR Spectroscopy.

PubMed

Yang, Guang; Nawaz, Tahir; Barrick, Thomas R; Howe, Franklyn A; Slabaugh, Greg

2015-12-01

Many approaches have been considered for automatic grading of brain tumors by means of pattern recognition with magnetic resonance spectroscopy (MRS). Providing an improved technique which can assist clinicians in accurately identifying brain tumor grades is our main objective. The proposed technique, which is based on the discrete wavelet transform (DWT) of whole-spectral or subspectral information of key metabolites, combined with unsupervised learning, inspects the separability of the extracted wavelet features from the MRS signal to aid the clustering. In total, we included 134 short echo time single voxel MRS spectra (SV MRS) in our study that cover normal controls, low grade and high grade tumors. The combination of DWT-based whole-spectral or subspectral analysis and unsupervised clustering achieved an overall clustering accuracy of 94.8% and a balanced error rate of 7.8%. To the best of our knowledge, it is the first study using DWT combined with unsupervised learning to cluster brain SV MRS. Instead of dimensionality reduction on SV MRS or feature selection using model fitting, our study provides an alternative method of extracting features to obtain promising clustering results.

Characterisation of colletotrichum species associated with anthracnose of banana.

PubMed

Zakaria, Latiffah; Sahak, Shamsiah; Zakaria, Maziah; Salleh, Baharuddin

2009-12-01

A total of 13 Colletotrichum isolates were obtained from different banana cultivars (Musa spp.) with symptoms of anthracnose. Colletotrichum isolates from anthracnose of guava (Psidium guajava) and water apple (Syzygium aqueum) were also included in this study. Based on cultural and morphological characteristics, isolates from banana and guava were identified as Colletotrichum musae and from water apple as Colletotrichum gloeosporiodes. Isolates of C. musae from banana and guava had similar banding patterns in a randomly amplified polymorphic DNA (RAPD) analysis with four random primers, and they clustered together in a UPGMA analysis. C. gloeosporiodes from water apple was clustered in a separate cluster. Based on the present study, C. musae was frequently isolated from anthracnose of different banana cultivars and the RAPD banding patterns of C. musae isolates were highly similar but showed intraspecific variations.

Characterisation of Colletotrichum Species Associated with Anthracnose of Banana

PubMed Central

Zakaria, Latiffah; Sahak, Shamsiah; Zakaria, Maziah; Salleh, Baharuddin

2009-01-01

A total of 13 Colletotrichum isolates were obtained from different banana cultivars (Musa spp.) with symptoms of anthracnose. Colletotrichum isolates from anthracnose of guava (Psidium guajava) and water apple (Syzygium aqueum) were also included in this study. Based on cultural and morphological characteristics, isolates from banana and guava were identified as Colletotrichum musae and from water apple as Colletotrichum gloeosporiodes. Isolates of C. musae from banana and guava had similar banding patterns in a randomly amplified polymorphic DNA (RAPD) analysis with four random primers, and they clustered together in a UPGMA analysis. C. gloeosporiodes from water apple was clustered in a separate cluster. Based on the present study, C. musae was frequently isolated from anthracnose of different banana cultivars and the RAPD banding patterns of C. musae isolates were highly similar but showed intraspecific variations. PMID:24575184

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

Editing ERTS-1 data to exclude land aids cluster analysis of water targets

NASA Technical Reports Server (NTRS)

Erb, R. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. It has been determined that an increase in the number of spectrally distinct coastal water types is achieved when data values over the adjacent land areas are excluded from the processing routine. This finding resulted from an automatic clustering analysis of ERTS-1 system corrected MSS scene 1002-18134 of 25 July 1972 over Monterey Bay, California. When the entire study area data set was submitted to the clustering only two distinct water classes were extracted. However, when the land area data points were removed from the data set and resubmitted to the clustering routine, four distinct groupings of water features were identified. Additionally, unlike the previous separation, the four types could be correlated to features observable in the associated ERTS-1 imagery. This exercise demonstrates that by proper selection of data submitted to the processing routine, based upon the specific application of study, additional information may be extracted from the ERTS-1 MSS data.

Unsupervised spike sorting based on discriminative subspace learning.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Analysis of genetic diversity in banana cultivars (Musa cvs.) from the South of Oman using AFLP markers and classification by phylogenetic, hierarchical clustering and principal component analyses*

PubMed Central

Opara, Umezuruike Linus; Jacobson, Dan; Al-Saady, Nadiya Abubakar

2010-01-01

Banana is an important crop grown in Oman and there is a dearth of information on its genetic diversity to assist in crop breeding and improvement programs. This study employed amplified fragment length polymorphism (AFLP) to investigate the genetic variation in local banana cultivars from the southern region of Oman. Using 12 primer combinations, a total of 1094 bands were scored, of which 1012 were polymorphic. Eighty-two unique markers were identified, which revealed the distinct separation of the seven cultivars. The results obtained show that AFLP can be used to differentiate the banana cultivars. Further classification by phylogenetic, hierarchical clustering and principal component analyses showed significant differences between the clusters found with molecular markers and those clusters created by previous studies using morphological analysis. Based on the analytical results, a consensus dendrogram of the banana cultivars is presented. PMID:20443211

Reproducibility of Cognitive Profiles in Psychosis Using Cluster Analysis.

PubMed

Lewandowski, Kathryn E; Baker, Justin T; McCarthy, Julie M; Norris, Lesley A; Öngür, Dost

2018-04-01

Cognitive dysfunction is a core symptom dimension that cuts across the psychoses. Recent findings support classification of patients along the cognitive dimension using cluster analysis; however, data-derived groupings may be highly determined by sampling characteristics and the measures used to derive the clusters, and so their interpretability must be established. We examined cognitive clusters in a cross-diagnostic sample of patients with psychosis and associations with clinical and functional outcomes. We then compared our findings to a previous report of cognitive clusters in a separate sample using a different cognitive battery. Participants with affective or non-affective psychosis (n=120) and healthy controls (n=31) were administered the MATRICS Consensus Cognitive Battery, and clinical and community functioning assessments. Cluster analyses were performed on cognitive variables, and clusters were compared on demographic, cognitive, and clinical measures. Results were compared to findings from our previous report. A four-cluster solution provided a good fit to the data; profiles included a neuropsychologically normal cluster, a globally impaired cluster, and two clusters of mixed profiles. Cognitive burden was associated with symptom severity and poorer community functioning. The patterns of cognitive performance by cluster were highly consistent with our previous findings. We found evidence of four cognitive subgroups of patients with psychosis, with cognitive profiles that map closely to those produced in our previous work. Clusters were associated with clinical and community variables and a measure of premorbid functioning, suggesting that they reflect meaningful groupings: replicable, and related to clinical presentation and functional outcomes. (JINS, 2018, 24, 382-390).

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

the-wizz: clustering redshift estimation for everyone

NASA Astrophysics Data System (ADS)

Morrison, C. B.; Hildebrandt, H.; Schmidt, S. J.; Baldry, I. K.; Bilicki, M.; Choi, A.; Erben, T.; Schneider, P.

2017-05-01

We present the-wizz, an open source and user-friendly software for estimating the redshift distributions of photometric galaxies with unknown redshifts by spatially cross-correlating them against a reference sample with known redshifts. The main benefit of the-wizz is in separating the angular pair finding and correlation estimation from the computation of the output clustering redshifts allowing anyone to create a clustering redshift for their sample without the intervention of an 'expert'. It allows the end user of a given survey to select any subsample of photometric galaxies with unknown redshifts, match this sample's catalogue indices into a value-added data file and produce a clustering redshift estimation for this sample in a fraction of the time it would take to run all the angular correlations needed to produce a clustering redshift. We show results with this software using photometric data from the Kilo-Degree Survey (KiDS) and spectroscopic redshifts from the Galaxy and Mass Assembly survey and the Sloan Digital Sky Survey. The results we present for KiDS are consistent with the redshift distributions used in a recent cosmic shear analysis from the survey. We also present results using a hybrid machine learning-clustering redshift analysis that enables the estimation of clustering redshifts for individual galaxies. the-wizz can be downloaded at http://github.com/morriscb/The-wiZZ/.

Marketing a national forest: the resource manager's dilemma

Treesearch

Howard A. Clonts; Jeffrey R. Hibbert

1995-01-01

National Forests throughout the United States are facing critical management decisions regarding optimal resource use amidst strong countervailing pressures for access. Visitors to Talladega National Forest in Alabama were surveyed to develop appropriate marketing strategies. Cluster analysis showed that separate homogeneous user groups exist. This information was...

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Comparison of Salmonella enteritidis phage types isolated from layers and humans in Belgium in 2005.

PubMed

Welby, Sarah; Imberechts, Hein; Riocreux, Flavien; Bertrand, Sophie; Dierick, Katelijne; Wildemauwe, Christa; Hooyberghs, Jozef; Van der Stede, Yves

2011-08-01

The aim of this study was to investigate the available results for Belgium of the European Union coordinated monitoring program (2004/665 EC) on Salmonella in layers in 2005, as well as the results of the monthly outbreak reports of Salmonella Enteritidis in humans in 2005 to identify a possible statistical significant trend in both populations. Separate descriptive statistics and univariate analysis were carried out and the parametric and/or non-parametric hypothesis tests were conducted. A time cluster analysis was performed for all Salmonella Enteritidis phage types (PTs) isolated. The proportions of each Salmonella Enteritidis PT in layers and in humans were compared and the monthly distribution of the most common PT, isolated in both populations, was evaluated. The time cluster analysis revealed significant clusters during the months May and June for layers and May, July, August, and September for humans. PT21, the most frequently isolated PT in both populations in 2005, seemed to be responsible of these significant clusters. PT4 was the second most frequently isolated PT. No significant difference was found for the monthly trend evolution of both PT in both populations based on parametric and non-parametric methods. A similar monthly trend of PT distribution in humans and layers during the year 2005 was observed. The time cluster analysis and the statistical significance testing confirmed these results. Moreover, the time cluster analysis showed significant clusters during the summer time and slightly delayed in time (humans after layers). These results suggest a common link between the prevalence of Salmonella Enteritidis in layers and the occurrence of the pathogen in humans. Phage typing was confirmed to be a useful tool for identifying temporal trends.

Variation of heavy metals in recent sediments from Piratininga Lagoon (Brazil): interpretation of geochemical data with the aid of multivariate analysis

NASA Astrophysics Data System (ADS)

Huang, W.; Campredon, R.; Abrao, J. J.; Bernat, M.; Latouche, C.

1994-06-01

In the last decade, the Atlantic coast of south-eastern Brazil has been affected by increasing deforestation and anthropogenic effluents. Sediments in the coastal lagoons have recorded the process of such environmental change. Thirty-seven sediment samples from three cores in Piratininga Lagoon, Rio de Janeiro, were analyzed for their major components and minor element concentrations in order to examine geochemical characteristics and the depositional environment and to investigate the variation of heavy metals of environmental concern. Two multivariate analysis methods, principal component analysis and cluster analysis, were performed on the analytical data set to help visualize the sample clusters and the element associations. On the whole, the sediment samples from each core are similar and the sample clusters corresponding to the three cores are clearly separated, as a result of the different conditions of sedimentation. Some changes in the depositional environment are recognized using the results of multivariate analysis. The enrichment of Pb, Cu, and Zn in the upper parts of cores is in agreement with increasing anthropogenic influx (pollution).

Optimized Clustering Estimators for BAO Measurements Accounting for Significant Redshift Uncertainty

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

Ross, Ashley J.; Banik, Nilanjan; Avila, Santiago

2017-05-15

We determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the BAO information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line-of-sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertaintymore » $$\\sigma_z \\geq 0.02(1+z)$$ we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for $$\\sigma_z \\geq 0.02(1+z)$$. For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations of galaxy simulations mimicking the Dark Energy Survey Year 1 sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.« less

Preliminary Comparisons of the Information Content and Utility of TM Versus MSS Data

NASA Technical Reports Server (NTRS)

Markham, B. L.

1984-01-01

Comparisons were made between subscenes from the first TM scene acquired of the Washington, D.C. area and a MSS scene acquired approximately one year earlier. Three types of analyses were conducted to compare TM and MSS data: a water body analysis, a principal components analysis and a spectral clustering analysis. The water body analysis compared the capability of the TM to the MSS for detecting small uniform targets. Of the 59 ponds located on aerial photographs 34 (58%) were detected by the TM with six commission errors (15%) and 13 (22%) were detected by the MSS with three commission errors (19%). The smallest water body detected by the TM was 16 meters; the smallest detected by the MSS was 40 meters. For the principal components analysis, means and covariance matrices were calculated for each subscene, and principal components images generated and characterized. In the spectral clustering comparison each scene was independently clustered and the clusters were assigned to informational classes. The preliminary comparison indicated that TM data provides enhancements over MSS in terms of (1) small target detection and (2) data dimensionality (even with 4-band data). The extra dimension, partially resultant from TM band 1, appears useful for built-up/non-built-up area separation.

On the Analysis of Clustering in an Irradiated Low Alloy Reactor Pressure Vessel Steel Weld.

PubMed

Lindgren, Kristina; Stiller, Krystyna; Efsing, Pål; Thuvander, Mattias

2017-04-01

Radiation induced clustering affects the mechanical properties, that is the ductile to brittle transition temperature (DBTT), of reactor pressure vessel (RPV) steel of nuclear power plants. The combination of low Cu and high Ni used in some RPV welds is known to further enhance the DBTT shift during long time operation. In this study, RPV weld samples containing 0.04 at% Cu and 1.6 at% Ni were irradiated to 2.0 and 6.4×1023 n/m2 in the Halden test reactor. Atom probe tomography (APT) was applied to study clustering of Ni, Mn, Si, and Cu. As the clusters are in the nanometer-range, APT is a very suitable technique for this type of study. From APT analyses information about size distribution, number density, and composition of the clusters can be obtained. However, the quantification of these attributes is not trivial. The maximum separation method (MSM) has been used to characterize the clusters and a detailed study about the influence of the choice of MSM cluster parameters, primarily on the cluster number density, has been undertaken.

Infrared spectroscopy reveals both qualitative and quantitative differences in equine subchondral bone during maturation

NASA Astrophysics Data System (ADS)

Kobrina, Yevgeniya; Isaksson, Hanna; Sinisaari, Miikka; Rieppo, Lassi; Brama, Pieter A.; van Weeren, René; Helminen, Heikki J.; Jurvelin, Jukka S.; Saarakkala, Simo

2010-11-01

The collagen phase in bone is known to undergo major changes during growth and maturation. The objective of this study is to clarify whether Fourier transform infrared (FTIR) microspectroscopy, coupled with cluster analysis, can detect quantitative and qualitative changes in the collagen matrix of subchondral bone in horses during maturation and growth. Equine subchondral bone samples (n = 29) from the proximal joint surface of the first phalanx are prepared from two sites subjected to different loading conditions. Three age groups are studied: newborn (0 days old), immature (5 to 11 months old), and adult (6 to 10 years old) horses. Spatial collagen content and collagen cross-link ratio are quantified from the spectra. Additionally, normalized second derivative spectra of samples are clustered using the k-means clustering algorithm. In quantitative analysis, collagen content in the subchondral bone increases rapidly between the newborn and immature horses. The collagen cross-link ratio increases significantly with age. In qualitative analysis, clustering is able to separate newborn and adult samples into two different groups. The immature samples display some nonhomogeneity. In conclusion, this is the first study showing that FTIR spectral imaging combined with clustering techniques can detect quantitative and qualitative changes in the collagen matrix of subchondral bone during growth and maturation.

Transverse Dimensions of Chorus in the Source Region

NASA Technical Reports Server (NTRS)

Santolik, O.; Gurnett, D. A.

2003-01-01

We report measurement of whistler-mode chorus by the four Cluster spacecraft at close separations. We focus our analysis on the generation region close to the magnetic equatorial plane at a radial distance of 4.4 Earth's radii. We use both linear and rank correlation analysis to define perpendicular dimensions of the sources of chorus elements below one half of the electron cyclotron frequency. Correlation is significant throughout the range of separation distances of 60-260 km parallel to the field line and 7-100 km in the perpendicular plane. At these scales, the correlation coefficient is independent for parallel separations, and decreases with perpendicular separation. The observations are consistent with a statistical model of the source region assuming individual sources as gaussian peaks of radiated power with a common half-width of 35 km perpendicular to the magnetic field. This characteristic scale is comparable to the wavelength of observed waves.

An analysis of genetic architecture in populations of Ponderosa Pine

Treesearch

Yan B. Linhart; Jeffry B. Mitton; Kareen B. Sturgeon; Martha L. Davis

1981-01-01

Patterns of genetic variation were studied in three populations of ponderosa pine in Colorado by using electrophoretically variable protein loci. Significant genetic differences were found between separate clusters of trees and between age classes within populations. In addition, data indicate that differential cone production and differential animal damage have...

Antagonists in Mutual Antipathies: A Person-Oriented Approach

ERIC Educational Resources Information Center

Guroglu, Berna; Haselager, Gerbert J. T.; van Lieshout, Cornelis F. M.; Scholte, Ron H. J.

2009-01-01

This study investigated the heterogeneity of mutual antipathy relationships. Separate cluster analyses of peer interactions of early adolescents (mean age 11 years) and adolescents (mean age of 14) yielded 3 "types of individuals" in each age group, namely Prosocial, Antisocial, and Withdrawn. Prevalence analysis of the 6 possible combinations of…

Genetic diversity of red-grained rice landraces in Hani's terraced fields based on phenotypic characteristics

NASA Astrophysics Data System (ADS)

Zhou, Xiaomei; Zheng, Yun; Zhang, Tingting; Zhang, Xiaoqian; Ma, Mengli; Meng, Hengling; Wang, Tiantao; Lu, Bingyue

2018-06-01

In order to provide useful information for protection and utilization of red-grained rice landraces from Hani's terraced fields, the phenotypic diversity of 61 red-grained rice landraces were assessed based 20 quantitative traits. The results indicated that the phenotypic diversity was abundant in red-grained rice landraces. Coefficients of variation (CV) ranged from 4.878% to 72.878%, and the largest of CV was the panicle neck length, while grain width was smallest. Shannon-Weaver diversity index (H') of 20 traits ranged from 1.464 to 2.165, the largest and the smallest H' values were observed in filled grain number and chalkiness, respectively. Cluster analysis based on unweighted pair group method showed 61 red-grain rice landraces grouped into eight clusters at a cut-off value of 6.2631. The first cluster included 11 landraces, the main cluster II involved 42 landraces, and the cluster IV included 3 landraces. Laopinzhonghongmi, Chena2, Laojingnuo, Bianhao6 and Baimi were separated from the main clusters.

Extraction of the number of peroxisomes in yeast cells by automated image analysis.

PubMed

Niemistö, Antti; Selinummi, Jyrki; Saleem, Ramsey; Shmulevich, Ilya; Aitchison, John; Yli-Harja, Olli

2006-01-01

An automated image analysis method for extracting the number of peroxisomes in yeast cells is presented. Two images of the cell population are required for the method: a bright field microscope image from which the yeast cells are detected and the respective fluorescent image from which the number of peroxisomes in each cell is found. The segmentation of the cells is based on clustering the local mean-variance space. The watershed transformation is thereafter employed to separate cells that are clustered together. The peroxisomes are detected by thresholding the fluorescent image. The method is tested with several images of a budding yeast Saccharomyces cerevisiae population, and the results are compared with manually obtained results.

A New Classification of Diabetic Gait Pattern Based on Cluster Analysis of Biomechanical Data

PubMed Central

Sawacha, Zimi; Guarneri, Gabriella; Avogaro, Angelo; Cobelli, Claudio

2010-01-01

Background The diabetic foot, one of the most serious complications of diabetes mellitus and a major risk factor for plantar ulceration, is determined mainly by peripheral neuropathy. Neuropathic patients exhibit decreased stability while standing as well as during dynamic conditions. A new methodology for diabetic gait pattern classification based on cluster analysis has been proposed that aims to identify groups of subjects with similar patterns of gait and verify if three-dimensional gait data are able to distinguish diabetic gait patterns from one of the control subjects. Method The gait of 20 nondiabetic individuals and 46 diabetes patients with and without peripheral neuropathy was analyzed [mean age 59.0 (2.9) and 61.1(4.4) years, mean body mass index (BMI) 24.0 (2.8), and 26.3 (2.0)]. K-means cluster analysis was applied to classify the subjects' gait patterns through the analysis of their ground reaction forces, joints and segments (trunk, hip, knee, ankle) angles, and moments. Results Cluster analysis classification led to definition of four well-separated clusters: one aggregating just neuropathic subjects, one aggregating both neuropathics and non-neuropathics, one including only diabetes patients, and one including either controls or diabetic and neuropathic subjects. Conclusions Cluster analysis was useful in grouping subjects with similar gait patterns and provided evidence that there were subgroups that might otherwise not be observed if a group ensemble was presented for any specific variable. In particular, we observed the presence of neuropathic subjects with a gait similar to the controls and diabetes patients with a long disease duration with a gait as altered as the neuropathic one. PMID:20920432

Study on transport infrastructure as mechanism of long-term urban planning strategies

NASA Astrophysics Data System (ADS)

Popova, Olga; Martynov, Kirill; Khusnutdinov, Rinat

2017-10-01

In this article, the authors carry out the research of the transport infrastructure. The authors have developed an algorithm for quality assessment of transport networks and connectivity of urban development areas. The results of the research are presented on the example of several central city quarters of Arkhangelsk city. The analysis was carried out by clustering objects (separate quarters of the Arkhangelsk city) using of SOM in comparable groups with a high level of similarity of characteristics inside each group. The result of clustering was 5 clusters with different levels of transport infrastructure. The novelty of the study is to justification for advantages of applying structural analysis for qualitative ranking of areas. The advantage of the proposed methodology is that it gives the opportunity both to compare the transport infrastructure quality of different city quarters and to determine the strategy for its development with a list of specific activities.

Key-Node-Separated Graph Clustering and Layouts for Human Relationship Graph Visualization.

PubMed

Itoh, Takayuki; Klein, Karsten

2015-01-01

Many graph-drawing methods apply node-clustering techniques based on the density of edges to find tightly connected subgraphs and then hierarchically visualize the clustered graphs. However, users may want to focus on important nodes and their connections to groups of other nodes for some applications. For this purpose, it is effective to separately visualize the key nodes detected based on adjacency and attributes of the nodes. This article presents a graph visualization technique for attribute-embedded graphs that applies a graph-clustering algorithm that accounts for the combination of connections and attributes. The graph clustering step divides the nodes according to the commonality of connected nodes and similarity of feature value vectors. It then calculates the distances between arbitrary pairs of clusters according to the number of connecting edges and the similarity of feature value vectors and finally places the clusters based on the distances. Consequently, the technique separates important nodes that have connections to multiple large clusters and improves the visibility of such nodes' connections. To test this technique, this article presents examples with human relationship graph datasets, including a coauthorship and Twitter communication network dataset.

Amide-induced phase separation of hexafluoroisopropanol-water mixtures depending on the hydrophobicity of amides.

PubMed

Takamuku, Toshiyuki; Wada, Hiroshi; Kawatoko, Chiemi; Shimomura, Takuya; Kanzaki, Ryo; Takeuchi, Munetaka

2012-06-21

Amide-induced phase separation of hexafluoro-2-propanol (HFIP)-water mixtures has been investigated to elucidate solvation properties of the mixtures by means of small-angle neutron scattering (SANS), (1)H and (13)C NMR, and molecular dynamics (MD) simulation. The amides included N-methylformamide (NMF), N-methylacetamide (NMA), and N-methylpropionamide (NMP). The phase diagrams of amide-HFIP-water ternary systems at 298 K showed that phase separation occurs in a closed-loop area of compositions as well as an N,N-dimethylformamide (DMF) system previously reported. The phase separation area becomes wider as the hydrophobicity of amides increases in the order of NMF < NMA < DMF < NMP. Thus, the evolution of HFIP clusters around amides due to the hydrophobic interaction gives rise to phase separation of the mixtures. In contrast, the disruption of HFIP clusters causes the recovery of the homogeneity of the ternary systems. The present results showed that HFIP clusters are evolved with increasing amide content to the lower phase separation concentration in the same mechanism among the four amide systems. However, the disruption of HFIP clusters in the NMP and DMF systems with further increasing amide content to the upper phase separation concentration occurs in a different way from those in the NMF and NMA systems.

An approach to functionally relevant clustering of the protein universe: Active site profile‐based clustering of protein structures and sequences

PubMed Central

Knutson, Stacy T.; Westwood, Brian M.; Leuthaeuser, Janelle B.; Turner, Brandon E.; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D.; Harper, Angela F.; Brown, Shoshana D.; Morris, John H.; Ferrin, Thomas E.; Babbitt, Patricia C.

2017-01-01

Abstract Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification—amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two‐Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure‐Function Linkage Database, SFLD) self‐identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self‐identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well‐curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP‐identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F‐measure and performance analysis on the enolase search results and comparison to GEMMA and SCI‐PHY demonstrate that TuLIP avoids the over‐division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. PMID:28054422

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Size exclusion chromatography for semipreparative scale separation of Au38(SR)24 and Au40(SR)24 and larger clusters.

PubMed

Knoppe, Stefan; Boudon, Julien; Dolamic, Igor; Dass, Amala; Bürgi, Thomas

2011-07-01

Size exclusion chromatography (SEC) on a semipreparative scale (10 mg and more) was used to size-select ultrasmall gold nanoclusters (<2 nm) from polydisperse mixtures. In particular, the ubiquitous byproducts of the etching process toward Au(38)(SR)(24) (SR, thiolate) clusters were separated and gained in high monodispersity (based on mass spectrometry). The isolated fractions were characterized by UV-vis spectroscopy, MALDI mass spectrometry, HPLC, and electron microscopy. Most notably, the separation of Au(38)(SR)(24) and Au(40)(SR)(24) clusters is demonstrated.

Development of a picture of the van der Waals interaction energy between clusters of nanometer-range particles

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

Arunachalam, V.; Marlow, W.H.; Lu, J.X.

1998-09-01

The importance of the long-range Lifshitz{endash}van der Waals interaction energy between condensed bodies is well known. However, its implementation for interacting bodies that are highly irregular and separated by distances varying from contact to micrometers has received little attention. As part of a study of collisions of irregular aerosol particles, an approach based on the Lifshitz theory of van der Waals interaction has been developed to compute the interaction energy between a sphere and an aggregate of spheres at all separations. In the first part of this study, the iterated sum-over-dipole interactions between pairs of approximately spherical molecular clusters aremore » compared with the Lifshitz and Lifshitz-Hamaker interaction energies for continuum spheres of radii equal to those of the clusters{close_quote} circumscribed spheres and of the same masses as the clusters. The Lifshitz energy is shown to converge to the iterated dipolar energy for quasispherical molecular clusters for sufficiently large separations, while the energy calculated by using the Lifshitz-Hamaker approach does not. Next, the interaction energies between a contacting pair of these molecular clusters and a third cluster in different relative positions are calculated first by coupling all molecules in the three-cluster system and second by ignoring the interactions between the molecules of the adhering clusters. The error calculated by this omission is shown to be very small, and is an indication of the error in computing the long-range interaction energy between a pair of interacting spheres and a third sphere as a simple sum over the Lifshitz energies between individual, condensed-matter spheres. This Lifshitz energy calculation is then combined with the short-separation, nonsingular van der Waals energy calculation of Lu, Marlow, and Arunachalam, to provide an integrated picture of the van der Waals energy from large separations to contact. {copyright} {ital 1998} {ital The American Physical Society}« less

High- and low-level hierarchical classification algorithm based on source separation process

NASA Astrophysics Data System (ADS)

Loghmari, Mohamed Anis; Karray, Emna; Naceur, Mohamed Saber

2016-10-01

High-dimensional data applications have earned great attention in recent years. We focus on remote sensing data analysis on high-dimensional space like hyperspectral data. From a methodological viewpoint, remote sensing data analysis is not a trivial task. Its complexity is caused by many factors, such as large spectral or spatial variability as well as the curse of dimensionality. The latter describes the problem of data sparseness. In this particular ill-posed problem, a reliable classification approach requires appropriate modeling of the classification process. The proposed approach is based on a hierarchical clustering algorithm in order to deal with remote sensing data in high-dimensional space. Indeed, one obvious method to perform dimensionality reduction is to use the independent component analysis process as a preprocessing step. The first particularity of our method is the special structure of its cluster tree. Most of the hierarchical algorithms associate leaves to individual clusters, and start from a large number of individual classes equal to the number of pixels; however, in our approach, leaves are associated with the most relevant sources which are represented according to mutually independent axes to specifically represent some land covers associated with a limited number of clusters. These sources contribute to the refinement of the clustering by providing complementary rather than redundant information. The second particularity of our approach is that at each level of the cluster tree, we combine both a high-level divisive clustering and a low-level agglomerative clustering. This approach reduces the computational cost since the high-level divisive clustering is controlled by a simple Boolean operator, and optimizes the clustering results since the low-level agglomerative clustering is guided by the most relevant independent sources. Then at each new step we obtain a new finer partition that will participate in the clustering process to enhance semantic capabilities and give good identification rates.

Gas and galaxies in filaments between clusters of galaxies. The study of A399-A401

NASA Astrophysics Data System (ADS)

Bonjean, V.; Aghanim, N.; Salomé, P.; Douspis, M.; Beelen, A.

2018-01-01

We have performed a multi-wavelength analysis of two galaxy cluster systems selected with the thermal Sunyaev-Zel'dovich (tSZ) effect and composed of cluster pairs and an inter-cluster filament. We have focused on one pair of particular interest: A399-A401 at redshift z 0.073 seperated by 3 Mpc. We have also performed the first analysis of one lower-significance newly associated pair: A21-PSZ2 G114.09-34.34 at z 0.094, separated by 4.2 Mpc. We have characterised the intra-cluster gas using the tSZ signal from Planck and, when possible, the galaxy optical and infrared (IR) properties based on two photometric redshift catalogues: 2MPZ and WISExSCOS. From the tSZ data, we measured the gas pressure in the clusters and in the inter-cluster filaments. In the case of A399-A401, the results are in perfect agreement with previous studies and, using the temperature measured from the X-rays, we further estimate the gas density in the filament and find n0 = (4.3 ± 0.7) × 10-4 cm-3. The optical and IR colour-colour and colour-magnitude analyses of the galaxies selected in the cluster system, together with their star formation rate, show no segregation between galaxy populations, both in the clusters and in the filament of A399-A401. Galaxies are all passive, early type, and red and dead. The gas and galaxy properties of this system suggest that the whole system formed at the same time and corresponds to a pre-merger, with a cosmic filament gas heated by the collapse. For the other cluster system, the tSZ analysis was performed and the pressure in the clusters and in the inter-cluster filament was constrained. However, the limited or nonexistent optical and IR data prevent us from concluding on the presence of an actual cosmic filament or from proposing a scenario.

Genetic differentiation of chinese indigenous meat goats ascertained using microsatellite information.

PubMed

Ling, Y H; Zhang, X D; Yao, N; Ding, J P; Chen, H Q; Zhang, Z J; Zhang, Y H; Ren, C H; Ma, Y H; Zhang, X R

2012-02-01

To investigate the genetic diversity of seven Chinese indigenous meat goat breeds (Tibet goat, Guizhou white goat, Shannan white goat, Yichang white goat, Matou goat, Changjiangsanjiaozhou white goat and Anhui white goat), explain their genetic relationship and assess their integrity and degree of admixture, 302 individuals from these breeds and 42 Boer goats introduced from Africa as reference samples were genotyped for 11 microsatellite markers. Results indicated that the genetic diversity of Chinese indigenous meat goats was rich. The mean heterozygosity and the mean allelic richness (AR) for the 8 goat breeds varied from 0.697 to 0.738 and 6.21 to 7.35, respectively. Structure analysis showed that Tibet goat breed was genetically distinct and was the first to separate and the other Chinese goats were then divided into two sub-clusters: Shannan white goat and Yichang white goat in one cluster; and Guizhou white goat, Matou goat, Changjiangsanjiaozhou white goat and Anhui white goat in the other cluster. This grouping pattern was further supported by clustering analysis and Principal component analysis. These results may provide a scientific basis for the characteristization, conservation and utilization of Chinese meat goats.

Phylogeny of kemenyan (Styrax sp.) from North Sumatra based on morphological characters

NASA Astrophysics Data System (ADS)

Susilowati, A.; Kholibrina, C. R.; Rachmat, H. H.; Munthe, M. A.

2018-02-01

Kemenyan is the most famous local tree species from North Sumatra. Kemenyan is known as rosin producer that very valuable for pharmacheutical, cosmetic, food preservatives and vernis. Based on its history, there were only two species of kemenyan those were kemenyan durame and toba, but in its the natural distribution we also found others species showing different characteristics with previously known ones. The objectives of this research were:The objectives of this research were: (1). To determine the morphological diversity of kemenyan in North Sumatra and (2). To determine phylogeny clustering based on the morphological characters. Data was collected from direct observation and morphological characterization, based on purposive sampling technique to those samples trees atPakpak Bharat, North Sumatra. Morphological characters were examined using descriptive analysis, phenotypic variability using standard deviation, and cluster analysis. The result showed that there was a difference between 4 species kemenyen (batak, minyak, durame and toba) according to 75 observed characters including flower, fruits, leaf, stem, bark, crown type, wood and the resin. Analysis and both quantitative and qualitative characters kemenyan clustered into two groups. In which, kemenyan toba separated with other clusters.

Cluster analysis of cognitive performance in elderly and demented subjects.

PubMed

Giaquinto, S; Nolfe, G; Calvani, M

1985-06-01

48 elderly normals, 14 demented subjects and 76 young controls were tested for basic cognitive functions. All the tests were quantified and could therefore be subjected to statistical analysis. The results show a difference in the speed of information processing and in memory load between the young controls and elderly normals but the age groups differed in quantitative terms only. Cluster analysis showed that the elderly and the demented formed two distinctly separate groups at the qualitative level, the basic cognitive processes being damaged in the demented group. Age thus appears to be only a risk factor for dementia and not its cause. It is concluded that batteries based on precise and measurable tasks are the most appropriate not only for the study of dementia but for rehabilitation purposes too.

The Technical and Biological Reproducibility of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Based Typing: Employment of Bioinformatics in a Multicenter Study

PubMed Central

Oberle, Michael; Wohlwend, Nadia; Jonas, Daniel; Maurer, Florian P.; Jost, Geraldine; Tschudin-Sutter, Sarah; Vranckx, Katleen; Egli, Adrian

2016-01-01

Background The technical, biological, and inter-center reproducibility of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI TOF MS) typing data has not yet been explored. The aim of this study is to compare typing data from multiple centers employing bioinformatics using bacterial strains from two past outbreaks and non-related strains. Material/Methods Participants received twelve extended spectrum betalactamase-producing E. coli isolates and followed the same standard operating procedure (SOP) including a full-protein extraction protocol. All laboratories provided visually read spectra via flexAnalysis (Bruker, Germany). Raw data from each laboratory allowed calculating the technical and biological reproducibility between centers using BioNumerics (Applied Maths NV, Belgium). Results Technical and biological reproducibility ranged between 96.8–99.4% and 47.6–94.4%, respectively. The inter-center reproducibility showed a comparable clustering among identical isolates. Principal component analysis indicated a higher tendency to cluster within the same center. Therefore, we used a discriminant analysis, which completely separated the clusters. Next, we defined a reference center and performed a statistical analysis to identify specific peaks to identify the outbreak clusters. Finally, we used a classifier algorithm and a linear support vector machine on the determined peaks as classifier. A validation showed that within the set of the reference center, the identification of the cluster was 100% correct with a large contrast between the score with the correct cluster and the next best scoring cluster. Conclusions Based on the sufficient technical and biological reproducibility of MALDI-TOF MS based spectra, detection of specific clusters is possible from spectra obtained from different centers. However, we believe that a shared SOP and a bioinformatics approach are required to make the analysis robust and reliable. PMID:27798637

Improving estimation of kinetic parameters in dynamic force spectroscopy using cluster analysis

NASA Astrophysics Data System (ADS)

Yen, Chi-Fu; Sivasankar, Sanjeevi

2018-03-01

Dynamic Force Spectroscopy (DFS) is a widely used technique to characterize the dissociation kinetics and interaction energy landscape of receptor-ligand complexes with single-molecule resolution. In an Atomic Force Microscope (AFM)-based DFS experiment, receptor-ligand complexes, sandwiched between an AFM tip and substrate, are ruptured at different stress rates by varying the speed at which the AFM-tip and substrate are pulled away from each other. The rupture events are grouped according to their pulling speeds, and the mean force and loading rate of each group are calculated. These data are subsequently fit to established models, and energy landscape parameters such as the intrinsic off-rate (koff) and the width of the potential energy barrier (xβ) are extracted. However, due to large uncertainties in determining mean forces and loading rates of the groups, errors in the estimated koff and xβ can be substantial. Here, we demonstrate that the accuracy of fitted parameters in a DFS experiment can be dramatically improved by sorting rupture events into groups using cluster analysis instead of sorting them according to their pulling speeds. We test different clustering algorithms including Gaussian mixture, logistic regression, and K-means clustering, under conditions that closely mimic DFS experiments. Using Monte Carlo simulations, we benchmark the performance of these clustering algorithms over a wide range of koff and xβ, under different levels of thermal noise, and as a function of both the number of unbinding events and the number of pulling speeds. Our results demonstrate that cluster analysis, particularly K-means clustering, is very effective in improving the accuracy of parameter estimation, particularly when the number of unbinding events are limited and not well separated into distinct groups. Cluster analysis is easy to implement, and our performance benchmarks serve as a guide in choosing an appropriate method for DFS data analysis.

The fine-scale genetic structure and evolution of the Japanese population

PubMed Central

Katsuya, Tomohiro; Kimura, Ryosuke; Nabika, Toru; Isomura, Minoru; Ohkubo, Takayoshi; Tabara, Yasuharu; Yamamoto, Ken; Yokota, Mitsuhiro; Liu, Xuanyao; Saw, Woei-Yuh; Mamatyusupu, Dolikun; Yang, Wenjun; Xu, Shuhua

2017-01-01

The contemporary Japanese populations largely consist of three genetically distinct groups—Hondo, Ryukyu and Ainu. By principal-component analysis, while the three groups can be clearly separated, the Hondo people, comprising 99% of the Japanese, form one almost indistinguishable cluster. To understand fine-scale genetic structure, we applied powerful haplotype-based statistical methods to genome-wide single nucleotide polymorphism data from 1600 Japanese individuals, sampled from eight distinct regions in Japan. We then combined the Japanese data with 26 other Asian populations data to analyze the shared ancestry and genetic differentiation. We found that the Japanese could be separated into nine genetic clusters in our dataset, showing a marked concordance with geography; and that major components of ancestry profile of Japanese were from the Korean and Han Chinese clusters. We also detected and dated admixture in the Japanese. While genetic differentiation between Ryukyu and Hondo was suggested to be caused in part by positive selection, genetic differentiation among the Hondo clusters appeared to result principally from genetic drift. Notably, in Asians, we found the possibility that positive selection accentuated genetic differentiation among distant populations but attenuated genetic differentiation among close populations. These findings are significant for studies of human evolution and medical genetics. PMID:29091727

Identification of Clinical Phenotypes in Idiopathic Interstitial Pneumonia with Pulmonary Emphysema.

PubMed

Sato, Suguru; Tanino, Yoshinori; Misa, Kenichi; Fukuhara, Naoko; Nikaido, Takefumi; Uematsu, Manabu; Fukuhara, Atsuro; Wang, Xintao; Ishida, Takashi; Munakata, Mitsuru

2016-01-01

Objective Since the term "combined pulmonary fibrosis and emphysema" (CPFE) was first proposed, the co-existence of pulmonary fibrosis and pulmonary emphysema (PE) has drawn considerable attention. However, conflicting results on the clinical characteristics of patients with both pulmonary fibrosis and PE have been published because of the lack of an exact definition of CPFE. The goal of this study was thus to clarify the clinical characteristics and phenotypes of idiopathic interstitial pneumonia (IIP) with PE. Methods We retrospectively analyzed IIP patients who had been admitted to our hospital. Their chest high-resolution computed tomography images were classified into two groups according to the presence of PE. We then performed a cluster analysis to identify the phenotypes of IIP patients with PE. Results Forty-four (53.7%) out of 82 patients had at least mild emphysema in their bilateral lungs. The cluster analysis separated the IIP patients with PE into three clusters. The overall survival rate of one cluster that consisted of mainly idiopathic pulmonary fibrosis (IPF) patients was significantly worse than those of the other clusters. Conclusion Three different phenotypes can be identified in IIP patients with PE, and IPF with PE is a distinct clinical phenotype with a poor prognosis.

Combinations of Personal Responsibility: Differences on Pre-service and Practicing Teachers’ Efficacy, Engagement, Classroom Goal Structures and Wellbeing

PubMed Central

Daniels, Lia M.; Radil, Amanda I.; Goegan, Lauren D.

2017-01-01

Pre-service and practicing teachers feel responsible for a range of educational activities. Four domains of personal responsibility emerging in the literature are: student achievement, student motivation, relationships with students, and responsibility for ones own teaching. To date, most research has used variable-centered approaches to examining responsibilities even though the domains appear related. In two separate samples we used cluster analysis to explore how pre-service (n = 130) and practicing (n = 105) teachers combined personal responsibilities and their impact on three professional cognitions and their wellbeing. Both groups had low and high responsibility clusters but the third cluster differed: Pre-service teachers combined responsibilities for relationships and their own teaching in a cluster we refer to as teacher-based responsibility; whereas, practicing teachers combined achievement and motivation in a cluster we refer to as student-outcome focused responsibility. These combinations affected outcomes for pre-service but not practicing teachers. Pre-service teachers in the low responsibility cluster reported less engagement, less mastery approaches to instruction, and more performance goal structures than the other two clusters. PMID:28620332

Investigation of defect clusters in ion-irradiated Ni and NiCo using diffuse X-ray scattering and electron microscopy

DOE PAGES

Olsen, Raina J.; Jin, Ke; Lu, Chenyang; ...

2015-11-23

The nature of defect clusters in Ni and Nimore » $$_{50}$$Co$$_{50}$$ (NiCo) irradiated at room temperature with 2–16 MeV Ni ions is studied using asymptotic diffuse X-ray scattering and transmission electron microscopy (TEM). Analysis of the scattering data provides separate size distributions for vacancy and interstitial type defect clusters, showing that both types of defect clusters have a smaller size and higher density in NiCo than in Ni. Diffuse scattering results show good quantitative agreement with TEM results for cluster sizes greater than 4 nm diameter, but find that the majority of vacancy clusters are under 2 nm in NiCo, which, if not detected, would lead to the conclusion that defect density was actually lower in the alloy. Interstitial dislocation loops and stacking fault tetrahedra are identified by TEM. Lastly comparison of diffuse scattering lineshapes to those calculated for dislocation loops and SFTs indicates that most of the vacancy clusters are SFTs.« less

Combinations of Personal Responsibility: Differences on Pre-service and Practicing Teachers' Efficacy, Engagement, Classroom Goal Structures and Wellbeing.

PubMed

Daniels, Lia M; Radil, Amanda I; Goegan, Lauren D

2017-01-01

Pre-service and practicing teachers feel responsible for a range of educational activities. Four domains of personal responsibility emerging in the literature are: student achievement, student motivation, relationships with students, and responsibility for ones own teaching. To date, most research has used variable-centered approaches to examining responsibilities even though the domains appear related. In two separate samples we used cluster analysis to explore how pre-service ( n = 130) and practicing ( n = 105) teachers combined personal responsibilities and their impact on three professional cognitions and their wellbeing. Both groups had low and high responsibility clusters but the third cluster differed: Pre-service teachers combined responsibilities for relationships and their own teaching in a cluster we refer to as teacher-based responsibility; whereas, practicing teachers combined achievement and motivation in a cluster we refer to as student-outcome focused responsibility. These combinations affected outcomes for pre-service but not practicing teachers. Pre-service teachers in the low responsibility cluster reported less engagement, less mastery approaches to instruction, and more performance goal structures than the other two clusters.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

PubMed

Lee, Hyejoo; Malaspina, Dolores; Ahn, Hongshik; Perrin, Mary; Opler, Mark G; Kleinhaus, Karine; Harlap, Susan; Goetz, Raymond; Antonius, Daniel

2011-05-01

Paternal age related schizophrenia (PARS) has been proposed as a subgroup of schizophrenia with distinct etiology, pathophysiology and symptoms. This study uses a k-means clustering analysis approach to generate hypotheses about differences between PARS and other cases of schizophrenia. We studied PARS (operationally defined as not having any family history of schizophrenia among first and second-degree relatives and fathers' age at birth ≥ 35 years) in a series of schizophrenia cases recruited from a research unit. Data were available on demographic variables, symptoms (Positive and Negative Syndrome Scale; PANSS), cognitive tests (Wechsler Adult Intelligence Scale-Revised; WAIS-R) and olfaction (University of Pennsylvania Smell Identification Test; UPSIT). We conducted a series of k-means clustering analyses to identify clusters of cases containing high concentrations of PARS. Two analyses generated clusters with high concentrations of PARS cases. The first analysis (N=136; PARS=34) revealed a cluster containing 83% PARS cases, in which the patients showed a significant discrepancy between verbal and performance intelligence. The mean paternal and maternal ages were 41 and 33, respectively. The second analysis (N=123; PARS=30) revealed a cluster containing 71% PARS cases, of which 93% were females; the mean age of onset of psychosis, at 17.2, was significantly early. These results strengthen the evidence that PARS cases differ from other patients with schizophrenia. Hypothesis-generating findings suggest that features of PARS may include a discrepancy between verbal and performance intelligence, and in females, an early age of onset. These findings provide a rationale for separating these phenotypes from others in future clinical, genetic and pathophysiologic studies of schizophrenia and in considering responses to treatment. Copyright © 2011 Elsevier B.V. All rights reserved.

Multi-band morpho-Spectral Component Analysis Deblending Tool (MuSCADeT): Deblending colourful objects

NASA Astrophysics Data System (ADS)

Joseph, R.; Courbin, F.; Starck, J.-L.

2016-05-01

We introduce a new algorithm for colour separation and deblending of multi-band astronomical images called MuSCADeT which is based on Morpho-spectral Component Analysis of multi-band images. The MuSCADeT algorithm takes advantage of the sparsity of astronomical objects in morphological dictionaries such as wavelets and their differences in spectral energy distribution (SED) across multi-band observations. This allows us to devise a model independent and automated approach to separate objects with different colours. We show with simulations that we are able to separate highly blended objects and that our algorithm is robust against SED variations of objects across the field of view. To confront our algorithm with real data, we use HST images of the strong lensing galaxy cluster MACS J1149+2223 and we show that MuSCADeT performs better than traditional profile-fitting techniques in deblending the foreground lensing galaxies from background lensed galaxies. Although the main driver for our work is the deblending of strong gravitational lenses, our method is fit to be used for any purpose related to deblending of objects in astronomical images. An example of such an application is the separation of the red and blue stellar populations of a spiral galaxy in the galaxy cluster Abell 2744. We provide a python package along with all simulations and routines used in this paper to contribute to reproducible research efforts. Codes can be found at http://lastro.epfl.ch/page-126973.html

Characterizing Suicide in Toronto: An Observational Study and Cluster Analysis

PubMed Central

Sinyor, Mark; Schaffer, Ayal; Streiner, David L

2014-01-01

Objective: To determine whether people who have died from suicide in a large epidemiologic sample form clusters based on demographic, clinical, and psychosocial factors. Method: We conducted a coroner’s chart review for 2886 people who died in Toronto, Ontario, from 1998 to 2010, and whose death was ruled as suicide by the Office of the Chief Coroner of Ontario. A cluster analysis using known suicide risk factors was performed to determine whether suicide deaths separate into distinct groups. Clusters were compared according to person- and suicide-specific factors. Results: Five clusters emerged. Cluster 1 had the highest proportion of females and nonviolent methods, and all had depression and a past suicide attempt. Cluster 2 had the highest proportion of people with a recent stressor and violent suicide methods, and all were married. Cluster 3 had mostly males between the ages of 20 and 64, and all had either experienced recent stressors, suffered from mental illness, or had a history of substance abuse. Cluster 4 had the youngest people and the highest proportion of deaths by jumping from height, few were married, and nearly one-half had bipolar disorder or schizophrenia. Cluster 5 had all unmarried people with no prior suicide attempts, and were the least likely to have an identified mental illness and most likely to leave a suicide note. Conclusions: People who die from suicide assort into different patterns of demographic, clinical, and death-specific characteristics. Identifying and studying subgroups of suicides may advance our understanding of the heterogeneous nature of suicide and help to inform development of more targeted suicide prevention strategies. PMID:24444321

Analysis of neoplastic lesions in magnetic resonance imaging using self-organizing maps.

PubMed

Mei, Paulo Afonso; de Carvalho Carneiro, Cleyton; Fraser, Stephen J; Min, Li Li; Reis, Fabiano

2015-12-15

To provide an improved method for the identification and analysis of brain tumors in MRI scans using a semi-automated computational approach, that has the potential to provide a more objective, precise and quantitatively rigorous analysis, compared to human visual analysis. Self-Organizing Maps (SOM) is an unsupervised, exploratory data analysis tool, which can automatically domain an image into selfsimilar regions or clusters, based on measures of similarity. It can be used to perform image-domain of brain tissue on MR images, without prior knowledge. We used SOM to analyze T1, T2 and FLAIR acquisitions from two MRI machines in our service from 14 patients with brain tumors confirmed by biopsies--three lymphomas, six glioblastomas, one meningioma, one ganglioglioma, two oligoastrocytomas and one astrocytoma. The SOM software was used to analyze the data from the three image acquisitions from each patient and generated a self-organized map for each containing 25 clusters. Damaged tissue was separated from the normal tissue using the SOM technique. Furthermore, in some cases it allowed to separate different areas from within the tumor--like edema/peritumoral infiltration and necrosis. In lesions with less precise boundaries in FLAIR, the estimated damaged tissue area in the resulting map appears bigger. Our results showed that SOM has the potential to be a powerful MR imaging analysis technique for the assessment of brain tumors. Copyright © 2015. Published by Elsevier B.V.

First instalment in resolution of the Banksia spinulosa complex (Proteaceae): B. neoanglica, a new species supported by phenetic analysis, ecology and geography

PubMed Central

Stimpson, Margaret L.; Weston, Peter H.; Telford, Ian R.H.; Bruhl, Jeremy J.

2012-01-01

Abstract Taxa in the Banksia spinulosa Sm. complex (Proteaceae) have populations with sympatric, parapatric and allopatric distributions and unclear or disputed boundaries. Our hypothesis is that under biological, phenetic and diagnosable species concepts that each of the currently named taxa within the Banksia spinulosa complex is a separate species. Based on specimens collected as part of this study, and data recorded from specimens in six Australian herbaria, complemented by phenetic analysis (semi–strong multidimensional scaling and UPGMA clustering) and a detailed morphological study, we investigated both morphological variation and geographic distribution in the Banksia spinulosa complex. All specimens used for this study are held at the N.C.W. Beadle Herbarium or the National Herbarium of New South Wales. In total 23 morphological characters (11 quantitative, five binary, and seven multistate characters) were analysed phenetically for 89 specimens. Ordination and cluster analysis resulted in individuals grouping strongly allowing recognition of distinct groups consistent with their recognition as separate species. Additional morphological analysis was completed on all specimens using leaf, floral, fruit and stem morphology, providing clear cut diagnosable groups and strong support for the recognition of Banksia spinulosa var. cunninghamii and Banksia spinulosa var. neoanglica as species. PMID:23170073

Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation.

PubMed

Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi

2015-01-01

Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it.

Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation

PubMed Central

Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi

2015-01-01

Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it. PMID:26221133

THE STRUCTURE OF THE MERGING RCS 231953+00 SUPERCLUSTER AT z {approx} 0.9

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

Faloon, A. J.; Webb, T. M. A.; Geach, J. E.

2013-05-10

The RCS 2319+00 supercluster is a massive supercluster at z = 0.9 comprising three optically selected, spectroscopically confirmed clusters separated by <3 Mpc on the plane of the sky. This supercluster is one of a few known examples of the progenitors of present-day massive clusters (10{sup 15} M{sub Sun} by z {approx} 0.5). We present an extensive spectroscopic campaign carried out on the supercluster field resulting, in conjunction with previously published data, in 1961 high-confidence galaxy redshifts. We find 302 structure members spanning three distinct redshift walls separated from one another by {approx}65 Mpc ({Delta} z = 0.03). The componentmore » clusters have spectroscopic redshifts of 0.901, 0.905, and 0.905. The velocity dispersions are consistent with those predicted from X-ray data, giving estimated cluster masses of {approx}10{sup 14.5}-10{sup 14.9} M{sub Sun }. The Dressler-Shectman test finds evidence of substructure in the supercluster field and a friends-of-friends analysis identified five groups in the supercluster, including a filamentary structure stretching between two cluster cores previously identified in the infrared by Coppin et al. The galaxy colors further show this filamentary structure to be a unique region of activity within the supercluster, comprised mainly of blue galaxies compared to the {approx}43%-77% red-sequence galaxies present in the other groups and cluster cores. Richness estimates from stacked luminosity function fits result in average group mass estimates consistent with {approx}10{sup 13} M{sub Sun} halos. Currently, 22% of our confirmed members reside in {approx}> 10{sup 13} M{sub Sun} groups/clusters destined to merge onto the most massive cluster, in agreement with the massive halo galaxy fractions important in cluster galaxy pre-processing in N-body simulation merger tree studies.« less

Cluster Analysis of Velocity Field Derived from Dense GNSS Network of Japan

NASA Astrophysics Data System (ADS)

Takahashi, A.; Hashimoto, M.

2015-12-01

Dense GNSS networks have been widely used to observe crustal deformation. Simpson et al. (2012) and Savage and Simpson (2013) have conducted cluster analyses of GNSS velocity field in the San Francisco Bay Area and Mojave Desert, respectively. They have successfully found velocity discontinuities. They also showed an advantage of cluster analysis for classifying GNSS velocity field. Since in western United States, strike-slip events are dominant, geometry is simple. However, the Japanese Islands are tectonically complicated due to subduction of oceanic plates. There are many types of crustal deformation such as slow slip event and large postseismic deformation. We propose a modified clustering method of GNSS velocity field in Japan to separate time variant and static crustal deformation. Our modification is performing cluster analysis every several months or years, then qualifying cluster member similarity. If a GNSS station moved differently from its neighboring GNSS stations, the station will not belong to in the cluster which includes its surrounding stations. With this method, time variant phenomena were distinguished. We applied our method to GNSS data of Japan from 1996 to 2015. According to the analyses, following conclusions were derived. The first is the clusters boundaries are consistent with known active faults. For examples, the Arima-Takatsuki-Hanaore fault system and the Shimane-Tottori segment proposed by Nishimura (2015) are recognized, though without using prior information. The second is improving detectability of time variable phenomena, such as a slow slip event in northern part of Hokkaido region detected by Ohzono et al. (2015). The last one is the classification of postseismic deformation caused by large earthquakes. The result suggested velocity discontinuities in postseismic deformation of the Tohoku-oki earthquake. This result implies that postseismic deformation is not continuously decaying proportional to distance from its epicenter.

Accounting for measurement error in biomarker data and misclassification of subtypes in the analysis of tumor data

PubMed Central

Nevo, Daniel; Zucker, David M.; Tamimi, Rulla M.; Wang, Molin

2017-01-01

A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps–clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses’ Health Study to demonstrate the utility of our method. PMID:27558651

Phylogenetic analysis of Hungarian goose parvovirus isolates and vaccine strains.

PubMed

Tatár-Kis, Tímea; Mató, Tamás; Markos, Béla; Palya, Vilmos

2004-08-01

Polymerase chain reaction and sequencing were used to analyse goose parvovirus field isolates and vaccine strains. Two fragments of the genome were amplified. Fragment "A" represents a region of VP3 gene, while fragment "B" represents a region upstream of the VP3 gene, encompassing part of the VP1 gene. In the region of fragment "A" the deduced amino acid sequence of the strains was identical, therefore differentiation among strains could be done only at the nucleotide level, which resulted in the formation of three groups: Hungarian, West-European and Asian strains. In the region of fragment "B", separation of groups could be done by both nucleotide and deduced amino acid sequence level. The nucleotide sequences resulted in the same groups as for fragment "A" but with a different clustering pattern among the Hungarian strains. Within the "Hungarian" group most of the recent field isolates fell into one cluster, very closely related or identical to each other, indicating a very slow evolutionary change. The attenuated strains and field isolates from 1979/80 formed a separate cluster. When vaccine strains and field isolates were compared, two specific amino acid differences were found that can be considered as possible markers for vaccinal strains. Sequence analysis of fragment "B" seems to be a suitable method for differentiation of attenuated vaccine strains from virulent strains. Copyright 2004 Houghton Trust Ltd

Chemical indices and methods of multivariate statistics as a tool for odor classification.

PubMed

Mahlke, Ingo T; Thiesen, Peter H; Niemeyer, Bernd

2007-04-01

Industrial and agricultural off-gas streams are comprised of numerous volatile compounds, many of which have substantially different odorous properties. State-of-the-art waste-gas treatment includes the characterization of these molecules and is directed at, if possible, either the avoidance of such odorants during processing or the use of existing standardized air purification techniques like bioscrubbing or afterburning, which however, often show low efficiency under ecological and economical regards. Selective odor separation from the off-gas streams could ease many of these disadvantages but is not yet widely applicable. Thus, the aim of this paper is to identify possible model substances in selective odor separation research from 155 volatile molecules mainly originating from livestock facilities, fat refineries, and cocoa and coffee production by knowledge-based methods. All compounds are examined with regard to their structure and information-content using topological and information-theoretical indices. Resulting data are fitted in an observation matrix, and similarities between the substances are computed. Principal component analysis and k-means cluster analysis are conducted showing that clustering of indices data can depict odor information correlating well to molecular composition and molecular shape. Quantitative molecule describtion along with the application of such statistical means therefore provide a good classification tool of malodorant structure properties with no thermodynamic data needed. The approximate look-alike shape of odorous compounds within the clusters suggests a fair choice of possible model molecules.

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.

Software system for data management and distributed processing of multichannel biomedical signals.

PubMed

Franaszczuk, P J; Jouny, C C

2004-01-01

The presented software is designed for efficient utilization of cluster of PC computers for signal analysis of multichannel physiological data. The system consists of three main components: 1) a library of input and output procedures, 2) a database storing additional information about location in a storage system, 3) a user interface for selecting data for analysis, choosing programs for analysis, and distributing computing and output data on cluster nodes. The system allows for processing multichannel time series data in multiple binary formats. The description of data format, channels and time of recording are included in separate text files. Definition and selection of multiple channel montages is possible. Epochs for analysis can be selected both manually and automatically. Implementation of a new signal processing procedures is possible with a minimal programming overhead for the input/output processing and user interface. The number of nodes in cluster used for computations and amount of storage can be changed with no major modification to software. Current implementations include the time-frequency analysis of multiday, multichannel recordings of intracranial EEG of epileptic patients as well as evoked response analyses of repeated cognitive tasks.

The X-ray luminosity functions of Abell clusters from the Einstein Cluster Survey

NASA Technical Reports Server (NTRS)

Burg, R.; Giacconi, R.; Forman, W.; Jones, C.

1994-01-01

We have derived the present epoch X-ray luminosity function of northern Abell clusters using luminosities from the Einstein Cluster Survey. The sample is sufficiently large that we can determine the luminosity function for each richness class separately with sufficient precision to study and compare the different luminosity functions. We find that, within each richness class, the range of X-ray luminosity is quite large and spans nearly a factor of 25. Characterizing the luminosity function for each richness class with a Schechter function, we find that the characteristic X-ray luminosity, L(sub *), scales with richness class as (L(sub *) varies as N(sub*)(exp gamma), where N(sub *) is the corrected, mean number of galaxies in a richness class, and the best-fitting exponent is gamma = 1.3 +/- 0.4. Finally, our analysis suggests that there is a lower limit to the X-ray luminosity of clusters which is determined by the integrated emission of the cluster member galaxies, and this also scales with richness class. The present sample forms a baseline for testing cosmological evolution of Abell-like clusters when an appropriate high-redshift cluster sample becomes available.

Cluster Analysis of Vulnerable Groups in Acute Traumatic Brain Injury Rehabilitation.

PubMed

Kucukboyaci, N Erkut; Long, Coralynn; Smith, Michelle; Rath, Joseph F; Bushnik, Tamara

2018-01-06

To analyze the complex relation between various social indicators that contribute to socioeconomic status and health care barriers. Cluster analysis of historical patient data obtained from inpatient visits. Inpatient rehabilitation unit in a large urban university hospital. Adult patients (N=148) receiving acute inpatient care, predominantly for closed head injury. Not applicable. We examined the membership of patients with traumatic brain injury in various "vulnerable group" clusters (eg, homeless, unemployed, racial/ethnic minority) and characterized the rehabilitation outcomes of patients (eg, duration of stay, changes in FIM scores between admission to inpatient stay and discharge). The cluster analysis revealed 4 major clusters (ie, clusters A-D) separated by vulnerable group memberships, with distinct durations of stay and FIM gains during their stay. Cluster B, the largest cluster and also consisting of mostly racial/ethnic minorities, had the shortest duration of hospital stay and one of the lowest FIM improvements among the 4 clusters despite higher FIM scores at admission. In cluster C, also consisting of mostly ethnic minorities with multiple socioeconomic status vulnerabilities, patients were characterized by low cognitive FIM scores at admission and the longest duration of stay, and they showed good improvement in FIM scores. Application of clustering techniques to inpatient data identified distinct clusters of patients who may experience differences in their rehabilitation outcome due to their membership in various "at-risk" groups. The results identified patients (ie, cluster B, with minority patients; and cluster D, with elderly patients) who attain below-average gains in brain injury rehabilitation. The results also suggested that systemic (eg, duration of stay) or clinical service improvements (eg, staff's language skills, ability to offer substance abuse therapy, provide appropriate referrals, liaise with intensive social work services, or plan subacute rehabilitation phase) could be beneficial for acute settings. Stronger recruitment, training, and retention initiatives for bilingual and multiethnic professionals may also be considered to optimize gains from acute inpatient rehabilitation after traumatic brain injury. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

A qualitative analysis of posttraumatic stress among Mexican victims of disaster.

PubMed

Norris, F H; Weisshaar, D L; Conrad, M L; Diaz, E M; Murphy, A D; Lbañez, G E

2001-10-01

In unstructured interviews, 24 Mexicans described survivors' responses to disasters in Guadalajara, Jalisco (n = 9), Homestead, Florida (n = 6), and Puerto Angel, Oaxaca (n = 9). This analysis assessed the extent to which symptom descriptions corresponded to the 17 criterion symptoms of PTSD. Nineteen participants (79%) mentioned from 1 to 9 criterion symptoms. Event-related distress, hypervigilance, recurrent recollections, and avoiding reminders were described most often. Only 3 criterion symptoms were never described. Twenty participants (83%) provided 109 separate expressions that could not be classified specifically as criterion symptoms. These phrases were sorted by 9 independent Mexican volunteers and cluster analyzed. Clusters composed of ataques de nervios, depression, lasting trauma, and somatic complaints provided the best description of the data.

Impact of SZ cluster residuals in CMB maps and CMB-LSS cross-correlations

NASA Astrophysics Data System (ADS)

Chen, T.; Remazeilles, M.; Dickinson, C.

2018-06-01

Residual foreground contamination in cosmic microwave background (CMB) maps, such as the residual contamination from thermal Sunyaev-Zeldovich (SZ) effect in the direction of galaxy clusters, can bias the cross-correlation measurements between CMB and large-scale structure optical surveys. It is thus essential to quantify those residuals and, if possible, to null out SZ cluster residuals in CMB maps. We quantify for the first time the amount of SZ cluster contamination in the released Planck 2015 CMB maps through (i) the stacking of CMB maps in the direction of the clusters, and (ii) the computation of cross-correlation power spectra between CMB maps and the SDSS-IV large-scale structure data. Our cross-power spectrum analysis yields a 30σ detection at the cluster scale (ℓ = 1500-2500) and a 39σ detection on larger scales (ℓ = 500-1500) due to clustering of SZ clusters, giving an overall 54σ detection of SZ cluster residuals in the Planck CMB maps. The Planck 2015 NILC CMB map is shown to have 44 ± 4% of thermal SZ foreground emission left in it. Using the 'Constrained ILC' component separation technique, we construct an alternative Planck CMB map, the 2D-ILC map, which is shown to have negligible SZ contamination, at the cost of being slightly more contaminated by Galactic foregrounds and noise. We also discuss the impact of the SZ residuals in CMB maps on the measurement of the ISW effect, which is shown to be negligible based on our analysis.

Clustering of health-related behaviors, health outcomes and demographics in Dutch adolescents: a cross-sectional study.

PubMed

Busch, Vincent; Van Stel, Henk F; Schrijvers, Augustinus J P; de Leeuw, Johannes R J

2013-12-04

Recent studies show several health-related behaviors to cluster in adolescents. This has important implications for public health. Interrelated behaviors have been shown to be most effectively targeted by multimodal interventions addressing wider-ranging improvements in lifestyle instead of via separate interventions targeting individual behaviors. However, few previous studies have taken into account a broad, multi-disciplinary range of health-related behaviors and connected these behavioral patterns to health-related outcomes. This paper presents an analysis of the clustering of a broad range of health-related behaviors with relevant demographic factors and several health-related outcomes in adolescents. Self-report questionnaire data were collected from a sample of 2,690 Dutch high school adolescents. Behavioral patterns were deducted via Principal Components Analysis. Subsequently a Two-Step Cluster Analysis was used to identify groups of adolescents with similar behavioral patterns and health-related outcomes. Four distinct behavioral patterns describe the analyzed individual behaviors: 1- risk-prone behavior, 2- bully behavior, 3- problematic screen time use, and 4- sedentary behavior. Subsequent cluster analysis identified four clusters of adolescents. Multi-problem behavior was associated with problematic physical and psychosocial health outcomes, as opposed to those exerting relatively few unhealthy behaviors. These associations were relatively independent of demographics such as ethnicity, gender and socio-economic status. The results show that health-related behaviors tend to cluster, indicating that specific behavioral patterns underlie individual health behaviors. In addition, specific patterns of health-related behaviors were associated with specific health outcomes and demographic factors. In general, unhealthy behavior on account of multiple health-related behaviors was associated with both poor psychosocial and physical health. These findings have significant meaning for future public health programs, which should be more tailored with use of such knowledge on behavioral clustering via e.g. Transfer Learning.

Clustering of health-related behaviors, health outcomes and demographics in Dutch adolescents: a cross-sectional study

PubMed Central

2013-01-01

Background Recent studies show several health-related behaviors to cluster in adolescents. This has important implications for public health. Interrelated behaviors have been shown to be most effectively targeted by multimodal interventions addressing wider-ranging improvements in lifestyle instead of via separate interventions targeting individual behaviors. However, few previous studies have taken into account a broad, multi-disciplinary range of health-related behaviors and connected these behavioral patterns to health-related outcomes. This paper presents an analysis of the clustering of a broad range of health-related behaviors with relevant demographic factors and several health-related outcomes in adolescents. Methods Self-report questionnaire data were collected from a sample of 2,690 Dutch high school adolescents. Behavioral patterns were deducted via Principal Components Analysis. Subsequently a Two-Step Cluster Analysis was used to identify groups of adolescents with similar behavioral patterns and health-related outcomes. Results Four distinct behavioral patterns describe the analyzed individual behaviors: 1- risk-prone behavior, 2- bully behavior, 3- problematic screen time use, and 4- sedentary behavior. Subsequent cluster analysis identified four clusters of adolescents. Multi-problem behavior was associated with problematic physical and psychosocial health outcomes, as opposed to those exerting relatively few unhealthy behaviors. These associations were relatively independent of demographics such as ethnicity, gender and socio-economic status. Conclusions The results show that health-related behaviors tend to cluster, indicating that specific behavioral patterns underlie individual health behaviors. In addition, specific patterns of health-related behaviors were associated with specific health outcomes and demographic factors. In general, unhealthy behavior on account of multiple health-related behaviors was associated with both poor psychosocial and physical health. These findings have significant meaning for future public health programs, which should be more tailored with use of such knowledge on behavioral clustering via e.g. Transfer Learning. PMID:24305509

Neural Coding Mechanisms in Gustation.

DTIC Science & Technology

1980-09-15

world is composed of four primary tastes ( sweet , sour, salty , and bitter), and that each of these is carried by a separate and private neural line, thus...ted sweet -sour- salty -bitter types. The mathematical method of analysis was hierarchical cluster analysis based on the responses of many neurons (20 to...block number) Taste Neural coding Neural organization Stimulus organization Olfaction AB TRACT M~ea -i .rvm~ .1* N necffas and idmatity by block mmnbwc

Application of cluster and discriminant analyses to diagnose lithological heterogeneity of the parent material according to its particle-size distribution

NASA Astrophysics Data System (ADS)

Giniyatullin, K. G.; Valeeva, A. A.; Smirnova, E. V.

2017-08-01

Particle-size distribution in soddy-podzolic and light gray forest soils of the Botanical Garden of Kazan Federal University has been studied. The cluster analysis of data on the samples from genetic soil horizons attests to the lithological heterogeneity of the profiles of all the studied soils. It is probable that they are developed from the two-layered sediments with the upper colluvial layer underlain by the alluvial layer. According to the discriminant analysis, the major contribution to the discrimination of colluvial and alluvial layers is that of the fraction >0.25 mm. The results of canonical analysis show that there is only one significant discriminant function that separates alluvial and colluvial sediments on the investigated territory. The discriminant function correlates with the contents of fractions 0.05-0.01, 0.25-0.05, and >0.25 mm. Classification functions making it possible to distinguish between alluvial and colluvial sediments have been calculated. Statistical assessment of particle-size distribution data obtained for the plow horizons on ten plowed fields within the garden indicates that this horizon is formed from colluvial sediments. We conclude that the contents of separate fractions and their ratios cannot be used as a universal criterion of the lithological heterogeneity. However, adequate combination of the cluster and discriminant analyses makes it possible to give a comprehensive assessment of the lithology of soil samples from data on the contents of sand and silt fractions, which considerably increases the information value and reliability of the results.

Cluster Analysis Identifies Distinct Pathogenetic Patterns in C3 Glomerulopathies/Immune Complex-Mediated Membranoproliferative GN.

PubMed

Iatropoulos, Paraskevas; Daina, Erica; Curreri, Manuela; Piras, Rossella; Valoti, Elisabetta; Mele, Caterina; Bresin, Elena; Gamba, Sara; Alberti, Marta; Breno, Matteo; Perna, Annalisa; Bettoni, Serena; Sabadini, Ettore; Murer, Luisa; Vivarelli, Marina; Noris, Marina; Remuzzi, Giuseppe

2018-01-01

Membranoproliferative GN (MPGN) was recently reclassified as alternative pathway complement-mediated C3 glomerulopathy (C3G) and immune complex-mediated membranoproliferative GN (IC-MPGN). However, genetic and acquired alternative pathway abnormalities are also observed in IC-MPGN. Here, we explored the presence of distinct disease entities characterized by specific pathophysiologic mechanisms. We performed unsupervised hierarchical clustering, a data-driven statistical approach, on histologic, genetic, and clinical data and data regarding serum/plasma complement parameters from 173 patients with C3G/IC-MPGN. This approach divided patients into four clusters, indicating the existence of four different pathogenetic patterns. Specifically, this analysis separated patients with fluid-phase complement activation (clusters 1-3) who had low serum C3 levels and a high prevalence of genetic and acquired alternative pathway abnormalities from patients with solid-phase complement activation (cluster 4) who had normal or mildly altered serum C3, late disease onset, and poor renal survival. In patients with fluid-phase complement activation, those in clusters 1 and 2 had massive activation of the alternative pathway, including activation of the terminal pathway, and the highest prevalence of subendothelial deposits, but those in cluster 2 had additional activation of the classic pathway and the highest prevalence of nephrotic syndrome at disease onset. Patients in cluster 3 had prevalent activation of C3 convertase and highly electron-dense intramembranous deposits. In addition, we provide a simple algorithm to assign patients with C3G/IC-MPGN to specific clusters. These distinct clusters may facilitate clarification of disease etiology, improve risk assessment for ESRD, and pave the way for personalized treatment. Copyright © 2018 by the American Society of Nephrology.

Social Support, Academic Adversity and Academic Buoyancy: A Person-Centred Analysis and Implications for Academic Outcomes

ERIC Educational Resources Information Center

Collie, Rebecca J.; Martin, Andrew J.; Bottrell, Dorothy; Armstrong, Derrick; Ungar, Michael; Liebenberg, Linda

2017-01-01

The present study employed person-centred analyses that enabled identification of groups of students separated on the basis of their perceptions of social support (home and community), academic support, academic adversity and academic buoyancy. Among a sample of 249 young people, including many from high-needs communities, cluster analysis…

[The commercially cultivated edible oyster mushrooms Pleurotus sajor-caju and P. pulmonarius are two separate species, similar in morphology but reproductively isolated].

PubMed

Shnyreva, A A; Sivolapova, A B; Shnyreva, A V

2012-11-01

Two closely related commercially cultivated oyster mushroom species, Pleurotus pulmonarius and P. sajor-caju have been differentiated by traditional mating experiments as well as analysis of the variable ITS and IGS sequences of the ribosomal gene cluster. Molecular analysis of the variable ITS and IGS regions has allowed neither reliable differentiation between the morphologically similar species P. pulmonarius and P. sajor-caju nor confirmation of species identity of the P. sajor-caju strains CS-32, H-1, and H-2. Analysis of the sexual (mating) compatibility between haploid tester strains of these two species in monokaryon-monokaryon mating experiments has demonstrated complete reproductive isolation between P. pulmonarius and P. sajor-caju, thereby confirming that these are separate species.

Insights into magmatic processes and hydrothermal alteration of in situ superfast spreading ocean crust at ODP/IODP site 1256 from a cluster analysis of rock magnetic properties

NASA Astrophysics Data System (ADS)

Dekkers, Mark J.; Heslop, David; Herrero-Bervera, Emilio; Acton, Gary; Krasa, David

2014-08-01

We analyze magnetic properties from Ocean Drilling Program (ODP)/Integrated ODP (IODP) Hole 1256D (6°44.1' N, 91°56.1' W) on the Cocos Plate in ˜15.2 Ma oceanic crust generated by superfast seafloor spreading, the only drill hole that has sampled all three oceanic crust layers in a tectonically undisturbed setting. Fuzzy c-means cluster analysis and nonlinear mapping are utilized to study down-hole trends in the ratio of the saturation remanent magnetization and the saturation magnetization, the coercive force, the ratio of the remanent coercive force and coercive force, the low-field magnetic susceptibility, and the Curie temperature, to evaluate the effects of magmatic and hydrothermal processes on magnetic properties. A statistically robust five cluster solution separates the data predominantly into three clusters that express increasing hydrothermal alteration of the lavas, which differ from two distinct clusters mainly representing the dikes and gabbros. Extensive alteration 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. Thus, the analysis complements interpretation based on electrofacies analysis. All clusters display rock magnetic characteristics compatible with an ability to retain a stable natural remanent magnetization suggesting that the entire sampled sequence of ocean crust can contribute to marine magnetic anomalies. Paleointensity determination is difficult because of the propensity of oxyexsolution during laboratory heating and/or the presence of intergrowths. The upper part of the extrusive sequence, the granoblastic dikes, and moderately altered gabbros may contain a comparatively uncontaminated thermoremanent magnetization.

The Impact of Clinical, Demographic and Risk Factors on Rates of HIV Transmission: A Population-based Phylogenetic Analysis in British Columbia, Canada

PubMed Central

Poon, Art F. Y.; Joy, Jeffrey B.; Woods, Conan K.; Shurgold, Susan; Colley, Guillaume; Brumme, Chanson J.; Hogg, Robert S.; Montaner, Julio S. G.; Harrigan, P. Richard

2015-01-01

Background. The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission. Methods. We reconstructed molecular phylogenies from 27 296 anonymized bulk HIV pol sequences representing 7747 individuals in BC—about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion. Results. Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter. Conclusions. Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention. PMID:25312037

The Angular Power Spectrum of BATSE 3B Gamma-Ray Bursts

NASA Technical Reports Server (NTRS)

Tegmark, Max; Hartmann, Dieter H.; Briggs, Michael S.; Meegan, Charles A.

1996-01-01

We compute the angular power spectrum C(sub l) from the BATSE 3B catalog of 1122 gamma-ray bursts and find no evidence for clustering on any scale. These constraints bridge the entire range from small scales (which probe source clustering and burst repetition) to the largest scales (which constrain possible anisotropics from the Galactic halo or from nearby cosmological large-scale structures). We develop an analysis technique that takes the angular position errors into account. For specific clustering or repetition models, strong upper limits can be obtained down to scales l approx. equal to 30, corresponding to a couple of degrees on the sky. The minimum-variance burst weighting that we employ is visualized graphically as an all-sky map in which each burst is smeared out by an amount corresponding to its position uncertainty. We also present separate bandpass-filtered sky maps for the quadrupole term and for the multipole ranges l = 3-10 and l = 11-30, so that the fluctuations on different angular scales can be inspected separately for visual features such as localized 'hot spots' or structures aligned with the Galactic plane. These filtered maps reveal no apparent deviations from isotropy.

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Two Point Autocorrelation Analysis of Auger Highest Energy Events Backtracked in Galactic Magnetic Field

NASA Astrophysics Data System (ADS)

Petrov, Yevgeniy

2009-10-01

Searches for sources of the highest-energy cosmic rays traditionally have included looking for clusters of event arrival directions on the sky. The smallest cluster is a pair of events falling within some angular window. In contrast to the standard two point (2-pt) autocorrelation analysis, this work takes into account influence of the galactic magnetic field (GMF). The highest energy events, those above 50EeV, collected by the surface detector of the Pierre Auger Observatory between January 1, 2004 and May 31, 2009 are used in the analysis. Having assumed protons as primaries, events are backtracked through BSS/S, BSS/A, ASS/S and ASS/A versions of Harari-Mollerach-Roulet (HMR) model of the GMF. For each version of the model, a 2-pt autocorrelation analysis is applied to the backtracked events and to 105 isotropic Monte Carlo realizations weighted by the Auger exposure. Scans in energy, separation angular window and different model parameters reveal clustering at different angular scales. Small angle clustering at 2-3 deg is particularly interesting and it is compared between different field scenarios. The strength of the autocorrelation signal at those angular scales differs between BSS and ASS versions of the HMR model. The BSS versions of the model tend to defocus protons as they arrive to Earth whereas for the ASS, in contrary, it is more likely to focus them.

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Deep observation of A2163: studying a new bullet cluster

NASA Astrophysics Data System (ADS)

Bourdin, Herve

2011-10-01

Exhibiting a clear spatial separation between the gas and dark matter component of a fastly accreted subcluster, the `bullet cluster', 1E 0657-56, has provided us a unique laboratory to investigate the impact of violent cluster mergers on the Intra-Cluster Medium, galaxies and dark matter properties. In recent analyses of X-ray, optical and weak-lensing data, we show that the massive cluster A2163 also exhibits a crossing gas bullet separated from a galaxy and dark matter over-density, and suggest that both A2163 and 1E 0657-56 share a common merging scenario possibly just differing in the time elapsed after the closest cluster encounters. With this deeper XMM observation of A2163, we propose to refine our knowledge of the dynamics and geometry of the on-going subcluster accretion.

Competing Effects Between Screen Media Time and Physical Activity in Adolescent Girls: Clustering a Self-Organizing Maps Analysis.

PubMed

Valencia-Peris, Alexandra; Devís-Devís, José; García-Massó, Xavier; Lizandra, Jorge; Pérez-Gimeno, Esther; Peiró-Velert, Carmen

2016-06-01

Previous research shows contradictory findings on potential competing effects between sedentary screen media usage (SMU) and physical activity (PA). This study examined these effects on adolescent girls via self-organizing maps analysis focusing on 3 target profiles. A sample of 1,516 girls aged 12 to 18 years self-reported daily time engagement in PA (moderate and vigorous intensity) and in screen media activities (TV/video/DVD, computer, and videogames), separately and combined. Topological interrelationships from the 13 emerging maps indicated a moderate competing effect between physically active and sedentary SMU patterns. Higher SES and overweight status were linked to either active or inactive behaviors. Three target clusters were explored in more detail. Cluster 1, named temperate-media actives, showed capabilities of being active while engaging in a moderate level of SMU (TV/video/DVD mainly). In Cluster 2, named prudent-media inactives, and Cluster 3, compulsive-media inactives, a competing effect between SMU and PA emerged, being sedentary SMU behaviors responsible for a low involvement in active pursuits. SMU and PA emerge as both related and independent behaviors in girls, resulting in a moderate competing effect. Findings support the case for recommending the timing of PA and SMU for recreational purposes considering different profiles, sociodemographic factors and types of SMU.

The history of introduction of the African baobab (Adansonia digitata, Malvaceae: Bombacoideae) in the Indian subcontinent

PubMed Central

Bell, Karen L.; Rangan, Haripriya; Kull, Christian A.; Murphy, Daniel J.

2015-01-01

To investigate the pathways of introduction of the African baobab, Adansonia digitata, to the Indian subcontinent, we examined 10 microsatellite loci in individuals from Africa, India, the Mascarenes and Malaysia, and matched this with historical evidence of human interactions between source and destination regions. Genetic analysis showed broad congruence of African clusters with biogeographic regions except along the Zambezi (Mozambique) and Kilwa (Tanzania), where populations included a mixture of individuals assigned to at least two different clusters. Individuals from West Africa, the Mascarenes, southeast India and Malaysia shared a cluster. Baobabs from western and central India clustered separately from Africa. Genetic diversity was lower in populations from the Indian subcontinent than in African populations, but the former contained private alleles. Phylogenetic analysis showed Indian populations were closest to those from the Mombasa-Dar es Salaam coast. The genetic results provide evidence of multiple introductions of African baobabs to the Indian subcontinent over a longer time period than previously assumed. Individuals belonging to different genetic clusters in Zambezi and Kilwa may reflect the history of trafficking captives from inland areas to supply the slave trade between the fifteenth and nineteenth centuries. Baobabs in the Mascarenes, southeast India and Malaysia indicate introduction from West Africa through eighteenth and nineteenth century European colonial networks. PMID:26473060

The history of introduction of the African baobab (Adansonia digitata, Malvaceae: Bombacoideae) in the Indian subcontinent.

PubMed

Bell, Karen L; Rangan, Haripriya; Kull, Christian A; Murphy, Daniel J

2015-09-01

To investigate the pathways of introduction of the African baobab, Adansonia digitata, to the Indian subcontinent, we examined 10 microsatellite loci in individuals from Africa, India, the Mascarenes and Malaysia, and matched this with historical evidence of human interactions between source and destination regions. Genetic analysis showed broad congruence of African clusters with biogeographic regions except along the Zambezi (Mozambique) and Kilwa (Tanzania), where populations included a mixture of individuals assigned to at least two different clusters. Individuals from West Africa, the Mascarenes, southeast India and Malaysia shared a cluster. Baobabs from western and central India clustered separately from Africa. Genetic diversity was lower in populations from the Indian subcontinent than in African populations, but the former contained private alleles. Phylogenetic analysis showed Indian populations were closest to those from the Mombasa-Dar es Salaam coast. The genetic results provide evidence of multiple introductions of African baobabs to the Indian subcontinent over a longer time period than previously assumed. Individuals belonging to different genetic clusters in Zambezi and Kilwa may reflect the history of trafficking captives from inland areas to supply the slave trade between the fifteenth and nineteenth centuries. Baobabs in the Mascarenes, southeast India and Malaysia indicate introduction from West Africa through eighteenth and nineteenth century European colonial networks.

Guasom Analysis Of The Alhambra Survey

NASA Astrophysics Data System (ADS)

Garabato, Daniel; Manteiga, Minia; Dafonte, Carlos; Álvarez, Marco A.

2017-10-01

GUASOM is a data mining tool designed for knowledge discovery in large astronomical spectrophotometric archives developed in the framework of Gaia DPAC (Data Processing and Analysis Consortium). Our tool is based on a type of unsupervised learning Artificial Neural Networks named Self-organizing maps (SOMs). SOMs permit the grouping and visualization of big amount of data for which there is no a priori knowledge and hence they are very useful for analyzing the huge amount of information present in modern spectrophotometric surveys. SOMs are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. Each cluster has a representative, called prototype which is a virtual pattern that better represents or resembles the set of input patterns belonging to such a cluster. Prototypes make easier the task of determining the physical nature and properties of the objects populating each cluster. Our algorithm has been tested on the ALHAMBRA survey spectrophotometric observations, here we present our results concerning the survey segmentation, visualization of the data structure, separation between types of objects (stars and galaxies), data homogeneity of neurons, cluster prototypes, redshift distribution and crossmatch with other databases (Simbad).

WIYN OPEN CLUSTER STUDY. LV. ASTROMETRY AND MEMBERSHIP IN NGC 6819

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

Platais, Imants; Gosnell, Natalie M.; Meibom, Soren

2013-08-01

We present proper motions and astrometric membership analysis for 15,750 stars around the intermediate-age open cluster NGC 6819. The accuracy of relative proper motions for well-measured stars ranges from {approx}0.2 mas yr{sup -1} within 10' of the cluster center to 1.1 mas yr{sup -1} outside this radius. In the proper motion vector-point diagram, the separation between the cluster members and field stars is convincing down to V {approx} 18 and within 10' from the cluster center. The formal sum of membership probabilities indicates a total of {approx}2500 cluster members down to V {approx} 22. We confirm the cluster membership ofmore » several variable stars, including some eclipsing binaries. The estimated absolute proper motion of NGC 6819 is {mu}{sub x}{sup abs}=-2.6{+-}0.5 and {mu}{sub y}{sup abs}=-4.2{+-}0.5 mas yr{sup -1}. A cross-identification between the proper motion catalog and a list of X-ray sources in the field of NGC 6819 resulted in a number of new likely optical counterparts, including a candidate CV. For the first time we show that there is significant differential reddening toward NGC 6819.« less

Nuclear counterparts of the cytoplasmic mitochondrial 12S rRNA gene: a problem of ancient DNA and molecular phylogenies.

PubMed

van der Kuyl, A C; Kuiken, C L; Dekker, J T; Perizonius, W R; Goudsmit, J

1995-06-01

Monkey mummy bones and teeth originating from the North Saqqara Baboon Galleries (Egypt), soft tissue from a mummified baboon in a museum collection, and nineteenth/twentieth-century skin fragments from mangabeys were used for DNA extraction and PCR amplification of part of the mitochondrial 12S rRNA gene. Sequences aligning with the 12S rRNA gene were recovered but were only distantly related to contemporary monkey mitochondrial 12S rRNA sequences. However, many of these sequences were identical or closely related to human nuclear DNA sequences resembling mitochondrial 12S rRNA (isolated from a cell line depleted in mitochondria) and therefore have to be considered contamination. Subsequently in a separate study we were able to recover genuine mitochondrial 12S rRNA sequences from many extant species of nonhuman Old World primates and sequences closely resembling the human nuclear integrations. Analysis of all sequences by the neighbor-joining (NJ) method indicated that mitochondrial DNA sequences and their nuclear counterparts can be divided into two distinct clusters. One cluster contained all temporary cytoplasmic mitochondrial DNA sequences and approximately half of the monkey nuclear mitochondriallike sequences. A second cluster contained most human nuclear sequences and the other half of monkey nuclear sequences with a separate branch leading to human and gorilla mitochondrial and nuclear sequences. Sequences recovered from ancient materials were equally divided between the two clusters. These results constitute a warning for when working with ancient DNA or performing phylogenetic analysis using mitochondrial DNA as a target sequence: Nuclear counterparts of mitochondrial genes may lead to faulty interpretation of results.

Identification and DUS Testing of Rice Varieties through Microsatellite Markers.

PubMed

Pourabed, Ehsan; Jazayeri Noushabadi, Mohammad Reza; Jamali, Seyed Hossein; Moheb Alipour, Naser; Zareyan, Abbas; Sadeghi, Leila

2015-01-01

Identification and registration of new rice varieties are very important to be free from environmental effects and using molecular markers that are more reliable. The objectives of this study were, first, the identification and distinction of 40 rice varieties consisting of local varieties of Iran, improved varieties, and IRRI varieties using PIC, and discriminating power, second, cluster analysis based on Dice similarity coefficient and UPGMA algorithm, and, third, determining the ability of microsatellite markers to separate varieties utilizing the best combination of markers. For this research, 12 microsatellite markers were used. In total, 83 polymorphic alleles (6.91 alleles per locus) were found. In addition, the variation of PIC was calculated from 0.52 to 0.9. The results of cluster analysis showed the complete discrimination of varieties from each other except for IR58025A and IR58025B. Moreover, cluster analysis could detect the most of the improved varieties from local varieties. Based on the best combination of markers analysis, five pair primers together have shown the same results of all markers for detection among all varieties. Considering the results of this research, we can propose that microsatellite markers can be used as a complementary tool for morphological characteristics in DUS tests.

Kinetics of Forming Aldehydes in Frying Oils and Their Distribution in French Fries Revealed by LC-MS-Based Chemometrics.

PubMed

Wang, Lei; Csallany, A Saari; Kerr, Brian J; Shurson, Gerald C; Chen, Chi

2016-05-18

In this study, the kinetics of aldehyde formation in heated frying oils was characterized by 2-hydrazinoquinoline derivatization, liquid chromatography-mass spectrometry (LC-MS) analysis, principal component analysis (PCA), and hierarchical cluster analysis (HCA). The aldehydes contributing to time-dependent separation of heated soybean oil (HSO) in a PCA model were grouped by the HCA into three clusters (A1, A2, and B) on the basis of their kinetics and fatty acid precursors. The increases of 4-hydroxynonenal (4-HNE) and the A2-to-B ratio in HSO were well-correlated with the duration of thermal stress. Chemometric and quantitative analysis of three frying oils (soybean, corn, and canola oils) and French fry extracts further supported the associations between aldehyde profiles and fatty acid precursors and also revealed that the concentrations of pentanal, hexanal, acrolein, and the A2-to-B ratio in French fry extracts were more comparable to their values in the frying oils than other unsaturated aldehydes. All of these results suggest the roles of specific aldehydes or aldehyde clusters as novel markers of the lipid oxidation status for frying oils or fried foods.

Cluster analysis of bone microarchitecture from high resolution peripheral quantitative computed tomography demonstrates two separate phenotypes associated with high fracture risk in men and women.

PubMed

Edwards, M H; Robinson, D E; Ward, K A; Javaid, M K; Walker-Bone, K; Cooper, C; Dennison, E M

2016-07-01

Osteoporosis is a major healthcare problem which is conventionally assessed by dual energy X-ray absorptiometry (DXA). New technologies such as high resolution peripheral quantitative computed tomography (HRpQCT) also predict fracture risk. HRpQCT measures a number of bone characteristics that may inform specific patterns of bone deficits. We used cluster analysis to define different bone phenotypes and their relationships to fracture prevalence and areal bone mineral density (BMD). 177 men and 159 women, in whom fracture history was determined by self-report and vertebral fracture assessment, underwent HRpQCT of the distal radius and femoral neck DXA. Five clusters were derived with two clusters associated with elevated fracture risk. "Cluster 1" contained 26 women (50.0% fractured) and 30 men (50.0% fractured) with a lower mean cortical thickness and cortical volumetric BMD, and in men only, a mean total and trabecular area more than the sex-specific cohort mean. "Cluster 2" contained 20 women (50.0% fractured) and 14 men (35.7% fractured) with a lower mean trabecular density and trabecular number than the sex-specific cohort mean. Logistic regression showed fracture rates in these clusters to be significantly higher than the lowest fracture risk cluster [5] (p<0.05). Mean femoral neck areal BMD was significantly lower than cluster 5 in women in cluster 1 and 2 (p<0.001 for both), and in men, in cluster 2 (p<0.001) but not 1 (p=0.220). In conclusion, this study demonstrates two distinct high risk clusters in both men and women which may differ in etiology and response to treatment. As cluster 1 in men does not have low areal BMD, these men may not be identified as high risk by conventional DXA alone. Copyright © 2016. Published by Elsevier Inc.

Mass Profile Decomposition of the Frontier Fields Cluster MACS J0416-2403: Insights on the Dark-matter Inner Profile

NASA Astrophysics Data System (ADS)

Annunziatella, M.; Bonamigo, M.; Grillo, C.; Mercurio, A.; Rosati, P.; Caminha, G.; Biviano, A.; Girardi, M.; Gobat, R.; Lombardi, M.; Munari, E.

2017-12-01

We present a high-resolution dissection of the two-dimensional total mass distribution in the core of the Hubble Frontier Fields galaxy cluster MACS J0416.1‑2403, at z = 0.396. We exploit HST/WFC3 near-IR (F160W) imaging, VLT/Multi Unit Spectroscopic Explorer spectroscopy, and Chandra data to separate the stellar, hot gas, and dark-matter mass components in the inner 300 kpc of the cluster. We combine the recent results of our refined strong lensing analysis, which includes the contribution of the intracluster gas, with the modeling of the surface brightness and stellar mass distributions of 193 cluster members, of which 144 are spectroscopically confirmed. We find that, moving from 10 to 300 kpc from the cluster center, the stellar to total mass fraction decreases from 12% to 1% and the hot gas to total mass fraction increases from 3% to 9%, resulting in a baryon fraction of approximatively 10% at the outermost radius. We measure that the stellar component represents ∼30%, near the cluster center, and 15%, at larger clustercentric distances, of the total mass in the cluster substructures. We subtract the baryonic mass component from the total mass distribution and conclude that within 30 kpc (∼3 times the effective radius of the brightest cluster galaxy) from the cluster center the surface mass density profile of the total mass and global (cluster plus substructures) dark-matter are steeper and that of the diffuse (cluster) dark-matter is shallower than an NFW profile. Our current analysis does not point to a significant offset between the cluster stellar and dark-matter components. This detailed and robust reconstruction of the inner dark-matter distribution in a larger sample of galaxy clusters will set a new benchmark for different structure formation scenarios.

[Chlorobaculum macestae sp. nov., a new green sulfur bacterium].

PubMed

Koppen, O I; Berg, I A; Lebedeva, N V; Taisova, A S; Kolganova, T V; Slobodova, N V; Bulygina, E S; Turova, T P; Ivanovskiĭ, R N

2008-01-01

The investigated green sulfur bacterium, strain M, was isolated from a sulfidic spring on the Black Sea Coast of the Caucasus. The cells of strain M are straight or curved rods 0.6-0.9 x 1.8-4.2 microm in size. According to the cell wall structure, the bacteria are gram-negative. Chlorosomes are located along the cell periphery. Strain M is an obligate anaerobe capable of photoautotrophic growth on sulfide, thiosulfate, and H2. It utilizes ammonium, urea, casein hydrolysate, and N2 as nitrogen sources and sulfide, thiosulfate, and elemental sulfur as sulfur sources. Bacteriochlorophyll c and the carotenoid chlorobactene are the main pigments. The optimal growth temperature is 25-28 degrees C; the optimal pH is 6.8. The strain does not require NaCl. Vitamin B12 stimulates growth. The content of the G+C base pairs in the DNA of strain M is 58.3 mol %. In the phylogenetic tree constructed on the basis of analysis of nucleotide sequences of 16S rRNA genes, strain M forms a separate branch, which occupies an intermediate position between the phylogenetic cluster containing representatives of the genus Chlorobaculum (94.9-96.8%) and the cluster containing species of the genus Chlorobium (94.1-96.5%). According to the results of analysis of the amino acid sequence corresponding to the fmo gene, strain M represents a branch which, unlike that in the "ribosomal" tree, falls into the cluster of the genus Chlorobaculum (95.8-97.2%). Phylogenetic analysis of the amino acid sequence corresponding to the nifH gene placed species of the genera Chlorobaculum and Chlorobium into a single cluster, whereas strain M formed a separate branch. The results obtained allow us to describe strain M as a new species of the genus Chlorobaculum. Chlorobaculum macestae sp. nov.

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods.

PubMed

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines.

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods

PubMed Central

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines. PMID:26890416

Three 3D metal coordination polymers based on triazol-functionalized rigid ligand: Synthesis, topological structure and properties

NASA Astrophysics Data System (ADS)

Meng, Lingkun; Liu, Kang; Liang, Chen; Guo, Xiaolei; Han, Xu; Ren, Siyuan; Ma, Dingxuan; Li, Guanghua; Shi, Zhan; Feng, Shouhua

2018-02-01

By using a triazol-functionalized tricarboxylate, three novel metal coordination polymers, namely, [Zn2L(OH)]·0.5H2O (1), [Co2L(OH)(H2O)]·5.5H2O (2), [Cu2(HL)] (3) L = ［5-(3-(4-carboxyphenyl)-5-methyl-4H-1,2,4-triazol-4-yl)isophthalate］ were synthesized under hydrothermal reactions. All the compounds were characterized by element analysis, IR spectroscopy, thermogravimetric analysis, power X-ray diffrcation and single-crystal X-ray diffrcation. Structural analysis reveals that compounds 1 and 2 have 3D networks with flu topologies where rigid trizaol-functionalized ligands as 4-connected nodes and Zn4(COO)6 or Co4(COO)6 clusters serves as 8-connected secondary building units. Compound 3 has 3D network with pcu topology where Cu4(COO)4 clusters serve as 6-connected secondary building units. Gas adsorption studies reveal that desolvated compoud 1 exhibits high H2 absorption capacity at 77 K and highly selective separation abilities of CO2 and C3H8 over CH4 at room temperature. The results suggest that 1 has potential application in gas storage and separation. In addition, the magnetic properties of compound 2 were also investigated.

Phase separation and large deviations of lattice active matter

NASA Astrophysics Data System (ADS)

Whitelam, Stephen; Klymko, Katherine; Mandal, Dibyendu

2018-04-01

Off-lattice active Brownian particles form clusters and undergo phase separation even in the absence of attractions or velocity-alignment mechanisms. Arguments that explain this phenomenon appeal only to the ability of particles to move persistently in a direction that fluctuates, but existing lattice models of hard particles that account for this behavior do not exhibit phase separation. Here we present a lattice model of active matter that exhibits motility-induced phase separation in the absence of velocity alignment. Using direct and rare-event sampling of dynamical trajectories, we show that clustering and phase separation are accompanied by pronounced fluctuations of static and dynamic order parameters. This model provides a complement to off-lattice models for the study of motility-induced phase separation.

Accounting for measurement error in biomarker data and misclassification of subtypes in the analysis of tumor data.

PubMed

Nevo, Daniel; Zucker, David M; Tamimi, Rulla M; Wang, Molin

2016-12-30

A common paradigm in dealing with heterogeneity across tumors in cancer analysis is to cluster the tumors into subtypes using marker data on the tumor, and then to analyze each of the clusters separately. A more specific target is to investigate the association between risk factors and specific subtypes and to use the results for personalized preventive treatment. This task is usually carried out in two steps-clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The first is the measurement error in the biomarker values. The second is the misclassification error when assigning observations to clusters. We consider the case with a specified set of relevant markers and propose a unified single-likelihood approach for normally distributed biomarkers. As an alternative, we consider a two-step procedure with the tumor type misclassification error taken into account in the second-step risk factor analysis. We describe our method for binary data and also for survival analysis data using a modified version of the Cox model. We present asymptotic theory for the proposed estimators. Simulation results indicate that our methods significantly lower the bias with a small price being paid in terms of variance. We present an analysis of breast cancer data from the Nurses' Health Study to demonstrate the utility of our method. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Atomically precise arrays of fluorescent silver clusters: a modular approach for metal cluster photonics on DNA nanostructures.

PubMed

Copp, Stacy M; Schultz, Danielle E; Swasey, Steven; Gwinn, Elisabeth G

2015-03-24

The remarkable precision that DNA scaffolds provide for arraying nanoscale optical elements enables optical phenomena that arise from interactions of metal nanoparticles, dye molecules, and quantum dots placed at nanoscale separations. However, control of ensemble optical properties has been limited by the difficulty of achieving uniform particle sizes and shapes. Ligand-stabilized metal clusters offer a route to atomically precise arrays that combine desirable attributes of both metals and molecules. Exploiting the unique advantages of the cluster regime requires techniques to realize controlled nanoscale placement of select cluster structures. Here we show that atomically monodisperse arrays of fluorescent, DNA-stabilized silver clusters can be realized on a prototypical scaffold, a DNA nanotube, with attachment sites separated by <10 nm. Cluster attachment is mediated by designed DNA linkers that enable isolation of specific clusters prior to assembly on nanotubes and preserve cluster structure and spectral purity after assembly. The modularity of this approach generalizes to silver clusters of diverse sizes and DNA scaffolds of many types. Thus, these silver cluster nano-optical elements, which themselves have colors selected by their particular DNA templating oligomer, bring unique dimensions of control and flexibility to the rapidly expanding field of nano-optics.

[Study on HPLC fingerprint of Oldenlandia diffusa].

PubMed

Chen, Yan; Yao, Zhi-Hong; Dai, Yi; Cheng, Hong; Wen, Li-Rong; Zhou, Guang-Xiong; Yao, Xin-Sheng

2012-06-01

To establish the HPLC fingerprint chromatogram of Oldenlandia diffusa coupled with chemometrics means for the quality control of multi-batches of medicinal material. The separation was developed on C18 column(4.6 mm x 250 mm, 5 microm) by gradient elution with acetonitrile-water(both containing 0.1 per thousand (V/V) ocetic acid) as mobile phase at a flow rate of 0.8 mL/min, the detection wavelength at 238 nm and column temperature at 30 degrees C. The HPLC fingerprint chromatogram of Oldenlandia diffusa was set up and the main characteristic peaks were identified by comparing with chemical reference substance. The quality of 22 batches of medicinal material was evaluated by similarity assay as well as principal component analysis (PCA) and cluster analysis. The established HPLC fingerprint chromatogram of Oldenlandia diffusa was specific, precise, reproducible and stable. 11 peaks were chemically identified. The similarity of 17 batches of Oldenlandia diffusa was obviously higher than 5 batches of adulterants. PCA showed that 17 batches of Oldenlandia diffusa were in a domain and 5 batches of adulterants were far apart from the domain. The cluster analysis of the 22 batches of medicinal material showed that 17 batches of Oldenlandia diffusa were in a cluster while 5 batches of adulterants were excluded. Further cluster analysis was carried out for the quality consistency of 17 batches of Oldenlandia diffusa and accordingly they were devided into 4 clusters. With the combination of chemometrics means, the HPLC fingerprint chromatogram provides a method for evaluation of authenticity and quality control of Oldenlandia diffusa, which is favorable to improve overall quality control of Oldenlandia diffusa.

Is burnout separable from depression in cluster analysis? A longitudinal study.

PubMed

Bianchi, Renzo; Schonfeld, Irvin Sam; Laurent, Eric

2015-06-01

Whether burnout and depression represent distinct pathologies is unclear. The aim of this study was to examine whether burnout and depressive symptoms manifest themselves separately from each other or are so closely intertwined as to reflect the same phenomenon. A two-wave longitudinal study involving 627 French schoolteachers (73 % female) was conducted. Burnout was assessed with the Maslach Burnout Inventory and depression with the 9-item depression module of the Patient Health Questionnaire. Burnout and depressive symptoms clustered both at baseline and follow-up. Cluster membership at time 1 (T1) predicted cases of burnout and depression at time 2 (T2), controlling for gender, age, length of employment, lifetime history of depression, and antidepressant intake. Changes in burnout and depressive symptoms from T1 to T2 were found to overlap. Teachers with increasing burnout experienced increases in depression and teachers with decreasing burnout experienced decreases in depression. In addition, emotional exhaustion, the core of burnout, was more strongly associated with depression than with depersonalization, the second dimension of burnout, underlining an inconsistency in the conceptualization of the burnout syndrome. Our results are consistent with recent findings showing qualitative and quantitative symptom overlap of burnout with depression. The close interconnection of burnout and depression questions the relevance of a nosological distinction between the two entities. Emotional exhaustion and depersonalization, the two main dimensions of burnout, may be better conceptualized as depressive responses to adverse occupational environments than as components of a separate entity.

Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application

PubMed Central

Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

2009-01-01

Background microRNAs (miRNAs) are single-stranded RNA molecules of about 20–23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. Results GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. Conclusion GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA. PMID:19534746

Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application.

PubMed

Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

2009-06-16

microRNAs (miRNAs) are single-stranded RNA molecules of about 20-23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA.

Cell separation: Terminology and practical considerations

PubMed Central

Tomlinson, Sophie; Yang, Xuebin B; Kirkham, Jennifer

2013-01-01

Cell separation is a powerful tool in biological research. Increasing usage, particularly within the tissue engineering and regenerative medicine communities, means that researchers from a diverse range of backgrounds are utilising cell separation technologies. This review aims to offer potential solutions to cell sorting problems and to clarify common ambiguities in terminology and experimental design. The frequently used cell separation terms of ‘purity’, ‘recovery’ and ‘viability’ are discussed, and attempts are made to reach a consensus view of their sometimes ambiguous meanings. The importance of appropriate experimental design is considered, with aspects such as marker expression, tissue isolation and original cell population analysis discussed. Finally, specific technical issues such as cell clustering, dead cell removal and non-specific antibody binding are considered and potential solutions offered. The solutions offered may provide a starting point to improve the quality of cell separations achieved by both the novice and experienced researcher alike. PMID:23440031

Proper motions in the VVV Survey: Results for more than 15 million stars across NGC 6544

NASA Astrophysics Data System (ADS)

Contreras Ramos, R.; Zoccali, M.; Rojas, F.; Rojas-Arriagada, A.; Gárate, M.; Huijse, P.; Gran, F.; Soto, M.; Valcarce, A. A. R.; Estévez, P. A.; Minniti, D.

2017-12-01

Context. In the last six years, the VISTA Variable in the Vía Láctea (VVV) survey mapped 562 sq. deg. across the bulge and southern disk of the Galaxy. However, a detailed study of these regions, which includes 36 globular clusters (GCs) and thousands of open clusters is by no means an easy challenge. High differential reddening and severe crowding along the line of sight makes highly hamper to reliably distinguish stars belonging to different populations and/or systems. Aims: The aim of this study is to separate stars that likely belong to the Galactic GC NGC 6544 from its surrounding field by means of proper motion (PM) techniques. Methods: This work was based upon a new astrometric reduction method optimized for images of the VVV survey. Results: PSF-fitting photometry over the six years baseline of the survey allowed us to obtain a mean precision of 0.51 mas yr-1, in each PM coordinate, for stars with Ks< 15 mag. In the area studied here, cluster stars separate very well from field stars, down to the main sequence turnoff and below, allowing us to derive for the first time the absolute PM of NGC 6544. Isochrone fitting on the clean and differential reddening corrected cluster color magnitude diagram yields an age of 11-13 Gyr, and metallicity [Fe/H] =-1.5 dex, in agreement with previous studies restricted to the cluster core. We were able to derive the cluster orbit assuming an axisymmetric model of the Galaxy and conclude that NGC 6544 is likely a halo GC. We have not detected tidal tail signatures associated to the cluster, but a remarkable elongation in the galactic center direction has been found. The precision achieved in the PM determination also allows us to separate bulge stars from foreground disk stars, enabling the kinematical selection of bona fide bulge stars across the whole survey area. Conclusions: Kinematical techniques are a fundamental step toward disentangling different stellar populations that overlap in a studied field. Our results show that VVV data is perfectly suitable for this kind of analysis. Based on observations taken with ESO telescopes at Paranal Observatory under programme IDs 179.B-2002.

Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing.

PubMed

Sarrafzadeh, Omid; Dehnavi, Alireza Mehri

2015-01-01

Segmentation of leukocytes acts as the foundation for all automated image-based hematological disease recognition systems. Most of the time, hematologists are interested in evaluation of white blood cells only. Digital image processing techniques can help them in their analysis and diagnosis. The main objective of this paper is to detect leukocytes from a blood smear microscopic image and segment them into their two dominant elements, nucleus and cytoplasm. The segmentation is conducted using two stages of applying K-means clustering. First, the nuclei are segmented using K-means clustering. Then, a proposed method based on region growing is applied to separate the connected nuclei. Next, the nuclei are subtracted from the original image. Finally, the cytoplasm is segmented using the second stage of K-means clustering. The results indicate that the proposed method is able to extract the nucleus and cytoplasm regions accurately and works well even though there is no significant contrast between the components in the image. In this paper, a method based on K-means clustering and region growing is proposed in order to detect leukocytes from a blood smear microscopic image and segment its components, the nucleus and the cytoplasm. As region growing step of the algorithm relies on the information of edges, it will not able to separate the connected nuclei more accurately in poor edges and it requires at least a weak edge to exist between the nuclei. The nucleus and cytoplasm segments of a leukocyte can be used for feature extraction and classification which leads to automated leukemia detection.

Nucleus and cytoplasm segmentation in microscopic images using K-means clustering and region growing

PubMed Central

Sarrafzadeh, Omid; Dehnavi, Alireza Mehri

2015-01-01

Background: Segmentation of leukocytes acts as the foundation for all automated image-based hematological disease recognition systems. Most of the time, hematologists are interested in evaluation of white blood cells only. Digital image processing techniques can help them in their analysis and diagnosis. Materials and Methods: The main objective of this paper is to detect leukocytes from a blood smear microscopic image and segment them into their two dominant elements, nucleus and cytoplasm. The segmentation is conducted using two stages of applying K-means clustering. First, the nuclei are segmented using K-means clustering. Then, a proposed method based on region growing is applied to separate the connected nuclei. Next, the nuclei are subtracted from the original image. Finally, the cytoplasm is segmented using the second stage of K-means clustering. Results: The results indicate that the proposed method is able to extract the nucleus and cytoplasm regions accurately and works well even though there is no significant contrast between the components in the image. Conclusions: In this paper, a method based on K-means clustering and region growing is proposed in order to detect leukocytes from a blood smear microscopic image and segment its components, the nucleus and the cytoplasm. As region growing step of the algorithm relies on the information of edges, it will not able to separate the connected nuclei more accurately in poor edges and it requires at least a weak edge to exist between the nuclei. The nucleus and cytoplasm segments of a leukocyte can be used for feature extraction and classification which leads to automated leukemia detection. PMID:26605213

International linkage of two food-borne hepatitis A clusters through traceback of mussels, the Netherlands, 2012.

PubMed

Boxman, Ingeborg L A; Verhoef, Linda; Vennema, Harry; Ngui, Siew-Lin; Friesema, Ingrid H M; Whiteside, Chris; Lees, David; Koopmans, Marion

2016-01-01

This report describes an outbreak investigation starting with two closely related suspected food-borne clusters of Dutch hepatitis A cases, nine primary cases in total, with an unknown source in the Netherlands. The hepatitis A virus (HAV) genotype IA sequences of both clusters were highly similar (459/460 nt) and were not reported earlier. Food questionnaires and a case-control study revealed an association with consumption of mussels. Analysis of mussel supply chains identified the most likely production area. International enquiries led to identification of a cluster of patients near this production area with identical HAV sequences with onsets predating the first Dutch cluster of cases. The most likely source for this cluster was a case who returned from an endemic area in Central America, and a subsequent household cluster from which treated domestic sewage was discharged into the suspected mussel production area. Notably, mussels from this area were also consumed by a separate case in the United Kingdom sharing an identical strain with the second Dutch cluster. In conclusion, a small number of patients in a non-endemic area led to geographically dispersed hepatitis A outbreaks with food as vehicle. This link would have gone unnoticed without sequence analyses and international collaboration.

Structural characterization of a magnetic granular system under a time-dependent magnetic field: Voronoi tessellation and multifractal analysis

NASA Astrophysics Data System (ADS)

Moctezuma, R. E.; Arauz-Lara, J. L.; Donado, F.

2018-04-01

The structure of a two-dimensional magnetic granular system was determined by multifractal and Voronoi polygon analysis for a wide range of particle concentrations. Randomizing of the particle motions are produced by applying to the system a time-dependent sinusoidal magnetic field directed along the vertical direction. Both repulsive and attractive short-range interactions between the particles are induced. A direct observation of such system shows qualitatively that, as particle concentration increases, the structure evolves from being liquid-like at low particle concentrations to solid-like at high concentrations. We observe the formation of clusters which are small and weakly bonded and short-lived at low concentrations. Above a threshold particle concentration, clusters grow larger and are more strongly attached. In the system, one can distinguish the mobile particles from the immobile particles belonging to clusters, they can be considered separately as two different phases, a fluid and a solid. We determined the information entropy of the system as a whole and separately from each phase as particle concentration increases. The distribution of the Voronoi polygon areas are well fitted by a two-parameter gamma distribution and we have found that the regularity factor shows a notable change when pieces of the solid phase start to form. The methods we use here show that they can use even when the system is heterogeneous and they provide information when changes start.

Sequence and genetic organization of a Zymomonas mobilis gene cluster that encodes several enzymes of glucose metabolism

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

Barnell, W.O.; Kyung Cheol Yi; Conway, T.

1990-12-01

The Zymomonas mobilis genes that encode glucose-6-phosphate dehydrogenase (zwf), 6-phosphogluconate dehydratase (edd), and glucokinase (glk) were cloned independently by genetic complementation of specific defects in Escherichia coli metabolism. The identify of these cloned genes was confirmed by various biochemical means. Nucleotide sequence analysis established that these three genes are clustered on the genome and revealed an additional open reading frame in this region that has significant amino acid identity to the E.coli xylose-proton symporter and the human glucose transporter. On the basis of this evidence and structural analysis of the deduced primary amino acid sequence, this gene is believed tomore » encode the Z. mobilis glucose-facilitated diffusion protein, glf. The four genes in the 6-kb cluster are organized in the order glf, zwf, edd, glk. The glf and zwf genes are separated by 146 bp. The zwf and edd genes overlap by 8 bp, and their expression may be translationally coupled. The edd and glk genes are separated by 203 bp. The glk gene is followed by tandem transcriptional terminators. The four genes appear to be organized in an operon. Such an arrangement of the genes that govern glucose uptake and the first three steps of the Entner-Doudoroff glycolytic pathway provides the organism with a mechanism for carefully regulating the levels of the enzymes that control carbon flux into the pathway.« less

Genetic diversity of populations and clones of Rhopilema esculentum in China based on AFLP analysis

NASA Astrophysics Data System (ADS)

Qiao, Hongjin; Liu, Xiangquan; Zhang, Xijia; Jiang, Haibin; Wang, Jiying; Zhang, Limin

2013-03-01

Amplified fragment length polymorphisms (AFLP) markers were developed to assess the genetic variation of populations and clones of Rhopilema esculentum Kishinouye (Scyphozoa, Rhizostomatidae). One hundred and seventy-nine loci from 56 individuals of two hatchery populations and two wild populations were genotyped with five primer combinations. The polymorphic ratio, Shannon's diversity index and average heterozygosity were 70.3%, 0.346 and 0.228 for the white hatchery population, 74.3%, 0.313, and 0.201 for the red hatchery population, 79.3%, 0.349, and 0.224 for the Jiangsu wild population, and 74.9%, 0.328 and 0.210 for the Penglai wild population, respectively. Thus, all populations had a relatively high level of genetic diversity. A specific band was identified that could separate the white from the red hatchery population. There was 84.85% genetic differentiation within populations. Individual cluster analysis using unweighted pair-group method with arithmetic mean (UPGMA) suggested that hatchery populations and wild populations could be divided. For the hatchery populations, the white and red populations clustered separately; however, for the wild populations, Penglai and Jiangsu populations clustered together. The genetic diversity at the clone level was also determined. Our data suggest that there are relatively high genetic diversities within populations but low genetic differentiation between populations, which may be related to the long-term use of germplasm resources from Jiangsu Province for artificial seeding and releasing. These findings will benefit the artificial seeding and conservation of the germplasm resources.

Joining X-Ray to Lensing: An Accurate Combined Analysis of MACS J0416.1-2403

NASA Astrophysics Data System (ADS)

Bonamigo, M.; Grillo, C.; Ettori, S.; Caminha, G. B.; Rosati, P.; Mercurio, A.; Annunziatella, M.; Balestra, I.; Lombardi, M.

2017-06-01

We present a novel approach for a combined analysis of X-ray and gravitational lensing data and apply this technique to the merging galaxy cluster MACS J0416.1-2403. The method exploits the information on the intracluster gas distribution that comes from a fit of the X-ray surface brightness and then includes the hot gas as a fixed mass component in the strong-lensing analysis. With our new technique, we can separate the collisional from the collision-less diffuse mass components, thus obtaining a more accurate reconstruction of the dark matter distribution in the core of a cluster. We introduce an analytical description of the X-ray emission coming from a set of dual pseudo-isothermal elliptical mass distributions, which can be directly used in most lensing softwares. By combining Chandra observations with Hubble Frontier Fields imaging and Multi Unit Spectroscopic Explorer spectroscopy in MACS J0416.1-2403, we measure a projected gas-to-total mass fraction of approximately 10% at 350 kpc from the cluster center. Compared to the results of a more traditional cluster mass model (diffuse halos plus member galaxies), we find a significant difference in the cumulative projected mass profile of the dark matter component and that the dark matter over total mass fraction is almost constant, out to more than 350 kpc. In the coming era of large surveys, these results show the need of multiprobe analyses for detailed dark matter studies in galaxy clusters.

Analysis on unevenness of skin color using the melanin and hemoglobin components separated by independent component analysis of skin color image

NASA Astrophysics Data System (ADS)

Ojima, Nobutoshi; Fujiwara, Izumi; Inoue, Yayoi; Tsumura, Norimichi; Nakaguchi, Toshiya; Iwata, Kayoko

2011-03-01

Uneven distribution of skin color is one of the biggest concerns about facial skin appearance. Recently several techniques to analyze skin color have been introduced by separating skin color information into chromophore components, such as melanin and hemoglobin. However, there are not many reports on quantitative analysis of unevenness of skin color by considering type of chromophore, clusters of different sizes and concentration of the each chromophore. We propose a new image analysis and simulation method based on chromophore analysis and spatial frequency analysis. This method is mainly composed of three techniques: independent component analysis (ICA) to extract hemoglobin and melanin chromophores from a single skin color image, an image pyramid technique which decomposes each chromophore into multi-resolution images, which can be used for identifying different sizes of clusters or spatial frequencies, and analysis of the histogram obtained from each multi-resolution image to extract unevenness parameters. As the application of the method, we also introduce an image processing technique to change unevenness of melanin component. As the result, the method showed high capabilities to analyze unevenness of each skin chromophore: 1) Vague unevenness on skin could be discriminated from noticeable pigmentation such as freckles or acne. 2) By analyzing the unevenness parameters obtained from each multi-resolution image for Japanese ladies, agerelated changes were observed in the parameters of middle spatial frequency. 3) An image processing system modulating the parameters was proposed to change unevenness of skin images along the axis of the obtained age-related change in real time.

A pattern recognition approach to transistor array parameter variance

NASA Astrophysics Data System (ADS)

da F. Costa, Luciano; Silva, Filipi N.; Comin, Cesar H.

2018-06-01

The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives.

Comparative Chemometric Analysis for Classification of Acids and Bases via a Colorimetric Sensor Array.

PubMed

Kangas, Michael J; Burks, Raychelle M; Atwater, Jordyn; Lukowicz, Rachel M; Garver, Billy; Holmes, Andrea E

2018-02-01

With the increasing availability of digital imaging devices, colorimetric sensor arrays are rapidly becoming a simple, yet effective tool for the identification and quantification of various analytes. Colorimetric arrays utilize colorimetric data from many colorimetric sensors, with the multidimensional nature of the resulting data necessitating the use of chemometric analysis. Herein, an 8 sensor colorimetric array was used to analyze select acid and basic samples (0.5 - 10 M) to determine which chemometric methods are best suited for classification quantification of analytes within clusters. PCA, HCA, and LDA were used to visualize the data set. All three methods showed well-separated clusters for each of the acid or base analytes and moderate separation between analyte concentrations, indicating that the sensor array can be used to identify and quantify samples. Furthermore, PCA could be used to determine which sensors showed the most effective analyte identification. LDA, KNN, and HQI were used for identification of analyte and concentration. HQI and KNN could be used to correctly identify the analytes in all cases, while LDA correctly identified 95 of 96 analytes correctly. Additional studies demonstrated that controlling for solvent and image effects was unnecessary for all chemometric methods utilized in this study.

Assessment of metal pollution based on multivariate statistical modeling of 'hot spot' sediments from the Black Sea.

PubMed

Simeonov, V; Massart, D L; Andreev, G; Tsakovski, S

2000-11-01

The paper deals with application of different statistical methods like cluster and principal components analysis (PCA), partial least squares (PLSs) modeling. These approaches are an efficient tool in achieving better understanding about the contamination of two gulf regions in Black Sea. As objects of the study, a collection of marine sediment samples from Varna and Bourgas "hot spots" gulf areas are used. In the present case the use of cluster and PCA make it possible to separate three zones of the marine environment with different levels of pollution by interpretation of the sediment analysis (Bourgas gulf, Varna gulf and lake buffer zone). Further, the extraction of four latent factors offers a specific interpretation of the possible pollution sources and separates natural from anthropogenic factors, the latter originating from contamination by chemical, oil refinery and steel-work enterprises. Finally, the PLSs modeling gives a better opportunity in predicting contaminant concentration on tracer (or tracers) element as compared to the one-dimensional approach of the baseline models. The results of the study are important not only in local aspect as they allow quick response in finding solutions and decision making but also in broader sense as a useful environmetrical methodology.

Classification of LC columns based on the QSRR method and selectivity toward moclobemide and its metabolites.

PubMed

Plenis, Alina; Olędzka, Ilona; Bączek, Tomasz

2013-05-05

This paper focuses on a comparative study of the column classification system based on the quantitative structure-retention relationships (QSRR method) and column performance in real biomedical analysis. The assay was carried out for the LC separation of moclobemide and its metabolites in human plasma, using a set of 24 stationary phases. The QSRR models established for the studied stationary phases were compared with the column test performance results under two chemometric techniques - the principal component analysis (PCA) and the hierarchical clustering analysis (HCA). The study confirmed that the stationary phase classes found closely related by the QSRR approach yielded comparable separation for moclobemide and its metabolites. Therefore, the QSRR method could be considered supportive in the selection of a suitable column for the biomedical analysis offering the selection of similar or dissimilar columns with a relatively higher certainty. Copyright © 2013 Elsevier B.V. All rights reserved.

Defining clusters in APT reconstructions of ODS steels.

PubMed

Williams, Ceri A; Haley, Daniel; Marquis, Emmanuelle A; Smith, George D W; Moody, Michael P

2013-09-01

Oxide nanoclusters in a consolidated Fe-14Cr-2W-0.3Ti-0.3Y₂O₃ ODS steel and in the alloy powder after mechanical alloying (but before consolidation) are investigated by atom probe tomography (APT). The maximum separation method is a standard method to define and characterise clusters from within APT data, but this work shows that the extent of clustering between the two materials is sufficiently different that the nanoclusters in the mechanically alloyed powder and in the consolidated material cannot be compared directly using the same cluster selection parameters. As the cluster selection parameters influence the size and composition of the clusters significantly, a procedure to optimise the input parameters for the maximum separation method is proposed by sweeping the d(max) and N(min) parameter space. By applying this method of cluster parameter selection combined with a 'matrix correction' to account for trajectory aberrations, differences in the oxide nanoclusters can then be reliably quantified. Copyright © 2012 Elsevier B.V. All rights reserved.

Cluster-collision frequency. I. The long-range intercluster potential

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

Amadon, A.S.; Marlow, W.H.

1991-05-15

In recent years, gas-borne atomic and molecular clusters have emerged as subjects of basic physical and chemical interest and are gaining recognition for their importance in numerous applications. To calculate the evolution of the mass distribution of these clusters, their thermal collision rates are required. For computing these collision rates, the long-range interaction energy between clusters is required and is the subject of this paper. Utilizing a formulation of the iterated van der Waals interaction over discrete molecules that can be shown to converge with increasing numbers of atoms to the Lifshitz--van der Waals interaction for condensed matter, we calculatemore » the interaction energy as a function of center-of-mass separation for identical pairs of clusters of 13, 33, and 55 molecules of carbon tetrachloride in icosahedral and dodecahedral configurations. Two different relative orientations are chosen for each pair of clusters, and the energies are compared with energies calculated from the standard formula for continuum matter derived by summing over pair interactions with the Hamaker constant calculated according to Lifshitz theory. The results of these calculations give long-range interaction energies that assume typical adhesion-type values at cluster contact, unlike the unbounded results for the Lifshitz-Hamaker model. The relative difference between the discrete molecular energies and the continuum energies vanishes for {ital r}{sup *}{approx}2, where {ital r}{sup *} is the center-of-mass separation distance in units of cluster diameter. For larger separations, the relative difference changes sign, showing a value of approximately 15%, with the difference diminishing for increasing-sized clusters.« less

Mechanisms for the clustering of inertial particles in the inertial range of isotropic turbulence

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

Bragg, Andrew D.; Ireland, Peter J.; Collins, Lance R.

2015-08-27

In this study, we consider the physical mechanism for the clustering of inertial particles in the inertial range of isotropic turbulence. We analyze the exact, but unclosed, equation governing the radial distribution function (RDF) and compare the mechanisms it describes for clustering in the dissipation and inertial ranges. We demonstrate that in the limit St r <<1, where St r is the Stokes number based on the eddy turnover time scale at separation r, the clustering in the inertial range can be understood to be due to the preferential sampling of the coarse-grained fluid velocity gradient tensor at that scale.more » When St r≳O(1) this mechanism gives way to a nonlocal clustering mechanism. These findings reveal that the clustering mechanisms in the inertial range are analogous to the mechanisms that we identified for the dissipation regime. Further, we discuss the similarities and differences between the clustering mechanisms we identify in the inertial range and the “sweep-stick” mechanism developed by Coleman and Vassilicos. We show that the idea that initial particles are swept along with acceleration stagnation points is only approximately true because there always exists a finite difference between the velocity of the acceleration stagnation points and the local fluid velocity. This relative velocity is sufficient to allow particles to traverse the average distance between the stagnation points within the correlation time scale of the acceleration field. We also show that the stick part of the mechanism is only valid for St r<<1 in the inertial range. We emphasize that our clustering mechanism provides the more fundamental explanation since it, unlike the sweep-stick mechanism, is able to explain clustering in arbitrary spatially correlated velocity fields. We then consider the closed, model equation for the RDF given in Zaichik and Alipchenkov and use this, together with the results from our analysis, to predict the analytic form of the RDF in the inertial range for St r<<1, which, unlike that in the dissipation range, is not scale invariant. Finally, the results are in good agreement with direct numerical simulations, provided the separations are well within the inertial range.« less

Spatial clustering of fatal, and non-fatal, suicide in new South Wales, Australia: implications for evidence-based prevention.

PubMed

Torok, Michelle; Konings, Paul; Batterham, Philip J; Christensen, Helen

2017-10-06

Rates of suicide appear to be increasing, indicating a critical need for more effective prevention initiatives. To increase the efficacy of future prevention initiatives, we examined the spatial distribution of suicide deaths and suicide attempts in New South Wales (NSW), Australia, to identify where high incidence 'suicide clusters' were occurring. Such clusters represent candidate regions where intervention is critically needed, and likely to have the greatest impact, thus providing an evidence-base for the targeted prioritisation of resources. Analysis is based on official suicide mortality statistics for NSW, provided by the Australian Bureau of Statistics, and hospital separations for non-fatal intentional self-harm, provided through the NSW Health Admitted Patient Data Collection at a Statistical Area 2 (SA2) geography. Geographical Information System (GIS) techniques were applied to detect suicide clusters occurring between 2005 and 2013 (aggregated), for persons aged over 5 years. The final dataset contained 5466 mortality and 86,017 non-fatal intentional self-harm cases. In total, 25 Local Government Areas were identified as primary or secondary likely candidate regions for intervention. Together, these regions contained approximately 200 SA2 level suicide clusters, which represented 46% (n = 39,869) of hospital separations and 43% (n = 2330) of suicide deaths between 2005 and 2013. These clusters primarily converged on the Eastern coastal fringe of NSW. Crude rates of suicide deaths and intentional self-harm differed at the Local Government Areas (LGA) level in NSW. There was a tendency for primary suicide clusters to occur within metropolitan and coastal regions, rather than rural areas. The findings demonstrate the importance of taking geographical variation of suicidal behaviour into account, prior to development and implementation of prevention initiatives, so that such initiatives can target key problem areas where they are likely to have maximal impact.

Polymer depletion-driven cluster aggregation and initial phase separation in charged nanosized colloids

NASA Astrophysics Data System (ADS)

Gögelein, Christoph; Nägele, Gerhard; Buitenhuis, Johan; Tuinier, Remco; Dhont, Jan K. G.

2009-05-01

We study polymer depletion-driven cluster aggregation and initial phase separation in aqueous dispersions of charge-stabilized silica spheres, where the ionic strength and polymer (dextran) concentration are systematically varied, using dynamic light scattering and visual observation. Without polymers and for increasing salt and colloid content, the dispersions become increasingly unstable against irreversible cluster formation. By adding nonadsorbing polymers, a depletion-driven attraction is induced, which lowers the stabilizing Coulomb barrier and enhances the cluster growth rate. The initial growth rate increases with increasing polymer concentration and decreases with increasing polymer molar mass. These observations can be quantitatively understood by an irreversible dimer formation theory based on the classical Derjaguin, Landau, Verwey, and Overbeek pair potential, with the depletion attraction modeled by the Asakura-Oosawa-Vrij potential. At low colloid concentration, we observe an exponential cluster growth rate for all polymer concentrations considered, indicating a reaction-limited aggregation mechanism. At sufficiently high polymer and colloid concentrations, and lower salt content, a gas-liquidlike demixing is observed initially. Later on, the system separates into a gel and fluidlike phase. The experimental time-dependent state diagram is compared to the theoretical equilibrium phase diagram obtained from a generalized free-volume theory and is discussed in terms of an initial reversible phase separation process in combination with irreversible aggregation at later times.

Polymer depletion-driven cluster aggregation and initial phase separation in charged nanosized colloids.

PubMed

Gögelein, Christoph; Nägele, Gerhard; Buitenhuis, Johan; Tuinier, Remco; Dhont, Jan K G

2009-05-28

We study polymer depletion-driven cluster aggregation and initial phase separation in aqueous dispersions of charge-stabilized silica spheres, where the ionic strength and polymer (dextran) concentration are systematically varied, using dynamic light scattering and visual observation. Without polymers and for increasing salt and colloid content, the dispersions become increasingly unstable against irreversible cluster formation. By adding nonadsorbing polymers, a depletion-driven attraction is induced, which lowers the stabilizing Coulomb barrier and enhances the cluster growth rate. The initial growth rate increases with increasing polymer concentration and decreases with increasing polymer molar mass. These observations can be quantitatively understood by an irreversible dimer formation theory based on the classical Derjaguin, Landau, Verwey, and Overbeek pair potential, with the depletion attraction modeled by the Asakura-Oosawa-Vrij potential. At low colloid concentration, we observe an exponential cluster growth rate for all polymer concentrations considered, indicating a reaction-limited aggregation mechanism. At sufficiently high polymer and colloid concentrations, and lower salt content, a gas-liquidlike demixing is observed initially. Later on, the system separates into a gel and fluidlike phase. The experimental time-dependent state diagram is compared to the theoretical equilibrium phase diagram obtained from a generalized free-volume theory and is discussed in terms of an initial reversible phase separation process in combination with irreversible aggregation at later times.

Locating sources within a dense sensor array using graph clustering

NASA Astrophysics Data System (ADS)

Gerstoft, P.; Riahi, N.

2017-12-01

We develop a model-free technique to identify weak sources within dense sensor arrays using graph clustering. No knowledge about the propagation medium is needed except that signal strengths decay to insignificant levels within a scale that is shorter than the aperture. We then reinterpret the spatial coherence matrix of a wave field as a matrix whose support is a connectivity matrix of a graph with sensors as vertices. In a dense network, well-separated sources induce clusters in this graph. The geographic spread of these clusters can serve to localize the sources. The support of the covariance matrix is estimated from limited-time data using a hypothesis test with a robust phase-only coherence test statistic combined with a physical distance criterion. The latter criterion ensures graph sparsity and thus prevents clusters from forming by chance. We verify the approach and quantify its reliability on a simulated dataset. The method is then applied to data from a dense 5200 element geophone array that blanketed of the city of Long Beach (CA). The analysis exposes a helicopter traversing the array and oil production facilities.

Dynamic Evolution Model Based on Social Network Services

NASA Astrophysics Data System (ADS)

Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

2013-11-01

Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

Cluster formation and phase separation in heteronuclear Janus dumbbells

NASA Astrophysics Data System (ADS)

Munaò, G.; O'Toole, P.; Hudson, T. S.; Costa, D.; Caccamo, C.; Sciortino, F.; Giacometti, A.

2015-06-01

We have recently investigated the phase behavior of model colloidal dumbbells constituted by two identical tangent hard spheres, with the first being surrounded by an attractive square-well interaction (Janus dumbbells, Munaó et al 2014 Soft Matter 10 5269). Here we extend our previous analysis by introducing in the model the size asymmetry of the hard-core diameters and study the enriched phase scenario thereby obtained. By employing standard Monte Carlo simulations we show that in such ‘heteronuclear Janus dumbbells’ a larger hard-sphere site promotes the formation of clusters, whereas in the opposite condition a gas-liquid phase separation takes place, with a narrow interval of intermediate asymmetries wherein the two phase behaviors may compete. In addition, some peculiar geometrical arrangements, such as lamellæ, are observed only around the perfectly symmetric case. A qualitative agreement is found with recent experimental results, where it is shown that the roughness of molecular surfaces in heterogeneous dimers leads to the formation of colloidal micelles.

Clustering of GPS velocities in the Mojave Block, southeastern California

USGS Publications Warehouse

Savage, James C.; Simpson, Robert W.

2013-01-01

We find subdivisions within the Mojave Block using cluster analysis to identify groupings in the velocities observed at GPS stations there. The clusters are represented on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. The most significant representation as judged by the gap test involves 4 clusters within the Mojave Block. The fault systems bounding the clusters from east to west are 1) the faults defining the eastern boundary of the Northeast Mojave Domain extended southward to connect to the Hector Mine rupture, 2) the Calico-Paradise fault system, 3) the Landers-Blackwater fault system, and 4) the Helendale-Lockhart fault system. This division of the Mojave Block is very similar to that proposed by Meade and Hager. However, no cluster boundary coincides with the Garlock Fault, the northern boundary of the Mojave Block. Rather, the clusters appear to continue without interruption from the Mojave Block north into the southern Walker Lane Belt, similar to the continuity across the Garlock Fault of the shear zone along the Blackwater-Little Lake fault system observed by Peltzer et al. Mapped traces of individual faults in the Mojave Block terminate within the block and do not continue across the Garlock Fault [Dokka and Travis, ].

Cluster analysis of obsessive-compulsive spectrum disorders in patients with obsessive-compulsive disorder: clinical and genetic correlates.

PubMed

Lochner, Christine; Hemmings, Sian M J; Kinnear, Craig J; Niehaus, Dana J H; Nel, Daniel G; Corfield, Valerie A; Moolman-Smook, Johanna C; Seedat, Soraya; Stein, Dan J

2005-01-01

Comorbidity of certain obsessive-compulsive spectrum disorders (OCSDs; such as Tourette's disorder) in obsessive-compulsive disorder (OCD) may serve to define important OCD subtypes characterized by differing phenomenology and neurobiological mechanisms. Comorbidity of the putative OCSDs in OCD has, however, not often been systematically investigated. The Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition , Axis I Disorders-Patient Version as well as a Structured Clinical Interview for Putative OCSDs (SCID-OCSD) were administered to 210 adult patients with OCD (N = 210, 102 men and 108 women; mean age, 35.7 +/- 13.3). A subset of Caucasian subjects (with OCD, n = 171; control subjects, n = 168), including subjects from the genetically homogeneous Afrikaner population (with OCD, n = 77; control subjects, n = 144), was genotyped for polymorphisms in genes involved in monoamine function. Because the items of the SCID-OCSD are binary (present/absent), a cluster analysis (Ward's method) using the items of SCID-OCSD was conducted. The association of identified clusters with demographic variables (age, gender), clinical variables (age of onset, obsessive-compulsive symptom severity and dimensions, level of insight, temperament/character, treatment response), and monoaminergic genotypes was examined. Cluster analysis of the OCSDs in our sample of patients with OCD identified 3 separate clusters at a 1.1 linkage distance level. The 3 clusters were named as follows: (1) "reward deficiency" (including trichotillomania, Tourette's disorder, pathological gambling, and hypersexual disorder), (2) "impulsivity" (including compulsive shopping, kleptomania, eating disorders, self-injury, and intermittent explosive disorder), and (3) "somatic" (including body dysmorphic disorder and hypochondriasis). Several significant associations were found between cluster scores and other variables; for example, cluster I scores were associated with earlier age of onset of OCD and the presence of tics, cluster II scores were associated with female gender and childhood emotional abuse, and cluster III scores were associated with less insight and with somatic obsessions and compulsions. However, none of these clusters were associated with any particular genetic variant. Analysis of comorbid OCSDs in OCD suggested that these lie on a number of different dimensions. These dimensions are partially consistent with previous theoretical approaches taken toward classifying OCD spectrum disorders. The lack of genetic validation of these clusters in the present study may indicate the involvement of other, as yet untested, genes. Further genetic and cluster analyses of comorbid OCSDs in OCD may ultimately contribute to a better delineation of OCD endophenotypes.

Comparison of the DiversiLab Repetitive Element PCR System with spa Typing and Pulsed-Field Gel Electrophoresis for Clonal Characterization of Methicillin-Resistant Staphylococcus aureus▿

PubMed Central

Babouee, B.; Frei, R.; Schultheiss, E.; Widmer, A. F.; Goldenberger, D.

2011-01-01

The emergence of methicillin-resistant Staphylococcus aureus (MRSA) has become an increasing problem worldwide in recent decades. Molecular typing methods have been developed to identify clonality of strains and monitor spread of MRSA. We compared a new commercially available DiversiLab (DL) repetitive element PCR system with spa typing, spa clonal cluster analysis, and pulsed-field gel electrophoresis (PFGE) in terms of discriminatory power and concordance. A collection of 106 well-defined MRSA strains from our hospital was analyzed, isolated between 1994 and 2006. In addition, we analyzed 6 USA300 strains collected in our institution. DL typing separated the 106 MRSA isolates in 10 distinct clusters and 8 singleton patterns. Clustering analysis into spa clonal complexes resulted in 3 clusters: spa-CC 067/548, spa-CC 008, and spa-CC 012. The discriminatory powers (Simpson's index of diversity) were 0.982, 0.950, 0.846, and 0.757 for PFGE, spa typing, DL typing, and spa clonal clustering, respectively. DL typing and spa clonal clustering showed the highest concordance, calculated by adjusted Rand's coefficients. The 6 USA300 isolates grouped homogeneously into distinct PFGE and DL clusters, and all belonged to spa type t008 and spa-CC 008. Among the three methods, DL proved to be rapid and easy to perform. DL typing qualifies for initial screening during outbreak investigation. However, compared to PFGE and spa typing, DL typing has limited discriminatory power and therefore should be complemented by more discriminative methods in isolates that share identical DL patterns. PMID:21307215

Galaxy And Mass Assembly (GAMA): the signatures of galaxy interactions as viewed from small scale galaxy clustering

NASA Astrophysics Data System (ADS)

Gunawardhana, M. L. P.; Norberg, P.; Zehavi, I.; Farrow, D. J.; Loveday, J.; Hopkins, A. M.; Davies, L. J. M.; Wang, L.; Alpaslan, M.; Bland-Hawthorn, J.; Brough, S.; Holwerda, B. W.; Owers, M. S.; Wright, A. H.

2018-06-01

Statistical studies of galaxy-galaxy interactions often utilise net change in physical properties of progenitors as a function of the separation between their nuclei to trace both the strength and the observable timescale of their interaction. In this study, we use two-point auto, cross and mark correlation functions to investigate the extent to which small-scale clustering properties of star forming galaxies can be used to gain physical insight into galaxy-galaxy interactions between galaxies of similar optical brightness and stellar mass. The Hα star formers, drawn from the highly spatially complete Galaxy And Mass Assembly (GAMA) survey, show an increase in clustering on small separations. Moreover, the clustering strength shows a strong dependence on optical brightness and stellar mass, where (1) the clustering amplitude of optically brighter galaxies at a given separation is larger than that of optically fainter systems, (2) the small scale clustering properties (e.g. the strength, the scale at which the signal relative to the fiducial power law plateaus) of star forming galaxies appear to differ as a function of increasing optical brightness of galaxies. According to cross and mark correlation analyses, the former result is largely driven by the increased dust content in optically bright star forming galaxies. The latter could be interpreted as evidence of a correlation between interaction-scale and optical brightness of galaxies, where physical evidence of interactions between optically bright star formers, likely hosted within relatively massive halos, persist over larger separations than those between optically faint star formers.

The impact of clinical, demographic and risk factors on rates of HIV transmission: a population-based phylogenetic analysis in British Columbia, Canada.

PubMed

Poon, Art F Y; Joy, Jeffrey B; Woods, Conan K; Shurgold, Susan; Colley, Guillaume; Brumme, Chanson J; Hogg, Robert S; Montaner, Julio S G; Harrigan, P Richard

2015-03-15

The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission. We reconstructed molecular phylogenies from 27,296 anonymized bulk HIV pol sequences representing 7747 individuals in BC-about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion. Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter. Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Comparing Dark Energy Survey and HST-CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

NASA Astrophysics Data System (ADS)

Palmese, A.; Lahav, O.; Banerji, M.; Gruen, D.; Jouvel, S.; Melchior, P.; Aleksić, J.; Annis, J.; Diehl, H. T.; Hartley, W. G.; Jeltema, T.; Romer, A. K.; Rozo, E.; Rykoff, E. S.; Seitz, S.; Suchyta, E.; Zhang, Y.; Abbott, T. M. C.; Abdalla, F. B.; Allam, S.; Benoit-Lévy, A.; Bertin, E.; Brooks, D.; Buckley-Geer, E.; Burke, D. L.; Capozzi, D.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Crocce, M.; Cunha, C. E.; D'Andrea, C. B.; da Costa, L. N.; Desai, S.; Dietrich, J. P.; Doel, P.; Estrada, J.; Evrard, A. E.; Flaugher, B.; Frieman, J.; Gerdes, D. W.; Goldstein, D. A.; Gruendl, R. A.; Gutierrez, G.; Honscheid, K.; James, D. J.; Kuehn, K.; Kuropatkin, N.; Li, T. S.; Lima, M.; Maia, M. A. G.; Marshall, J. L.; Miller, C. J.; Miquel, R.; Nord, B.; Ogando, R.; Plazas, A. A.; Roodman, A.; Sanchez, E.; Scarpine, V.; Sevilla-Noarbe, I.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Swanson, M. E. C.; Tarle, G.; Thomas, D.; Tucker, D.; Vikram, V.

2016-12-01

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (five filters) with those from the Hubble Space Telescope Cluster Lensing And Supernova Survey (CLASH; 17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25 per cent of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensing studies with DES and CLASH. An analysis of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f⋆ = (6.8 ± 1.7) × 10-3 within a radius of r200c ≃ 2 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both data sets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the ˜100 000 clusters that will be observed within this survey and yield important information about galaxy evolution.

Comparing Dark Energy Survey and HST –CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

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

Palmese, A.; Lahav, O.; Banerji, M.

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (five filters) with those from the Hubble Space Telescope Cluster Lensing And Supernova Survey (CLASH; 17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25 per cent of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensingmore » studies with DES and CLASH. An analysis of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f(star) = (6.8 +/- 1.7) x 10(-3) within a radius of r(200c) similar or equal to 2 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both data sets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the similar to 100 000 clusters that will be observed within this survey and yield important information about galaxy evolution.« less

Domain Evolution and Functional Diversification of Sulfite Reductases

NASA Astrophysics Data System (ADS)

Dhillon, Ashita; Goswami, Sulip; Riley, Monica; Teske, Andreas; Sogin, Mitchell

2005-02-01

Sulfite reductases are key enzymes of assimilatory and dissimilatory sulfur metabolism, which occur in diverse bacterial and archaeal lineages. They share a highly conserved domain "C-X5-C-n-C-X3-C" for binding siroheme and iron-sulfur clusters that facilitate electron transfer to the substrate. For each sulfite reductase cluster, the siroheme-binding domain is positioned slightly differently at the N-terminus of dsrA and dsrB, while in the assimilatory proteins the siroheme domain is located at the C-terminus. Our sequence and phylogenetic analysis of the siroheme-binding domain shows that sulfite reductase sequences diverged from a common ancestor into four separate clusters (aSir, alSir, dsr, and asrC) that are biochemically distinct; each serves a different assimilatory or dissimilatory role in sulfur metabolism. The phylogenetic distribution and functional grouping in sulfite reductase clusters (dsrA and dsrB vs. aSiR, asrC, and alSir) suggest that their functional diversification during evolution may have preceded the bacterial/archaeal divergence.

Individualization as Driving Force of Clustering Phenomena in Humans

PubMed Central

Mäs, Michael; Flache, Andreas; Helbing, Dirk

2010-01-01

One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict “monoculture” in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering. PMID:20975937

Analysis of chitin-binding proteins from Manduca sexta provides new insights into evolution of peritrophin A-type chitin-binding domains in insects.

PubMed

Tetreau, Guillaume; Dittmer, Neal T; Cao, Xiaolong; Agrawal, Sinu; Chen, Yun-Ru; Muthukrishnan, Subbaratnam; Haobo, Jiang; Blissard, Gary W; Kanost, Michael R; Wang, Ping

2015-07-01

In insects, chitin is a major structural component of the cuticle and the peritrophic membrane (PM). In nature, chitin is always associated with proteins among which chitin-binding proteins (CBPs) are the most important for forming, maintaining and regulating the functions of these extracellular structures. In this study, a genome-wide search for genes encoding proteins with ChtBD2-type (peritrophin A-type) chitin-binding domains (CBDs) was conducted. A total of 53 genes encoding 56 CBPs were identified, including 15 CPAP1s (cuticular proteins analogous to peritrophins with 1 CBD), 11 CPAP3s (CPAPs with 3 CBDs) and 17 PMPs (PM proteins) with a variable number of CBDs, which are structural components of cuticle or of the PM. CBDs were also identified in enzymes of chitin metabolism including 6 chitinases and 7 chitin deacetylases encoded by 6 and 5 genes, respectively. RNA-seq analysis confirmed that PMP and CPAP genes have differential spatial expression patterns. The expression of PMP genes is midgut-specific, while CPAP genes are widely expressed in different cuticle forming tissues. Phylogenetic analysis of CBDs of proteins in insects belonging to different orders revealed that CPAP1s from different species constitute a separate family with 16 different groups, including 6 new groups identified in this study. The CPAP3s are clustered into a separate family of 7 groups present in all insect orders. Altogether, they reveal that duplication events of CBDs in CPAP1s and CPAP3s occurred prior to the evolutionary radiation of insect species. In contrast to the CPAPs, all CBDs from individual PMPs are generally clustered and distinct from other PMPs in the same species in phylogenetic analyses, indicating that the duplication of CBDs in each of these PMPs occurred after divergence of insect species. Phylogenetic analysis of these three CBP families showed that the CBDs in CPAP1s form a clearly separate family, while those found in PMPs and CPAP3s were clustered together in the phylogenetic tree. For chitinases and chitin deacetylases, most of phylogenetic analysis performed with the CBD sequences resulted in similar clustering to the one obtained by using catalytic domain sequences alone, suggesting that CBDs were incorporated into these enzymes and evolved in tandem with the catalytic domains before the diversification of different insect orders. Based on these results, the evolution of CBDs in insect CBPs is discussed to provide a new insight into the CBD sequence structure and diversity, and their evolution and expression in insects. Copyright © 2014 Elsevier Ltd. All rights reserved.

REMOVING COOL CORES AND CENTRAL METALLICITY PEAKS IN GALAXY CLUSTERS WITH POWERFUL ACTIVE GALACTIC NUCLEUS OUTBURSTS

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

Guo Fulai; Mathews, William G., E-mail: fulai@ucolick.or

2010-07-10

Recent X-ray observations of galaxy clusters suggest that cluster populations are bimodally distributed according to central gas entropy and are separated into two distinct classes: cool core (CC) and non-cool core (NCC) clusters. While it is widely accepted that active galactic nucleus (AGN) feedback plays a key role in offsetting radiative losses and maintaining many clusters in the CC state, the origin of NCC clusters is much less clear. At the same time, a handful of extremely powerful AGN outbursts have recently been detected in clusters, with a total energy {approx}10{sup 61}-10{sup 62} erg. Using two-dimensional hydrodynamic simulations, we showmore » that if a large fraction of this energy is deposited near the centers of CC clusters, which is likely common due to dense cores, these AGN outbursts can completely remove CCs, transforming them to NCC clusters. Our model also has interesting implications for cluster abundance profiles, which usually show a central peak in CC systems. Our calculations indicate that during the CC to NCC transformation, AGN outbursts efficiently mix metals in cluster central regions and may even remove central abundance peaks if they are not broad enough. For CC clusters with broad central abundance peaks, AGN outbursts decrease peak abundances, but cannot effectively destroy the peaks. Our model may simultaneously explain the contradictory (possibly bimodal) results of abundance profiles in NCC clusters, some of which are nearly flat, while others have strong central peaks similar to those in CC clusters. A statistical analysis of the sizes of central abundance peaks and their redshift evolution may shed interesting insights on the origin of both types of NCC clusters and the evolution history of thermodynamics and AGN activity in clusters.« less

THE SWIFT AGN AND CLUSTER SURVEY. II. CLUSTER CONFIRMATION WITH SDSS DATA

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

Griffin, Rhiannon D.; Dai, Xinyu; Kochanek, Christopher S.

2016-01-15

We study 203 (of 442) Swift AGN and Cluster Survey extended X-ray sources located in the SDSS DR8 footprint to search for galaxy over-densities in three-dimensional space using SDSS galaxy photometric redshifts and positions near the Swift cluster candidates. We find 104 Swift clusters with a >3σ galaxy over-density. The remaining targets are potentially located at higher redshifts and require deeper optical follow-up observations for confirmation as galaxy clusters. We present a series of cluster properties including the redshift, brightest cluster galaxy (BCG) magnitude, BCG-to-X-ray center offset, optical richness, and X-ray luminosity. We also detect red sequences in ∼85% ofmore » the 104 confirmed clusters. The X-ray luminosity and optical richness for the SDSS confirmed Swift clusters are correlated and follow previously established relations. The distribution of the separations between the X-ray centroids and the most likely BCG is also consistent with expectation. We compare the observed redshift distribution of the sample with a theoretical model, and find that our sample is complete for z ≲ 0.3 and is still 80% complete up to z ≃ 0.4, consistent with the SDSS survey depth. These analysis results suggest that our Swift cluster selection algorithm has yielded a statistically well-defined cluster sample for further study of cluster evolution and cosmology. We also match our SDSS confirmed Swift clusters to existing cluster catalogs, and find 42, 23, and 1 matches in optical, X-ray, and Sunyaev–Zel’dovich catalogs, respectively, and so the majority of these clusters are new detections.« less

Analysis of heterogeneous water vapor uptake by metal iodide cluster ions via differential mobility analysis-mass spectrometry

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

Oberreit, Derek; Fluid Measurement Technologies, Inc., Saint Paul, Minnesota 55110; Rawat, Vivek K.

The sorption of vapor molecules onto pre-existing nanometer sized clusters is of importance in understanding particle formation and growth in gas phase environments and devising gas phase separation schemes. Here, we apply a differential mobility analyzer-mass spectrometer based approach to observe directly the sorption of vapor molecules onto iodide cluster ions of the form (MI){sub x}M{sup +} (x = 1-13, M = Na, K, Rb, or Cs) in air at 300 K and with water saturation ratios in the 0.01-0.64 range. The extent of vapor sorption is quantified in measurements by the shift in collision cross section (CCS) for eachmore » ion. We find that CCS measurements are sensitive enough to detect the transient binding of several vapor molecules to clusters, which shift CCSs by only several percent. At the same time, for the highest saturation ratios examined, we observed CCS shifts of up to 45%. For x < 4, cesium, rubidium, and potassium iodide cluster ions are found to uptake water to a similar extent, while sodium iodide clusters uptake less water. For x ≥ 4, sodium iodide cluster ions uptake proportionally more water vapor than rubidium and potassium iodide cluster ions, while cesium iodide ions exhibit less uptake. Measured CCS shifts are compared to predictions based upon a Kelvin-Thomson-Raoult (KTR) model as well as a Langmuir adsorption model. We find that the Langmuir adsorption model can be fit well to measurements. Meanwhile, KTR predictions deviate from measurements, which suggests that the earliest stages of vapor uptake by nanometer scale species are not well described by the KTR model.« less

HIV Transmission Networks in the San Diego–Tijuana Border Region

PubMed Central

Mehta, Sanjay R.; Wertheim, Joel O.; Brouwer, Kimberly C.; Wagner, Karla D.; Chaillon, Antoine; Strathdee, Steffanie; Patterson, Thomas L.; Rangel, Maria G.; Vargas, Mlenka; Murrell, Ben; Garfein, Richard; Little, Susan J.; Smith, Davey M.

2015-01-01

Background HIV sequence data can be used to reconstruct local transmission networks. Along international borders, like the San Diego–Tijuana region, understanding the dynamics of HIV transmission across reported risks, racial/ethnic groups, and geography can help direct effective prevention efforts on both sides of the border. Methods We gathered sociodemographic, geographic, clinical, and viral sequence data from HIV infected individuals participating in ten studies in the San Diego–Tijuana border region. Phylogenetic and network analysis was performed to infer putative relationships between HIV sequences. Correlates of identified clusters were evaluated and spatiotemporal relationships were explored using Bayesian phylogeographic analysis. Findings After quality filtering, 843 HIV sequences with associated demographic data and 263 background sequences from the region were analyzed, and 138 clusters were inferred (2–23 individuals). Overall, the rate of clustering did not differ by ethnicity, residence, or sex, but bisexuals were less likely to cluster than heterosexuals or men who have sex with men (p = 0.043), and individuals identifying as white (p ≤ 0.01) were more likely to cluster than other races. Clustering individuals were also 3.5 years younger than non-clustering individuals (p < 0.001). Although the sampled San Diego and Tijuana epidemics were phylogenetically compartmentalized, five clusters contained individuals residing on both sides of the border. Interpretation This study sampled ~ 7% of HIV infected individuals in the border region, and although the sampled networks on each side of the border were largely separate, there was evidence of persistent bidirectional cross-border transmissions that linked risk groups, thus highlighting the importance of the border region as a “melting pot” of risk groups. Funding NIH, VA, and Pendleton Foundation. PMID:26629540

HIV Transmission Networks in the San Diego-Tijuana Border Region.

PubMed

Mehta, Sanjay R; Wertheim, Joel O; Brouwer, Kimberly C; Wagner, Karla D; Chaillon, Antoine; Strathdee, Steffanie; Patterson, Thomas L; Rangel, Maria G; Vargas, Mlenka; Murrell, Ben; Garfein, Richard; Little, Susan J; Smith, Davey M

2015-10-01

HIV sequence data can be used to reconstruct local transmission networks. Along international borders, like the San Diego-Tijuana region, understanding the dynamics of HIV transmission across reported risks, racial/ethnic groups, and geography can help direct effective prevention efforts on both sides of the border. We gathered sociodemographic, geographic, clinical, and viral sequence data from HIV infected individuals participating in ten studies in the San Diego-Tijuana border region. Phylogenetic and network analysis was performed to infer putative relationships between HIV sequences. Correlates of identified clusters were evaluated and spatiotemporal relationships were explored using Bayesian phylogeographic analysis. After quality filtering, 843 HIV sequences with associated demographic data and 263 background sequences from the region were analyzed, and 138 clusters were inferred (2-23 individuals). Overall, the rate of clustering did not differ by ethnicity, residence, or sex, but bisexuals were less likely to cluster than heterosexuals or men who have sex with men (p = 0.043), and individuals identifying as white (p ≤ 0.01) were more likely to cluster than other races. Clustering individuals were also 3.5 years younger than non-clustering individuals (p < 0.001). Although the sampled San Diego and Tijuana epidemics were phylogenetically compartmentalized, five clusters contained individuals residing on both sides of the border. This study sampled ~ 7% of HIV infected individuals in the border region, and although the sampled networks on each side of the border were largely separate, there was evidence of persistent bidirectional cross-border transmissions that linked risk groups, thus highlighting the importance of the border region as a "melting pot" of risk groups. NIH, VA, and Pendleton Foundation.

Cardiometabolic risk clustering in spinal cord injury: results of exploratory factor analysis.

PubMed

Libin, Alexander; Tinsley, Emily A; Nash, Mark S; Mendez, Armando J; Burns, Patricia; Elrod, Matt; Hamm, Larry F; Groah, Suzanne L

2013-01-01

Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. One hundred twenty-one subjects (mean 37 ± 12 years; range, 18-73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3-factor model in persons with paraplegia (65.4% variance) and a 4-factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism.

HPLC-DAD-ESI-MS Analysis of Flavonoids from Leaves of Different Cultivars of Sweet Osmanthus.

PubMed

Wang, Yiguang; Fu, Jianxin; Zhang, Chao; Zhao, Hongbo

2016-09-14

Osmanthus fragrans Lour. has traditionally been a popular ornamental plant in China. In this study, ethanol extracts of the leaves of four cultivar groups of O. fragrans were analyzed by high-performance liquid chromatography coupled with diode array detection (HPLC-DAD) and high-performance liquid chromatography with electrospray ionization and mass spectrometry (HPLC-ESI-MS). The results suggest that variation in flavonoids among O. fragrans cultivars is quantitative, rather than qualitative. Fifteen components were detected and separated, among which, the structures of 11 flavonoids and two coumarins were identified or tentatively identified. According to principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on the abundance of these components (expressed as rutin equivalents), 22 selected cultivars were classified into four clusters. The seven cultivars from Cluster III ('Xiaoye Sugui', 'Boye Jingui', 'Wuyi Dangui', 'Yingye Dangui', 'Danzhuang', 'Foding Zhu', and 'Tianxiang Taige'), which are enriched in rutin and total flavonoids, and 'Sijigui' from Cluster II which contained the highest amounts of kaempferol glycosides and apigenin 7-O-glucoside, could be selected as potential pharmaceutical resources. However, the chemotaxonomy in this paper does not correlate with the distribution of the existing cultivar groups, demonstrating that the distribution of flavonoids in O. fragrans leaves does not provide an effective means of classification for O. fragrans cultivars based on flower color.

Metabolic Analysis of Various Date Palm Fruit (Phoenix dactylifera L.) Cultivars from Saudi Arabia to Assess Their Nutritional Quality.

PubMed

Hamad, Ismail; AbdElgawad, Hamada; Al Jaouni, Soad; Zinta, Gaurav; Asard, Han; Hassan, Sherif; Hegab, Momtaz; Hagagy, Nashwa; Selim, Samy

2015-07-27

Date palm is an important crop, especially in the hot-arid regions of the world. Date palm fruits have high nutritional and therapeutic value and possess significant antibacterial and antifungal properties. In this study, we performed bioactivity analyses and metabolic profiling of date fruits of 12 cultivars from Saudi Arabia to assess their nutritional value. Our results showed that the date extracts from different cultivars have different free radical scavenging and anti-lipid peroxidation activities. Moreover, the cultivars showed significant differences in their chemical composition, e.g., the phenolic content (10.4-22.1 mg/100 g DW), amino acids (37-108 μmol·g-1 FW) and minerals (237-969 mg/100 g DW). Principal component analysis (PCA) showed a clear separation of the cultivars into four different groups. The first group consisted of the Sokary, Nabtit Ali cultivars, the second group of Khlas Al Kharj, Khla Al Qassim, Mabroom, Khlas Al Ahsa, the third group of Khals Elshiokh, Nabot Saif, Khodry, and the fourth group consisted of Ajwa Al Madinah, Saffawy, Rashodia, cultivars. Hierarchical cluster analysis (HCA) revealed clustering of date cultivars into two groups. The first cluster consisted of the Sokary, Rashodia and Nabtit Ali cultivars, and the second cluster contained all the other tested cultivars. These results indicate that date fruits have high nutritive value, and different cultivars have different chemical composition.

Ion Mobility Mass Spectrometry Analysis of Isomeric Disaccharide Precursor, Product and Cluster Ions

PubMed Central

Li, Hongli; Bendiak, Brad; Siems, William F.; Gang, David R.; Hill, Herbert H.

2015-01-01

RATIONALE Carbohydrates are highly variable in structure owing to differences in their anomeric configurations, monomer stereochemistry, inter-residue linkage positions and general branching features. The separation of carbohydrate isomers poses a great challenge for current analytical techniques. METHODS The isomeric heterogeneity of disaccharide ions and monosaccharideglycolaldehyde product ions evaluated using electrospray traveling wave ion mobility mass spectrometry (Synapt G2 high definition mass spectrometer) in both positive and negative ion modes investigation. RESULTS The separation of isomeric disaccharide ions was observed but not fully achieved based on their mobility profiles. The mobilities of isomeric product ions, the monosaccharide-glycolaldehydes, derived from different disaccharide isomers were measured. Multiple mobility peaks were observed for both monosaccharide-glycolaldehyde cations and anions, indicating that there was more than one structural configuration in the gas phase as verified by NMR in solution. More importantly, the mobility patterns for isomeric monosaccharide-glycolaldehyde product ions were different, which enabled partial characterization of their respective disaccharide ions. Abundant disaccharide cluster ions were also observed. The Results showed that a majority of isomeric cluster ions had different drift times and, moreover, more than one mobility peak was detected for a number of specific cluster ions. CONCLUSIONS It is demonstrated that ion mobility mass spectrometry is an advantageous method to assess the isomeric heterogeneity of carbohydrate compounds. It is capable of differentiating different types of carbohydrate ions having identical m/z values as well as multiple structural configurations of single compounds. PMID:24591031

Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics.

PubMed

Song, Yuqiao; Liao, Jie; Dong, Junxing; Chen, Li

2015-09-01

The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M-H](-) . Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time-consuming methods for grape seed fingerprinting. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

The application of automatic recognition techniques in the Apollo 9 SO-65 experiment

NASA Technical Reports Server (NTRS)

Macdonald, R. B.

1970-01-01

A synoptic feature analysis is reported on Apollo 9 remote earth surface photographs that uses the methods of statistical pattern recognition to classify density points and clusterings in digital conversion of optical data. A computer derived geological map of a geological test site indicates that geological features of the range are separable, but that specific rock types are not identifiable.

Complete Genome Sequence of an Avian Paramyxovirus Type 4 from North America Reveals a Shorter Genome and New Genotype

PubMed Central

Parthiban, Manoharan; Kaliyaperumal, Manimaran; Xiao, Sa; Nayak, Baibaswata; Paldurai, Anandan; Kim, Shin-Hee; Ladman, Brian S.; Preskenis, Lauren A.; Gelb, Jack; Collins, Peter L.

2013-01-01

An avian paramyxovirus type 4 (APMV-4) was isolated from a duck in Delaware in 2010. Its genome is 15,048 nucleotides (nt) long, which is shorter by 6 nt than those for all previously reported strains. Phylogenetic analysis revealed that this strain formed a separate cluster within APMV-4 strains. PMID:23405329

Genetic differentiation and geographical Relationship of Asian barley landraces using SSRs

PubMed Central

Naeem, Rehan; Dahleen, Lynn; Mirza, Bushra

2011-01-01

Genetic diversity in 403 morphologically distinct landraces of barley (Hordeum vulgare L. subsp. vulgare) originating from seven geographical zones of Asia was studied using simple sequence repeat (SSR) markers from regions of medium to high recombination in the barley genome. The seven polymorphic SSR markers representing each of the chromosomes chosen for the study revealed a high level of allelic diversity among the landraces. Genetic richness was highest in those from India, followed by Pakistan while it was lowest for Uzbekistan and Turkmenistan. Out of the 50 alleles detected, 15 were unique to a geographic region. Genetic diversity was highest for landraces from Pakistan (0.70 ± 0.06) and lowest for those from Uzbekistan (0.18 ± 0.17). Likewise, polymorphic information content (PIC) was highest for Pakistan (0.67 ± 0.06) and lowest for Uzbekistan (0.15 ± 0.17). Diversity among groups was 40% compared to 60% within groups. Principal component analysis clustered the barley landraces into three groups to predict their domestication patterns. In total 51.58% of the variation was explained by the first two principal components of the barley germplasm. Pakistan landraces were clustered separately from those of India, Iran, Nepal and Iraq, whereas those from Turkmenistan and Uzbekistan were clustered together into a separate group. PMID:21734828

Analysis of EEG-fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection.

PubMed

Liston, Adam D; De Munck, Jan C; Hamandi, Khalid; Laufs, Helmut; Ossenblok, Pauly; Duncan, John S; Lemieux, Louis

2006-07-01

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

Functional analysis and classification of phytoplankton based on data from an automated flow cytometer.

PubMed

Malkassian, Anthony; Nerini, David; van Dijk, Mark A; Thyssen, Melilotus; Mante, Claude; Gregori, Gerald

2011-04-01

Analytical flow cytometry (FCM) is well suited for the analysis of phytoplankton communities in fresh and sea waters. The measurement of light scatter and autofluorescence properties of particles by FCM provides optical fingerprints, which enables different phytoplankton groups to be separated. A submersible version of the CytoSense flow cytometer (the CytoSub) has been designed for in situ autonomous sampling and analysis, making it possible to monitor phytoplankton at a short temporal scale and obtain accurate information about its dynamics. For data analysis, a manual clustering is usually performed a posteriori: data are displayed on histograms and scatterplots, and group discrimination is made by drawing and combining regions (gating). The purpose of this study is to provide greater objectivity in the data analysis by applying a nonmanual and consistent method to automatically discriminate clusters of particles. In other words, we seek for partitioning methods based on the optical fingerprints of each particle. As the CytoSense is able to record the full pulse shape for each variable, it quickly generates a large and complex dataset to analyze. The shape, length, and area of each curve were chosen as descriptors for the analysis. To test the developed method, numerical experiments were performed on simulated curves. Then, the method was applied and validated on phytoplankton cultures data. Promising results have been obtained with a mixture of various species whose optical fingerprints overlapped considerably and could not be accurately separated using manual gating. Copyright © 2011 International Society for Advancement of Cytometry.

Identification and DUS Testing of Rice Varieties through Microsatellite Markers

PubMed Central

Pourabed, Ehsan; Jazayeri Noushabadi, Mohammad Reza; Jamali, Seyed Hossein; Moheb Alipour, Naser; Zareyan, Abbas; Sadeghi, Leila

2015-01-01

Identification and registration of new rice varieties are very important to be free from environmental effects and using molecular markers that are more reliable. The objectives of this study were, first, the identification and distinction of 40 rice varieties consisting of local varieties of Iran, improved varieties, and IRRI varieties using PIC, and discriminating power, second, cluster analysis based on Dice similarity coefficient and UPGMA algorithm, and, third, determining the ability of microsatellite markers to separate varieties utilizing the best combination of markers. For this research, 12 microsatellite markers were used. In total, 83 polymorphic alleles (6.91 alleles per locus) were found. In addition, the variation of PIC was calculated from 0.52 to 0.9. The results of cluster analysis showed the complete discrimination of varieties from each other except for IR58025A and IR58025B. Moreover, cluster analysis could detect the most of the improved varieties from local varieties. Based on the best combination of markers analysis, five pair primers together have shown the same results of all markers for detection among all varieties. Considering the results of this research, we can propose that microsatellite markers can be used as a complementary tool for morphological characteristics in DUS tests. PMID:25755666

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.

Clonal structure in Ichthyobacterium seriolicida, the causative agent of bacterial haemolytic jaundice in yellowtail, Seriola quinqueradiata, inferred from molecular epidemiological analysis.

PubMed

Matsuyama, T; Fukuda, Y; Sakai, T; Tanimoto, N; Nakanishi, M; Nakamura, Y; Takano, T; Nakayasu, C

2017-08-01

Bacterial haemolytic jaundice caused by Ichthyobacterium seriolicida has been responsible for mortality in farmed yellowtail, Seriola quinqueradiata, in western Japan since the 1980s. In this study, polymorphic analysis of I. seriolicida was performed using three molecular methods: amplified fragment length polymorphism (AFLP) analysis, multilocus sequence typing (MLST) and multiple-locus variable-number tandem repeat analysis (MLVA). Twenty-eight isolates were analysed using AFLP, while 31 isolates were examined by MLST and MLVA. No polymorphisms were identified by AFLP analysis using EcoRI and MseI, or by MLST of internal fragments of eight housekeeping genes. However, MLVA revealed variation in repeat numbers of three elements, allowing separation of the isolates into 16 sequence types. The unweighted pair group method using arithmetic averages cluster analysis of the MLVA data identified four major clusters, and all isolates belonged to clonal complexes. It is likely that I. seriolicida populations share a common ancestor, which may be a recently introduced strain. © 2016 John Wiley & Sons Ltd.

The sparkling Universe: clustering of voids and void clumps

NASA Astrophysics Data System (ADS)

Lares, Marcelo; Ruiz, Andrés N.; Luparello, Heliana E.; Ceccarelli, Laura; Garcia Lambas, Diego; Paz, Dante J.

2017-07-01

We analyse the clustering of cosmic voids using a numerical simulation and the main galaxy sample from the Sloan Digital Sky Survey. We take into account the classification of voids into two types that resemble different evolutionary modes: those with a rising integrated density profile (void-in-void mode or R-type) and voids with shells (void-in-cloud mode or S-type). The results show that voids of the same type have stronger clustering than the full sample. We use the correlation analysis to define void clumps, associations with at least two voids separated by a distance of at most the mean void separation. In order to study the spatial configuration of void clumps, we compute the minimal spanning tree and analyse their multiplicity, maximum length and elongation parameter. We further study the dynamics of the smaller sphere that enclose all the voids in each clump. Although the global densities of void clumps are different according to their member-void types, the bulk motions of these spheres are remarkably lower than those of randomly placed spheres with the same radius distribution. In addition, the coherence of pairwise void motions does not strongly depend on whether voids belong to the same clump. Void clumps are useful to analyse the large-scale flows around voids, since voids embedded in large underdense regions are mostly in the void-in-void regime, where the expansion of the larger region produces the separation of voids. Similarly, voids around overdense regions form clumps that are in collapse, as reflected in the relative velocities of voids that are mostly approaching.

A High Angular Resolution Multiplicity Survey of the Open Clusters α Persei and Praesepe

NASA Astrophysics Data System (ADS)

Patience, J.; Ghez, A. M.; Reid, I. N.; Matthews, K.

2002-03-01

Two hundred forty-two members of the Praesepe and α Persei clusters have been surveyed with high angular resolution 2.2 μm speckle imaging on the 3 m Infrared Telescope Facility, the 5 m Hale, and the 10 m Keck telescopes, along with direct imaging using the near-infrared camera (NICMOS) aboard the Hubble Space Telescope. The observed stars range in spectral type from B (~5 Msolar) to early M (~0.5 Msolar), with the majority of the targets more massive than ~0.8 Msolar. The one quadruple and 39 binary systems detected encompass separations from 0.053" to 7.28" 28 of the systems are new detections, and there are nine candidate substellar companions. The results of the survey are used to test binary star formation and evolution scenarios and to investigate the effects of companion stars on X-ray emission and stellar rotation. The main results are as follows:1. Over the projected separation range of 26 to 581 AU and magnitude differences of ΔK<4.0 (comparable to mass ratios q=Msec/Mprim>0.25), the companion-star fraction (CSF) for α Per is 0.09+/-0.03, and that for Praesepe is 0.10+/-0.03. This fraction is consistent with the field G dwarf value, implying that there is not a systematic decline in multiplicity with age at these separations on timescales of a few times 107 yr. The combination of previous spectroscopic work and the current cluster survey results in a cluster binary separation distribution that peaks at 4+1-1.5 AU, a significantly smaller value than the peaks of both the field G dwarf and the nearby T Tauri distributions. If the field G dwarf distribution represents a superposition of distributions from the populations that contributed to the field, then the data imply that ~30% of field binaries formed in dark clouds like the nearby T Tauri stars and the remaining ~70% formed in denser regions.2. An exploration of the binary star properties reveals a cluster CSF that increases with decreasing target mass, and a cluster mass ratio distribution that rises more sharply for higher mass stars but is independent of binary separation. These observational trends are consistent with several models of capture in small clusters and simulations of accretion following fragmentation in a cluster environment. Other types of capture and fragmentation are either inconsistent with these data or currently lack testable predictions.3. Among the cluster A stars, there is a higher fraction of binaries in the subset with X-ray detections, consistent with the hypothesis that lower mass companions are the true source of X-ray emission.4. Finally, in the younger cluster α Per, the rotational velocities for solar-type binaries with separations less than 60 AU are significantly higher than those of wider systems. This suggests that companions may critically affect the rotational evolution of young stars.

Prevalence of Nitrosomonas cluster 7 populations in the ammonia-oxidizing community of a submerged membrane bioreactor treating urban wastewater under different operation conditions.

PubMed

Cerrone, F; Poyatos, J M; Molina-Muñoz, M; Cortés-Lorenzo, C; González-López, J; Rodelas, B

2013-07-01

A pilot-scale ultrafiltration membrane bioreactor (MBR) was used for the aerobic treatment of urban wastewater in four experimental stages influenced by seasonal temperature and different sets of operation conditions. The structure of the ammonia-oxidizing bacteria (AOB) community was profiled by temperature gradient gel electrophoresis (TGGE), based on the amplification and separation of partial ammonia-monoxygenase subunit A (amoA) genes. Canonical correspondence analysis revealed that temperature, hydraulic retention time and percentage of ammonia removal had a significant effect on the fingerprints of AOB communities. Phylogenetic analysis conducted on amoA/AmoA sequences of reamplified TGGE bands showed, however, that closely related ammonia-oxidizing populations inhabited the sludge of the MBR in all experimental stages. Nitrosomonas cluster 7 populations (N. europaea-N. eutropha cluster) prevailed under all conditions tested, even when the MBR was operated under complete biomass retention or at low temperatures, suggesting that the high ammonia concentrations in the system were determinant to select r-strategist AOB.

Structural parameters of young star clusters: fractal analysis

NASA Astrophysics Data System (ADS)

Hetem, A.

2017-07-01

A unified view of star formation in the Universe demand detailed and in-depth studies of young star clusters. This work is related to our previous study of fractal statistics estimated for a sample of young stellar clusters (Gregorio-Hetem et al. 2015, MNRAS 448, 2504). The structural properties can lead to significant conclusions about the early stages of cluster formation: 1) virial conditions can be used to distinguish warm collapsed; 2) bound or unbound behaviour can lead to conclusions about expansion; and 3) fractal statistics are correlated to the dynamical evolution and age. The technique of error bars estimation most used in the literature is to adopt inferential methods (like bootstrap) to estimate deviation and variance, which are valid only for an artificially generated cluster. In this paper, we expanded the number of studied clusters, in order to enhance the investigation of the cluster properties and dynamic evolution. The structural parameters were compared with fractal statistics and reveal that the clusters radial density profile show a tendency of the mean separation of the stars increase with the average surface density. The sample can be divided into two groups showing different dynamic behaviour, but they have the same dynamic evolution, since the entire sample was revealed as being expanding objects, for which the substructures do not seem to have been completely erased. These results are in agreement with the simulations adopting low surface densities and supervirial conditions.

Detecting hybridization between Iranian wild wolf (Canis lupus pallipes) and free-ranging domestic dog (Canis familiaris) by analysis of microsatellite markers.

PubMed

Khosravi, Rasoul; Rezaei, Hamid Reza; Kaboli, Mohammad

2013-01-01

The genetic threat due to hybridization with free-ranging dogs is one major concern in wolf conservation. The identification of hybrids and extent of hybridization is important in the conservation and management of wolf populations. Genetic variation was analyzed at 15 unlinked loci in 28 dogs, 28 wolves, four known hybrids, two black wolves, and one dog with abnormal traits in Iran. Pritchard's model, multivariate ordination by principal component analysis and neighbor joining clustering were used for population clustering and individual assignment. Analysis of genetic variation showed that genetic variability is high in both wolf and dog populations in Iran. Values of H(E) in dog and wolf samples ranged from 0.75-0.92 and 0.77-0.92, respectively. The results of AMOVA showed that the two groups of dog and wolf were significantly different (F(ST) = 0.05 and R(ST) = 0.36; P < 0.001). In each of the three methods, wolf and dog samples were separated into two distinct clusters. Two dark wolves were assigned to the wolf cluster. Also these models detected D32 (dog with abnormal traits) and some other samples, which were assigned to more than one cluster and could be a hybrid. This study is the beginning of a genetic study in wolf populations in Iran, and our results reveal that as in other countries, hybridization between wolves and dogs is sporadic in Iran and can be a threat to wolf populations if human perturbations increase.

Distinguishing Fear Versus Distress Symptomatology in Pediatric OCD.

PubMed

Rozenman, Michelle; Peris, Tara; Bergman, R Lindsey; Chang, Susanna; O'Neill, Joseph; McCracken, James T; Piacentini, John

2017-02-01

Prior research has identified OCD subtypes or "clusters" of symptoms that differentially relate to clinical features of the disorder. Given the high comorbidity between OCD and anxiety, OCD symptom clusters may more broadly associate with fear and/or distress internalizing constructs. This study examines fear and distress dimensions, including physical concerns (fear), separation anxiety (fear), perfectionism (distress), and anxious coping (distress), as predictors of previously empirically-derived OCD symptom clusters in a sample of 215 youth diagnosed with primary OCD (ages 7-17, mean age = 12.25). Self-reported separation fears predicted membership in Cluster 1 (aggressive, sexual, religious, somatic obsessions, and checking compulsions) while somatic/autonomic fears predicted membership in Cluster 2 (symmetry obsessions and ordering, counting, repeating compulsions). Results highlight the diversity of pediatric OCD symptoms and their differential association with fear, suggesting the need to carefully assess both OCD and global fear constructs that might be directly targeted in treatment.

[Application of Kohonen Self-Organizing Feature Maps in QSAR of human ADMET and kinase data sets].

PubMed

Hegymegi-Barakonyi, Bálint; Orfi, László; Kéri, György; Kövesdi, István

2013-01-01

QSAR predictions have been proven very useful in a large number of studies for drug design, such as kinase inhibitor design as targets for cancer therapy, however the overall predictability often remains unsatisfactory. To improve predictability of ADMET features and kinase inhibitory data, we present a new method using Kohonen's Self-Organizing Feature Map (SOFM) to cluster molecules based on explanatory variables (X) and separate dissimilar ones. We calculated SOFM clusters for a large number of molecules with human ADMET and kinase inhibitory data, and we showed that chemically similar molecules were in the same SOFM cluster, and within such clusters the QSAR models had significantly better predictability. We used also target variables (Y, e.g. ADMET) jointly with X variables to create a novel type of clustering. With our method, cells of loosely coupled XY data could be identified and separated into different model building sets.

Spectrum-Effect Relationships Between Chemical Fingerprints and Antibacterial Effects of Lonicerae Japonicae Flos and Lonicerae Flos Base on UPLC and Microcalorimetry

PubMed Central

Shi, Zhilong; Liu, Zhenjie; Liu, Chunsheng; Wu, Mingquan; Su, Haibin; Ma, Xiao; Zang, Yimei; Wang, Jiabo; Zhao, Yanling; Xiao, Xiaohe

2016-01-01

The traditional Chinese medicines Lonicerae Japonicae Flos (LJF, Jinyinhua in Chinese) and Lonicerae Flos (LF, Shanyinhua in Chinese) refer to the flower buds of five plants belonging to the Caprifoliaceae family. Until 2000, all of these were officially listed as a single item, LJF (Jinyinhua), in the Chinese Pharmacopoeia. However, there have recently been many academic controversies concerning the separation and combination of LJF and LF in administrative regulation. Till now there has been little work completed evaluating the relationships between biological activity and chemical properties among these drugs. Microcalorimetry and UPLC were used along with principal component analysis (PCA), hierarchical cluster analysis (HCA), and canonical correlation analysis (CCA) to investigate the relationships between the chemical ingredients and the antibacterial effects of LJF and LF. Using multivariate statistical analysis, LJF and LF could be initially separated according to their chemical fingerprints, and the antibacterial effects of the two herbal drugs were divided into two clusters. This result supports the disaggregation of LJF and LF by the Pharmacopoeia Committee. However, the sample of Lonicera fulvotomentosa Hsu et S. C. Cheng turned out to be an intermediate species, with similar antibacterial efficacy as LJF. The results of CCA indicated that chlorogenic acid and 3,4-Dicaffeoylquinic acid were the major components generating antibacterial effects. Furthermore, 3,4-Dicaffeoylquinic acid could be used as a new marker ingredient for quality control of LJF and LF. PMID:26869929

Method for evaluating wind turbine wake effects on wind farm performance

NASA Technical Reports Server (NTRS)

Neustadter, H. E.; Spera, D. A.

1985-01-01

A method of testing the performance of a cluster of wind turbine units an data analysis equations are presented which together form a simple and direct procedure for determining the reduction in energy output caused by the wake of an upwind turbine. This method appears to solve the problems presented by data scatter and wind variability. Test data from the three-unit Mod-2 wind turbine cluster at Goldendale, Washington, are analyzed to illustrate the application of the proposed method. In this sample case the reduction in energy was found to be about 10 percent when the Mod-2 units were separated a distance equal to seven diameters and winds were below rated.

Comparative ribotyping of Staphylococcus intermedius isolated from members of the Canoidea gives possible evidence for host-specificity and co-evolution of bacteria and hosts.

PubMed

Aarestrup, F M

2001-07-01

A total of 41 Staphylococcus intermedius isolates were isolated from skin of healthy members of six phylogenetic groups within the Canoidea (the dog family, skunk subfamily, weasel subfamily, racoon family, red panda and bear family) of different geographical origin and compared by EcoRI ribotyping and cluster analysis. The S. intermedius isolates from the different families and subfamilies clustered together in separate groups, almost completely following the phylogenetic relationship of the animal hosts. These ribotype data indicate host-specificity of different types of S. intermedius and suggest co-evolution between the animal hosts within the Canoidea and S. intermedius.

[A method for the analysis of overlapped peaks in the high performance liquid chromatogram based on spectrum analysis].

PubMed

Liu, Bao; Fan, Xiaoming; Huo, Shengnan; Zhou, Lili; Wang, Jun; Zhang, Hui; Hu, Mei; Zhu, Jianhua

2011-12-01

A method was established to analyse the overlapped chromatographic peaks based on the chromatographic-spectra data detected by the diode-array ultraviolet detector. In the method, the three-dimensional data were de-noised and normalized firstly; secondly the differences and clustering analysis of the spectra at different time points were calculated; then the purity of the whole chromatographic peak were analysed and the region were sought out in which the spectra of different time points were stable. The feature spectra were extracted from the spectrum-stable region as the basic foundation. The nonnegative least-square method was chosen to separate the overlapped peaks and get the flow curve which was based on the feature spectrum. The three-dimensional divided chromatographic-spectrum peak could be gained by the matrix operations of the feature spectra with the flow curve. The results displayed that this method could separate the overlapped peaks.

Fingerprinting postblast explosive residues by portable capillary electrophoresis with contactless conductivity detection.

PubMed

Kobrin, Eeva-Gerda; Lees, Heidi; Fomitšenko, Maria; Kubáň, Petr; Kaljurand, Mihkel

2014-04-01

A portable capillary electrophoretic system with contactless conductivity detection was used for fingerprint analysis of postblast explosive residues from commercial organic and improvised inorganic explosives on various surfaces (sand, concrete, metal witness plates). Simple extraction methods were developed for each of the surfaces for subsequent simultaneous capillary electrophoretic analysis of anions and cations. Dual-opposite end injection principle was used for fast (<4 min) separation of 10 common anions and cations from postblast residues using an optimized separation electrolyte composed of 20 mM MES, 20 mM l-histidine, 30 μM CTAB and 2 mM 18-crown-6. The concentrations of all ions obtained from the electropherograms were subjected to principal component analysis to classify the tested explosives on all tested surfaces, resulting in distinct cluster formations that could be used to verify (each) type of the explosive. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multilocus sequence typing and pulsed-field gel electrophoresis analysis of Oenococcus oeni from different wine-producing regions of China.

PubMed

Wang, Tao; Li, Hua; Wang, Hua; Su, Jing

2015-04-16

The present study established a typing method with NotI-based pulsed-field gel electrophoresis (PFGE) and stress response gene schemed multilocus sequence typing (MLST) for 55 Oenococcus oeni strains isolated from six individual regions in China and two model strains PSU-1 (CP000411) and ATCC BAA-1163 (AAUV00000000). Seven stress response genes, cfa, clpL, clpP, ctsR, mleA, mleP and omrA, were selected for MLST testing, and positive selective pressure was detected for these genes. Furthermore, both methods separated the strains into two clusters. The PFGE clusters are correlated with the region, whereas the sequence types (STs) formed by the MLST confirm the two clusters identified by PFGE. In addition, the population structure was a mixture of evolutionary pathways, and the strains exhibited both clonal and panmictic characteristics. Copyright © 2015 Elsevier B.V. All rights reserved.

Correlation of shallow marine, deep marine, and coastal terrestrial records of central California: asynchronous responses to paleoceanographic and paleoclimatic change during the past 19,000 years

NASA Astrophysics Data System (ADS)

McGann, M.

2016-12-01

Benthic and planktic foraminiferal census data combined with pollen data acquired from the continental margin off central California (core S3-15G, 3491 m depth from the western levy of the Monterey Fan; 36°23.53'N, 123°20.52'W) provide a unique opportunity to document concurrent paleoceanographic and paleoclimatic changes in the region during the late Quaternary. Radiocarbon dates and the ratio of the planktic foraminiferal species Neogloboquardrina pachyderma (Ehrenberg) to Neogloboquardrina incompta (Cifelli) provide a good age-depth model for the last 19,000 years. Q-mode cluster analysis of the benthic foraminifera grouped the fauna into two clusters reflecting faunal adaptation to changing climatic conditions during the Pleistocene and Holocene, whereas the R-mode cluster analysis identified glacial (Uvigerina senticosa and Globobulimina auriculata) and interglacial (Melonis pompilioides and Gyroidina planulata) faunas. A slight increase in oxygen concentration in the deep sea across the Pleistocene-Holocene transition is suggested by a reduction in abundance of G. auriculata and increased frequency of M. pompilioides. Q-mode cluster analysis of the planktic foraminifera indicates a change in the surface water from a glacial subpolar fauna in the Pleistocene to a transitional fauna in the Holocene. The pollen flora separated into three clusters by Q-mode cluster analysis, two of Pleistocene age (glacial and transitional) and one in the Holocene (interglacial), reflecting adaptation of the flora in the California Coast Ranges of central California to the warmer climate in the Holocene. Decoupling is evident between the benthic foraminiferal, planktic foraminiferal, and terrestrial floral responses to changing oceanographic and climatic conditions. The floral response leads the surface-dwelling planktic fauna by several millennia, and is followed by the deep-dwelling benthic fauna a millennium later.

Whole-Genome Sequencing Analysis of Salmonella enterica Serovar Enteritidis Isolates in Chile Provides Insights into Possible Transmission between Gulls, Poultry, and Humans.

PubMed

Toro, Magaly; Retamal, Patricio; Ayers, Sherry; Barreto, Marlen; Allard, Marc; Brown, Eric W; Gonzalez-Escalona, Narjol

2016-10-15

Salmonella enterica subsp. enterica serotype Enteritidis is a major cause of human salmonellosis worldwide; however, little is known about the genetic relationships between S Enteritidis clinical strains and S Enteritidis strains from other sources in Chile. We compared the whole genomes of 30 S Enteritidis strains isolated from gulls, domestic chicken eggs, and humans in Chile, to investigate their phylogenetic relationships and to establish their relatedness to international strains. Core genome multilocus sequence typing (cgMLST) analysis showed that only 246/4,065 shared loci differed among these Chilean strains, separating them into two clusters (I and II), with cluster II being further divided into five subclusters. One subcluster (subcluster 2) contained strains from all surveyed sources that differed at 1 to 18 loci (of 4,065 loci) with 1 to 18 single-nucleotide polymorphisms (SNPs), suggesting interspecies transmission of S Enteritidis in Chile. Moreover, clusters were formed by strains that were distant geographically, which could imply that gulls might be spreading the pathogen throughout the country. Our cgMLST analysis, using other S Enteritidis genomes available in the National Center for Biotechnology Information (NCBI) database, showed that S Enteritidis strains from Chile and the United States belonged to different lineages, which suggests that S Enteritidis regional markers might exist and could be used for trace-back investigations. This study highlights the importance of gulls in the spread of Salmonella Enteritidis in Chile. We revealed a close genetic relationship between some human and gull S Enteritidis strains (with as few as 2 of 4,065 genes being different), and we also found that gull strains were present in clusters formed by strains isolated from other sources or distant locations. Together with previously published evidence, this suggests that gulls might be spreading this pathogen between different regions in Chile and that some of those strains have been transmitted to humans. Moreover, we discovered that Chilean S Enteritidis strains clustered separately from most of S Enteritidis strains isolated throughout the world (in the GenBank database) and thus it might be possible to distinguish the geographical origins of strains based on specific genomic features. This could be useful for trace-back investigations of foodborne illnesses throughout the world. Copyright © 2016 Toro et al.

Whole-Genome Sequencing Analysis of Salmonella enterica Serovar Enteritidis Isolates in Chile Provides Insights into Possible Transmission between Gulls, Poultry, and Humans

PubMed Central

Ayers, Sherry; Barreto, Marlen; Allard, Marc; Brown, Eric W.

2016-01-01

ABSTRACT Salmonella enterica subsp. enterica serotype Enteritidis is a major cause of human salmonellosis worldwide; however, little is known about the genetic relationships between S. Enteritidis clinical strains and S. Enteritidis strains from other sources in Chile. We compared the whole genomes of 30 S. Enteritidis strains isolated from gulls, domestic chicken eggs, and humans in Chile, to investigate their phylogenetic relationships and to establish their relatedness to international strains. Core genome multilocus sequence typing (cgMLST) analysis showed that only 246/4,065 shared loci differed among these Chilean strains, separating them into two clusters (I and II), with cluster II being further divided into five subclusters. One subcluster (subcluster 2) contained strains from all surveyed sources that differed at 1 to 18 loci (of 4,065 loci) with 1 to 18 single-nucleotide polymorphisms (SNPs), suggesting interspecies transmission of S. Enteritidis in Chile. Moreover, clusters were formed by strains that were distant geographically, which could imply that gulls might be spreading the pathogen throughout the country. Our cgMLST analysis, using other S. Enteritidis genomes available in the National Center for Biotechnology Information (NCBI) database, showed that S. Enteritidis strains from Chile and the United States belonged to different lineages, which suggests that S. Enteritidis regional markers might exist and could be used for trace-back investigations. IMPORTANCE This study highlights the importance of gulls in the spread of Salmonella Enteritidis in Chile. We revealed a close genetic relationship between some human and gull S. Enteritidis strains (with as few as 2 of 4,065 genes being different), and we also found that gull strains were present in clusters formed by strains isolated from other sources or distant locations. Together with previously published evidence, this suggests that gulls might be spreading this pathogen between different regions in Chile and that some of those strains have been transmitted to humans. Moreover, we discovered that Chilean S. Enteritidis strains clustered separately from most of S. Enteritidis strains isolated throughout the world (in the GenBank database) and thus it might be possible to distinguish the geographical origins of strains based on specific genomic features. This could be useful for trace-back investigations of foodborne illnesses throughout the world. PMID:27520817

Molecular serotyping and antimicrobial resistance profiles of Actinobacillus pleuropneumoniae isolated from pigs in South Korea.

PubMed

Kim, Boram; Hur, Jin; Lee, Ji Yeong; Choi, Yoonyoung; Lee, John Hwa

2016-09-01

Actinobacillus pleuropneumoniae (APP) causes porcine pleuropneumonia (PP). Serotypes and antimicrobial resistance patterns in APP isolates from pigs in Korea were examined. Sixty-five APP isolates were genetically serotyped using standard and multiplex PCR (polymerase chain reaction). Antimicrobial susceptibilities were tested using the standardized disk-agar method. PCR was used to detect β-lactam, gentamicin and tetracycline-resistance genes. The random amplified polymorphic DNA (RAPD) patterns were determined by PCR. Korean pigs predominantly carried APP serotypes 1 and 5. Among 65 isolates, one isolate was sensitive to all 12 antimicrobials tested in this study. Sixty-two isolates was resistant to tetracycline and 53 isolates carried one or five genes including tet(B), tet(A), tet(H), tet(M)/tet(O), tet(C), tet(G) and/or tet(L)-1 markers. Among 64 strains, 9% and 26.6% were resistance to 10 and three or more antimicrobials, respectively. Thirteen different antimicrobial resistance patterns were observed and RAPD analysis revealed a separation of the isolates into two clusters: cluster II (6 strains resistant to 10 antimicrobials) and cluster I (the other 59 strains). Results show that APP serotypes 1 and 5 are the most common in Korea, and multi-drug resistant strains are prevalent. RAPD analysis demonstrated that six isolates resistant to 10 antimicrobials belonged to the same cluster.

Progressive myoclonic epilepsies

PubMed Central

Michelucci, Roberto; Canafoglia, Laura; Striano, Pasquale; Gambardella, Antonio; Magaudda, Adriana; Tinuper, Paolo; La Neve, Angela; Ferlazzo, Edoardo; Gobbi, Giuseppe; Giallonardo, Anna Teresa; Capovilla, Giuseppe; Visani, Elisa; Panzica, Ferruccio; Avanzini, Giuliano; Tassinari, Carlo Alberto; Bianchi, Amedeo; Zara, Federico

2014-01-01

Objective: To define the clinical spectrum and etiology of progressive myoclonic epilepsies (PMEs) in Italy using a database developed by the Genetics Commission of the Italian League against Epilepsy. Methods: We collected clinical and laboratory data from patients referred to 25 Italian epilepsy centers regardless of whether a positive causative factor was identified. PMEs of undetermined origins were grouped using 2-step cluster analysis. Results: We collected clinical data from 204 patients, including 77 with a diagnosis of Unverricht-Lundborg disease and 37 with a diagnosis of Lafora body disease; 31 patients had PMEs due to rarer genetic causes, mainly neuronal ceroid lipofuscinoses. Two more patients had celiac disease. Despite extensive investigation, we found no definitive etiology for 57 patients. Cluster analysis indicated that these patients could be grouped into 2 clusters defined by age at disease onset, age at myoclonus onset, previous psychomotor delay, seizure characteristics, photosensitivity, associated signs other than those included in the cardinal definition of PME, and pathologic MRI findings. Conclusions: Information concerning the distribution of different genetic causes of PMEs may provide a framework for an updated diagnostic workup. Phenotypes of the patients with PME of undetermined cause varied widely. The presence of separate clusters suggests that novel forms of PME are yet to be clinically and genetically characterized. PMID:24384641

Progressive myoclonic epilepsies: definitive and still undetermined causes.

PubMed

Franceschetti, Silvana; Michelucci, Roberto; Canafoglia, Laura; Striano, Pasquale; Gambardella, Antonio; Magaudda, Adriana; Tinuper, Paolo; La Neve, Angela; Ferlazzo, Edoardo; Gobbi, Giuseppe; Giallonardo, Anna Teresa; Capovilla, Giuseppe; Visani, Elisa; Panzica, Ferruccio; Avanzini, Giuliano; Tassinari, Carlo Alberto; Bianchi, Amedeo; Zara, Federico

2014-02-04

To define the clinical spectrum and etiology of progressive myoclonic epilepsies (PMEs) in Italy using a database developed by the Genetics Commission of the Italian League against Epilepsy. We collected clinical and laboratory data from patients referred to 25 Italian epilepsy centers regardless of whether a positive causative factor was identified. PMEs of undetermined origins were grouped using 2-step cluster analysis. We collected clinical data from 204 patients, including 77 with a diagnosis of Unverricht-Lundborg disease and 37 with a diagnosis of Lafora body disease; 31 patients had PMEs due to rarer genetic causes, mainly neuronal ceroid lipofuscinoses. Two more patients had celiac disease. Despite extensive investigation, we found no definitive etiology for 57 patients. Cluster analysis indicated that these patients could be grouped into 2 clusters defined by age at disease onset, age at myoclonus onset, previous psychomotor delay, seizure characteristics, photosensitivity, associated signs other than those included in the cardinal definition of PME, and pathologic MRI findings. Information concerning the distribution of different genetic causes of PMEs may provide a framework for an updated diagnostic workup. Phenotypes of the patients with PME of undetermined cause varied widely. The presence of separate clusters suggests that novel forms of PME are yet to be clinically and genetically characterized.

Robust MST-Based Clustering Algorithm.

PubMed

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

Limitations of cytochrome oxidase I for the barcoding of Neritidae (Mollusca: Gastropoda) as revealed by Bayesian analysis.

PubMed

Chee, S Y

2015-05-25

The mitochondrial DNA (mtDNA) cytochrome oxidase I (COI) gene has been universally and successfully utilized as a barcoding gene, mainly because it can be amplified easily, applied across a wide range of taxa, and results can be obtained cheaply and quickly. However, in rare cases, the gene can fail to distinguish between species, particularly when exposed to highly sensitive methods of data analysis, such as the Bayesian method, or when taxa have undergone introgressive hybridization, over-splitting, or incomplete lineage sorting. Such cases require the use of alternative markers, and nuclear DNA markers are commonly used. In this study, a dendrogram produced by Bayesian analysis of an mtDNA COI dataset was compared with that of a nuclear DNA ATPS-α dataset, in order to evaluate the efficiency of COI in barcoding Malaysian nerites (Neritidae). In the COI dendrogram, most of the species were in individual clusters, except for two species: Nerita chamaeleon and N. histrio. These two species were placed in the same subcluster, whereas in the ATPS-α dendrogram they were in their own subclusters. Analysis of the ATPS-α gene also placed the two genera of nerites (Nerita and Neritina) in separate clusters, whereas COI gene analysis placed both genera in the same cluster. Therefore, in the case of the Neritidae, the ATPS-α gene is a better barcoding gene than the COI gene.

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Application of Artificial Intelligence For Euler Solutions Clustering

NASA Astrophysics Data System (ADS)

Mikhailov, V.; Galdeano, A.; Diament, M.; Gvishiani, A.; Agayan, S.; Bogoutdinov, Sh.; Graeva, E.; Sailhac, P.

Results of Euler deconvolution strongly depend on the selection of viable solutions. Synthetic calculations using multiple causative sources show that Euler solutions clus- ter in the vicinity of causative bodies even when they do not group densely about perimeter of the bodies. We have developed a clustering technique to serve as a tool for selecting appropriate solutions. The method RODIN, employed in this study, is based on artificial intelligence and was originally designed for problems of classification of large data sets. It is based on a geometrical approach to study object concentration in a finite metric space of any dimension. The method uses a formal definition of cluster and includes free parameters that facilitate the search for clusters of given proper- ties. Test on synthetic and real data showed that the clustering technique successfully outlines causative bodies more accurate than other methods of discriminating Euler solutions. In complicated field cases such as the magnetic field in the Gulf of Saint Malo region (Brittany, France), the method provides geologically insightful solutions. Other advantages of the clustering method application are: - Clusters provide solutions associated with particular bodies or parts of bodies permitting the analysis of different clusters of Euler solutions separately. This may allow computation of average param- eters for individual causative bodies. - Those measurements of the anomalous field that yield clusters also form dense clusters themselves. The application of cluster- ing technique thus outlines areas where the influence of different causative sources is more prominent. This allows one to focus on areas for reinterpretation, using different window sizes, structural indices and so on.

Efficient evaluation of sampling quality of molecular dynamics simulations by clustering of dihedral torsion angles and Sammon mapping.

PubMed

Frickenhaus, Stephan; Kannan, Srinivasaraghavan; Zacharias, Martin

2009-02-01

A direct conformational clustering and mapping approach for peptide conformations based on backbone dihedral angles has been developed and applied to compare conformational sampling of Met-enkephalin using two molecular dynamics (MD) methods. Efficient clustering in dihedrals has been achieved by evaluating all combinations resulting from independent clustering of each dihedral angle distribution, thus resolving all conformational substates. In contrast, Cartesian clustering was unable to accurately distinguish between all substates. Projection of clusters on dihedral principal component (PCA) subspaces did not result in efficient separation of highly populated clusters. However, representation in a nonlinear metric by Sammon mapping was able to separate well the 48 highest populated clusters in just two dimensions. In addition, this approach also allowed us to visualize the transition frequencies between clusters efficiently. Significantly, higher transition frequencies between more distinct conformational substates were found for a recently developed biasing-potential replica exchange MD simulation method allowing faster sampling of possible substates compared to conventional MD simulations. Although the number of theoretically possible clusters grows exponentially with peptide length, in practice, the number of clusters is only limited by the sampling size (typically much smaller), and therefore the method is well suited also for large systems. The approach could be useful to rapidly and accurately evaluate conformational sampling during MD simulations, to compare different sampling strategies and eventually to detect kinetic bottlenecks in folding pathways.

The state of the residential fire fatality problem in Sweden: Epidemiology, risk factors, and event typologies.

PubMed

Jonsson, Anders; Bonander, Carl; Nilson, Finn; Huss, Fredrik

2017-09-01

Residential fires represent the largest category of fatal fires in Sweden. The purpose of this study was to describe the epidemiology of fatal residential fires in Sweden and to identify clusters of events. Data was collected from a database that combines information on fatal fires with data from forensic examinations and the Swedish Cause of Death-register. Mortality rates were calculated for different strata using population statistics and rescue service turnout reports. Cluster analysis was performed using multiple correspondence analysis with agglomerative hierarchical clustering. Male sex, old age, smoking, and alcohol were identified as risk factors, and the most common primary injury diagnosis was exposure to toxic gases. Compared to non-fatal fires, fatal residential fires more often originated in the bedroom, were more often caused by smoking, and were more likely to occur at night. Six clusters were identified. The first two clusters were both smoking-related, but were separated into (1) fatalities that often involved elderly people, usually female, whose clothes were ignited (17% of the sample), (2) middle-aged (45-64years old), (often) intoxicated men, where the fire usually originated in furniture (30%). Other clusters that were identified in the analysis were related to (3) fires caused by technical fault, started in electrical installations in single houses (13%), (4) cooking appliances left on (8%), (5) events with unknown cause, room and object of origin (25%), and (6) deliberately set fires (7%). Fatal residential fires were unevenly distributed in the Swedish population. To further reduce the incidence of fire mortality, specialized prevention efforts that focus on the different needs of each cluster are required. Cooperation between various societal functions, e.g. rescue services, elderly care, psychiatric clinics and other social services, with an application of both human and technological interventions, should reduce residential fire mortality in Sweden. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Clustering of GPS velocities in the Mojave Block, southeastern California

NASA Astrophysics Data System (ADS)

Savage, J. C.; Simpson, R. W.

2013-04-01

find subdivisions within the Mojave Block using cluster analysis to identify groupings in the velocities observed at GPS stations there. The clusters are represented on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. The most significant representation as judged by the gap test involves 4 clusters within the Mojave Block. The fault systems bounding the clusters from east to west are 1) the faults defining the eastern boundary of the Northeast Mojave Domain extended southward to connect to the Hector Mine rupture, 2) the Calico-Paradise fault system, 3) the Landers-Blackwater fault system, and 4) the Helendale-Lockhart fault system. This division of the Mojave Block is very similar to that proposed by Meade and Hager []. However, no cluster boundary coincides with the Garlock Fault, the northern boundary of the Mojave Block. Rather, the clusters appear to continue without interruption from the Mojave Block north into the southern Walker Lane Belt, similar to the continuity across the Garlock Fault of the shear zone along the Blackwater-Little Lake fault system observed by Peltzer et al. []. Mapped traces of individual faults in the Mojave Block terminate within the block and do not continue across the Garlock Fault [Dokka and Travis, ].

Robust water fat separated dual-echo MRI by phase-sensitive reconstruction.

PubMed

Romu, Thobias; Dahlström, Nils; Leinhard, Olof Dahlqvist; Borga, Magnus

2017-09-01

The purpose of this work was to develop and evaluate a robust water-fat separation method for T1-weighted symmetric two-point Dixon data. A method for water-fat separation by phase unwrapping of the opposite-phase images by phase-sensitive reconstruction (PSR) is introduced. PSR consists of three steps; (1), identification of clusters of tissue voxels; (2), unwrapping of the phase in each cluster by solving Poisson's equation; and (3), finding the correct sign of each unwrapped opposite-phase cluster, so that the water-fat images are assigned the correct identities. Robustness was evaluated by counting the number of water-fat swap artifacts in a total of 733 image volumes. The method was also compared to commercial software. In the water-fat separated image volumes, the PSR method failed to unwrap the phase of one cluster and misclassified 10. One swap was observed in areas affected by motion and was constricted to the affected area. Twenty swaps were observed surrounding susceptibility artifacts, none of which spread outside the artifact affected regions. The PSR method had fewer swaps when compared to commercial software. The PSR method can robustly produce water-fat separated whole-body images based on symmetric two-echo spoiled gradient echo images, under both ideal conditions and in the presence of common artifacts. Magn Reson Med 78:1208-1216, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Quantitative twoplex glycan analysis using 12C6 and 13C6 stable isotope 2-aminobenzoic acid labelling and capillary electrophoresis mass spectrometry.

PubMed

Váradi, Csaba; Mittermayr, Stefan; Millán-Martín, Silvia; Bones, Jonathan

2016-12-01

Capillary electrophoresis (CE) offers excellent efficiency and orthogonality to liquid chromatographic (LC) separations for oligosaccharide structural analysis. Combination of CE with high resolution mass spectrometry (MS) for glycan analysis remains a challenging task due to the MS incompatibility of background electrolyte buffers and additives commonly used in offline CE separations. Here, a novel method is presented for the analysis of 2-aminobenzoic acid (2-AA) labelled glycans by capillary electrophoresis coupled to mass spectrometry (CE-MS). To ensure maximum resolution and excellent precision without the requirement for excessive analysis times, CE separation conditions including the concentration and pH of the background electrolyte, the effect of applied pressure on the capillary inlet and the capillary length were evaluated. Using readily available 12/13 C 6 stable isotopologues of 2-AA, the developed method can be applied for quantitative glycan profiling in a twoplex manner based on the generation of extracted ion electropherograms (EIE) for 12 C 6 'light' and 13 C 6 'heavy' 2-AA labelled glycan isotope clusters. The twoplex quantitative CE-MS glycan analysis platform is ideally suited for comparability assessment of biopharmaceuticals, such as monoclonal antibodies, for differential glycomic analysis of clinical material for potential biomarker discovery or for quantitative microheterogeneity analysis of different glycosylation sites within a glycoprotein. Additionally, due to the low injection volume requirements of CE, subsequent LC-MS analysis of the same sample can be performed facilitating the use of orthogonal separation techniques for structural elucidation or verification of quantitative performance.

Adolescents' beverage choice at school and the impact on sugar intake.

PubMed

Ensaff, H; Russell, J; Barker, M E

2016-02-01

To examine students' beverage choice in school, with reference to its contribution to students' intake of non-milk extrinsic (NME) sugars. Beverage and food selection data for students aged 11-18 years (n=2461) were collected from two large secondary schools in England, for a continuous period of 145 (school A) and 125 (school B) school days. Descriptive analysis followed by cluster analysis of the beverage data were performed separately for each school. More than a third of all items selected by students were beverages, and juice-based beverages were students' most popular choice (school A, 38.6%; school B, 35.2%). Mean NME sugars derived from beverages alone was high (school A, 16.7 g/student-day; school B, 12.9 g/student-day). Based on beverage purchases, six clusters of students were identified at each school (school A: 'juice-based', 'assorted', 'water', 'cartoned flavoured milk', 'bottled flavoured milk', 'high volume juice-based'; school B: 'assorted', 'water with juice-based', 'sparkling juice/juice-based', 'water', 'high volume water', 'high volume juice-based'). Both schools included 'high volume juice-based' clusters with the highest NME sugar means from beverages (school A, 28.6 g/student-day; school B, 24.4 g/student-day), and 'water' clusters with the lowest. A hierarchy in NME sugars was found according to cluster; students in the 'high volume juice-based' cluster returned significantly higher levels of NME sugars than students in other clusters. This study reveals the contribution that school beverages combined with students' beverage choice behaviour is making to students' NME sugar intake. These findings inform school food initiatives, and more generally public health policy around adolescents' dietary intake.

Geographical markers for Saccharomyces cerevisiae strains with similar technological origins domesticated for rice-based ethnic fermented beverages production in North East India.

PubMed

Jeyaram, Kumaraswamy; Tamang, Jyoti Prakash; Capece, Angela; Romano, Patrizia

2011-11-01

Autochthonous strains of Saccharomyces cerevisiae from traditional starters used for the production of rice-based ethnic fermented beverage in North East India were examined for their genetic polymorphism using mitochondrial DNA-RFLP and electrophoretic karyotyping. Mitochondrial DNA-RFLP analysis of S. cerevisiae strains with similar technological origins from hamei starter of Manipur and marcha starter of Sikkim revealed widely separated clusters based on their geographical origin. Electrophoretic karyotyping showed high polymorphism amongst the hamei strains within similar mitochondrial DNA-RFLP cluster and one unique karyotype of marcha strain was widely distributed in the Sikkim-Himalayan region. We conceptualized the possibility of separate domestication events for hamei strains in Manipur (located in the Indo-Burma biodiversity hotspot) and marcha strains in Sikkim (located in Himalayan biodiversity hotspot), as a consequence of less homogeneity in the genomic structure between these two groups, their clear separation being based on geographical origin, but not on technological origin and low strain level diversity within each group. The molecular markers developed based on HinfI-mtDNA-RFLP profile and the chromosomal doublets in chromosome VIII position of Sikkim-Himalayan strains could be effectively used as geographical markers for authenticating the above starter strains and differentiating them from other commercial strains.

Performance comparison of independent component analysis algorithms for fetal cardiac signal reconstruction: a study on synthetic fMCG data

NASA Astrophysics Data System (ADS)

Mantini, D.; Hild, K. E., II; Alleva, G.; Comani, S.

2006-02-01

Independent component analysis (ICA) algorithms have been successfully used for signal extraction tasks in the field of biomedical signal processing. We studied the performances of six algorithms (FastICA, CubICA, JADE, Infomax, TDSEP and MRMI-SIG) for fetal magnetocardiography (fMCG). Synthetic datasets were used to check the quality of the separated components against the original traces. Real fMCG recordings were simulated with linear combinations of typical fMCG source signals: maternal and fetal cardiac activity, ambient noise, maternal respiration, sensor spikes and thermal noise. Clusters of different dimensions (19, 36 and 55 sensors) were prepared to represent different MCG systems. Two types of signal-to-interference ratios (SIR) were measured. The first involves averaging over all estimated components and the second is based solely on the fetal trace. The computation time to reach a minimum of 20 dB SIR was measured for all six algorithms. No significant dependency on gestational age or cluster dimension was observed. Infomax performed poorly when a sub-Gaussian source was included; TDSEP and MRMI-SIG were sensitive to additive noise, whereas FastICA, CubICA and JADE showed the best performances. Of all six methods considered, FastICA had the best overall performance in terms of both separation quality and computation times.

Genetic diversity among air yam (Dioscorea bulbifera) varieties based on single sequence repeat markers.

PubMed

Silva, D M; Siqueira, M V B M; Carrasco, N F; Mantello, C C; Nascimento, W F; Veasey, E A

2016-05-23

Dioscorea is the largest genus in the Dioscoreaceae family, and includes a number of economically important species including the air yam, D. bulbifera L. This study aimed to develop new single sequence repeat primers and characterize the genetic diversity of local varieties that originated in several municipalities of Brazil. We developed an enriched genomic library for D. bulbifera resulting in seven primers, six of which were polymorphic, and added four polymorphic loci developed for other Dioscorea species. This resulted in 10 polymorphic primers to evaluate 42 air yam accessions. Thirty-three alleles (bands) were found, with an average of 3.3 alleles per locus. The discrimination power ranged from 0.113 to 0.834, with an average of 0.595. Both principal coordinate and cluster analyses (using the Jaccard Index) failed to clearly separate the accessions according to their origins. However, the 13 accessions from Conceição dos Ouros, Minas Gerais State were clustered above zero on the principal coordinate 2 axis, and were also clustered into one subgroup in the cluster analysis. Accessions from Ubatuba, São Paulo State were clustered below zero on the same principal coordinate 2 axis, except for one accession, although they were scattered in several subgroups in the cluster analysis. Therefore, we found little spatial structure in the accessions, although those from Conceição dos Ouros and Ubatuba exhibited some spatial structure, and that there is a considerable level of genetic diversity in D. bulbifera maintained by traditional farmers in Brazil.

A model-based cluster analysis of social experiences in clinically anxious youth: links to emotional functioning.

PubMed

Suveg, Cynthia; Jacob, Marni L; Whitehead, Monica; Jones, Anna; Kingery, Julie Newman

2014-01-01

Social difficulties are commonly associated with anxiety disorders in youth, yet are not well specified in the literature. The aim of this study was to identify patterns of social experiences in clinically anxious children and examine the associations with indices of emotional functioning. A model-based cluster analysis was conducted on parent-, teacher-, and child-reports of social experiences with 64 children, ages 7-12 years (M = 8.86 years, SD = 1.59 years; 60.3% boys; 85.7% Caucasian) with a primary diagnosis of separation anxiety disorder, social phobia, and/or generalized anxiety disorder. Follow-up analyses examined cluster differences on indices of emotional functioning. Findings yielded three clusters of social experiences that were unrelated to diagnosis: (1) Unaware Children (elevated scores on parent- and teacher-reports of social difficulties but relatively low scores on child-reports, n = 12), (2) Average Functioning (relatively average scores across all informants, n = 44), and (3) Victimized and Lonely (elevated child-reports of overt and relational victimization and loneliness and relatively low scores on parent- and teacher-reports of social difficulties, n = 8). Youth in the Unaware Children cluster were rated as more emotionally dysregulated by teachers and had a greater number of diagnoses than youth in the Average Functioning group. In contrast, the Victimized and Lonely group self-reported greater frequency of negative affect and reluctance to share emotional experiences than the Average Functioning cluster. Overall, this study demonstrates that social maladjustment in clinically anxious children can manifest in a variety of ways and assessment should include multiple informants and methods.

Constraining AGN triggering mechanisms through the clustering analysis of active black holes

NASA Astrophysics Data System (ADS)

Gatti, M.; Shankar, F.; Bouillot, V.; Menci, N.; Lamastra, A.; Hirschmann, M.; Fiore, F.

2016-02-01

The triggering mechanisms for active galactic nuclei (AGN) are still debated. Some of the most popular ones include galaxy interactions (IT) and disc instabilities (DIs). Using an advanced semi-analytic model (SAM) of galaxy formation, coupled to accurate halo occupation distribution modelling, we investigate the imprint left by each separate triggering process on the clustering strength of AGN at small and large scales. Our main results are as follows: (I) DIs, irrespective of their exact implementation in the SAM, tend to fall short in triggering AGN activity in galaxies at the centre of haloes with Mh > 1013.5 h-1 M⊙. On the contrary, the IT scenario predicts abundance of active central galaxies that generally agrees well with observations at every halo mass. (II) The relative number of satellite AGN in DIs at intermediate-to-low luminosities is always significantly higher than in IT models, especially in groups and clusters. The low AGN satellite fraction predicted for the IT scenario might suggest that different feeding modes could simultaneously contribute to the triggering of satellite AGN. (III) Both scenarios are quite degenerate in matching large-scale clustering measurements, suggesting that the sole average bias might not be an effective observational constraint. (IV) Our analysis suggests the presence of both a mild luminosity and a more consistent redshift dependence in the AGN clustering, with AGN inhabiting progressively less massive dark matter haloes as the redshift increases. We also discuss the impact of different observational selection cuts in measuring AGN clustering, including possible discrepancies between optical and X-ray surveys.

Clustering gene expression regulators: new approach to disease subtyping.

PubMed

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Clustering Gene Expression Regulators: New Approach to Disease Subtyping

PubMed Central

Pyatnitskiy, Mikhail; Mazo, Ilya; Shkrob, Maria; Schwartz, Elena; Kotelnikova, Ekaterina

2014-01-01

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient. PMID:24416320

Universal dynamical properties preclude standard clustering in a large class of biochemical data.

PubMed

Gomez, Florian; Stoop, Ralph L; Stoop, Ruedi

2014-09-01

Clustering of chemical and biochemical data based on observed features is a central cognitive step in the analysis of chemical substances, in particular in combinatorial chemistry, or of complex biochemical reaction networks. Often, for reasons unknown to the researcher, this step produces disappointing results. Once the sources of the problem are known, improved clustering methods might revitalize the statistical approach of compound and reaction search and analysis. Here, we present a generic mechanism that may be at the origin of many clustering difficulties. The variety of dynamical behaviors that can be exhibited by complex biochemical reactions on variation of the system parameters are fundamental system fingerprints. In parameter space, shrimp-like or swallow-tail structures separate parameter sets that lead to stable periodic dynamical behavior from those leading to irregular behavior. We work out the genericity of this phenomenon and demonstrate novel examples for their occurrence in realistic models of biophysics. Although we elucidate the phenomenon by considering the emergence of periodicity in dependence on system parameters in a low-dimensional parameter space, the conclusions from our simple setting are shown to continue to be valid for features in a higher-dimensional feature space, as long as the feature-generating mechanism is not too extreme and the dimension of this space is not too high compared with the amount of available data. For online versions of super-paramagnetic clustering see http://stoop.ini.uzh.ch/research/clustering. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Characterization of esculin-positive Pseudomonas fluorescens strains isolated from an underground brook.

PubMed

Svec, P; Stegnerová, H; Durnová, E; Sedlácek, I

2004-01-01

A group of sixteen esculin-positive fluorescent pseudomonads isolated from an underground brook flowing through a cave complex was characterized by biotyping, multiple enzyme restriction fragment length polymorphism analysis of 16S rDNA (MERFLP), ribotyping and whole-cell fatty-acid methyl-esters analysis (FAME). All strains were phenotypically close to Pseudomonas fluorescens, but they revealed high biochemical variability as well as some reactions atypical for P. fluorescens species. Because identification of pseudomonads by of biochemical testing is often unclear, further techniques were employed. Fingerprints obtained by MERFLP clearly showed that all strains represent P. fluorescens species. Ribotyping separated the strains analyzed into four groups corresponding almost completely (with the exception of one strain) to the clustering based on biochemical profiles. FAME analysis grouped all the strains into one cluster together with the P. putida (biotype A, B), P. chlororaphis and P. fluorescens biotype F representatives, but differentiated them from other FAME profiles of all pseudomonads included in the standard library TSBA 40 provided by MIDI, Inc.

Discrimination of three Pegaga (Centella) varieties and determination of growth-lighting effects on metabolites content based on the chemometry of 1H nuclear magnetic resonance spectroscopy.

PubMed

H, Maulidiani; Khatib, Alfi; Shaari, Khozirah; Abas, Faridah; Shitan, Mahendran; Kneer, Ralf; Neto, Victor; Lajis, Nordin H

2012-01-11

The metabolites of three species of Apiaceae, also known as Pegaga, were analyzed utilizing (1)H NMR spectroscopy and multivariate data analysis. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) resolved the species, Centella asiatica, Hydrocotyle bonariensis, and Hydrocotyle sibthorpioides, into three clusters. The saponins, asiaticoside and madecassoside, along with chlorogenic acids were the metabolites that contributed most to the separation. Furthermore, the effects of growth-lighting condition to metabolite contents were also investigated. The extracts of C. asiatica grown in full-day light exposure exhibited a stronger radical scavenging activity and contained more triterpenes (asiaticoside and madecassoside), flavonoids, and chlorogenic acids as compared to plants grown in 50% shade. This study established the potential of using a combination of (1)H NMR spectroscopy and multivariate data analyses in differentiating three closely related species and the effects of growth lighting, based on their metabolite contents and identification of the markers contributing to their differences.

Genetic variation in resistance to blast (Pyricularia oryzae Cavara) in rice (Oryza sativa L.) germplasms of Bangladesh

PubMed Central

Khan, Mohammad Ashik Iqbal; Latif, Mohammad Abdul; Khalequzzaman, Mohammad; Tomita, Asami; Ali, Mohammad Ansar; Fukuta, Yoshimichi

2017-01-01

Genetic variation in blast resistance was clarified in 334 Bangladesh rice accessions from 4 major ecotypes (Aus, Aman, Boro and Jhum). Cluster analysis of polymorphism data of 74 SSR markers separated these accessions into cluster I (corresponding to the Japonica Group) and cluster II (corresponding to the Indica Group). Cluster II accessions were represented with high frequency in all ecotypes. Cluster II was further subdivided into subclusters IIa and IIb. Subcluster IIa accessions were represented with high frequency in only Aus and Jhum ecotypes. Cluster I accessions were more frequent in the Aman ecotype than in other ecotypes. Distinct variations in resistance were found, and accessions were classified into 4 groups (A1, A2, B1 and B2) based on their reactions to standard differential blast isolates. The most susceptible group was A2 (which included susceptible variety Lijiangxintuanheigu, most of the differential varieties, and a few Bangladesh accessions), followed in order by A1, B2 and B1 (the most resistant). Accessions from 4 ecotypes fell with different frequencies into each of these resistance groups. These results demonstrated that Japonica Group accessions were found mainly in Aman, and Indica Group accessions were distributed across all ecotypes. Susceptible accessions were limited in Aus and Aman. PMID:29398943

Control of Chemical Effects in the Separation Process of a Differential Mobility / Mass Spectrometer System

PubMed Central

Schneider, Bradley B.; Coy, Stephen L.; Krylov, Evgeny V.; Nazarov, Erkinjon G.

2013-01-01

Differential mobility spectrometry (DMS) separates ions on the basis of the difference in their migration rates under high versus low electric fields. Several models describing the physical nature of this field mobility dependence have been proposed but emerging as a dominant effect is the clusterization model sometimes referred to as the dynamic cluster-decluster model. DMS resolution and peak capacity is strongly influenced by the addition of modifiers which results in the formation and dissociation of clusters. This process increases selectivity due to the unique chemical interactions that occur between an ion and neutral gas phase molecules. It is thus imperative to bring the parameters influencing the chemical interactions under control and find ways to exploit them in order to improve the analytical utility of the device. In this paper we describe three important areas that need consideration in order to stabilize and capitalize on the chemical processes that dominate a DMS separation. The first involves means of controlling the dynamic equilibrium of the clustering reactions with high concentrations of specific reagents. The second area involves a means to deal with the unwanted heterogeneous cluster ion populations emitted from the electrospray ionization process that degrade resolution and sensitivity. The third involves fine control of parameters that affect the fundamental collision processes, temperature and pressure. PMID:20065515

Structural Analysis of Cubane-Type Iron Clusters

PubMed Central

Tan, Lay Ling; Holm, R. H.; Lee, Sonny C.

2013-01-01

The generalized cluster type [M4(μ3-Q)4Ln]x contains the cubane-type [M4Q4]z core unit that can approach, but typically deviates from, perfect Td symmetry. The geometric properties of this structure have been analyzed with reference to Td symmetry by a new protocol. Using coordinates of M and Q atoms, expressions have been derived for interatomic separations, bond angles, and volumes of tetrahedral core units (M4, Q4) and the total [M4Q4] core (as a tetracapped M4 tetrahedron). Values for structural parameters have been calculated from observed average values for a given cluster type. Comparison of calculated and observed values measures the extent of deviation of a given parameter from that required in an exact tetrahedral structure. The procedure has been applied to the structures of over 130 clusters containing [Fe4Q4] (Q = S2−, Se2−, Te2−, [NPR3]−, [NR]2−) units, of which synthetic and biological sulfide-bridged clusters constitute the largest subset. General structural features and trends in structural parameters are identified and summarized. An extensive database of structural properties (distances, angles, volumes) has been compiled in Supporting Information. PMID:24072952

Structural Analysis of Cubane-Type Iron Clusters.

PubMed

Tan, Lay Ling; Holm, R H; Lee, Sonny C

2013-07-13

The generalized cluster type [M 4 (μ 3 -Q) 4 L n ] x contains the cubane-type [M 4 Q 4 ] z core unit that can approach, but typically deviates from, perfect T d symmetry. The geometric properties of this structure have been analyzed with reference to T d symmetry by a new protocol. Using coordinates of M and Q atoms, expressions have been derived for interatomic separations, bond angles, and volumes of tetrahedral core units (M 4 , Q 4 ) and the total [M 4 Q 4 ] core (as a tetracapped M 4 tetrahedron). Values for structural parameters have been calculated from observed average values for a given cluster type. Comparison of calculated and observed values measures the extent of deviation of a given parameter from that required in an exact tetrahedral structure. The procedure has been applied to the structures of over 130 clusters containing [Fe 4 Q 4 ] (Q = S 2- , Se 2- , Te 2- , [NPR 3 ] - , [NR] 2- ) units, of which synthetic and biological sulfide-bridged clusters constitute the largest subset. General structural features and trends in structural parameters are identified and summarized. An extensive database of structural properties (distances, angles, volumes) has been compiled in Supporting Information.

Egocentric daily activity recognition via multitask clustering.

PubMed

Yan, Yan; Ricci, Elisa; Liu, Gaowen; Sebe, Nicu

2015-10-01

Recognizing human activities from videos is a fundamental research problem in computer vision. Recently, there has been a growing interest in analyzing human behavior from data collected with wearable cameras. First-person cameras continuously record several hours of their wearers' life. To cope with this vast amount of unlabeled and heterogeneous data, novel algorithmic solutions are required. In this paper, we propose a multitask clustering framework for activity of daily living analysis from visual data gathered from wearable cameras. Our intuition is that, even if the data are not annotated, it is possible to exploit the fact that the tasks of recognizing everyday activities of multiple individuals are related, since typically people perform the same actions in similar environments, e.g., people working in an office often read and write documents). In our framework, rather than clustering data from different users separately, we propose to look for clustering partitions which are coherent among related tasks. In particular, two novel multitask clustering algorithms, derived from a common optimization problem, are introduced. Our experimental evaluation, conducted both on synthetic data and on publicly available first-person vision data sets, shows that the proposed approach outperforms several single-task and multitask learning methods.

Re-entrant phase behavior for systems with competition between phase separation and self-assembly

NASA Astrophysics Data System (ADS)

Reinhardt, Aleks; Williamson, Alexander J.; Doye, Jonathan P. K.; Carrete, Jesús; Varela, Luis M.; Louis, Ard A.

2011-03-01

In patchy particle systems where there is a competition between the self-assembly of finite clusters and liquid-vapor phase separation, re-entrant phase behavior can be observed, with the system passing from a monomeric vapor phase to a region of liquid-vapor phase coexistence and then to a vapor phase of clusters as the temperature is decreased at constant density. Here, we present a classical statistical mechanical approach to the determination of the complete phase diagram of such a system. We model the system as a van der Waals fluid, but one where the monomers can assemble into monodisperse clusters that have no attractive interactions with any of the other species. The resulting phase diagrams show a clear region of re-entrance. However, for the most physically reasonable parameter values of the model, this behavior is restricted to a certain range of density, with phase separation still persisting at high densities.

Gastrointestinal Fibroblasts Have Specialized, Diverse Transcriptional Phenotypes: A Comprehensive Gene Expression Analysis of Human Fibroblasts

PubMed Central

Ishii, Genichiro; Aoyagi, Kazuhiko; Sasaki, Hiroki; Ochiai, Atsushi

2015-01-01

Background Fibroblasts are the principal stromal cells that exist in whole organs and play vital roles in many biological processes. Although the functional diversity of fibroblasts has been estimated, a comprehensive analysis of fibroblasts from the whole body has not been performed and their transcriptional diversity has not been sufficiently explored. The aim of this study was to elucidate the transcriptional diversity of human fibroblasts within the whole body. Methods Global gene expression analysis was performed on 63 human primary fibroblasts from 13 organs. Of these, 32 fibroblasts from gastrointestinal organs (gastrointestinal fibroblasts: GIFs) were obtained from a pair of 2 anatomical sites: the submucosal layer (submucosal fibroblasts: SMFs) and the subperitoneal layer (subperitoneal fibroblasts: SPFs). Using hierarchical clustering analysis, we elucidated identifiable subgroups of fibroblasts and analyzed the transcriptional character of each subgroup. Results In unsupervised clustering, 2 major clusters that separate GIFs and non-GIFs were observed. Organ- and anatomical site-dependent clusters within GIFs were also observed. The signature genes that discriminated GIFs from non-GIFs, SMFs from SPFs, and the fibroblasts of one organ from another organ consisted of genes associated with transcriptional regulation, signaling ligands, and extracellular matrix remodeling. Conclusions GIFs are characteristic fibroblasts with specific gene expressions from transcriptional regulation, signaling ligands, and extracellular matrix remodeling related genes. In addition, the anatomical site- and organ-dependent diversity of GIFs was also discovered. These features of GIFs contribute to their specific physiological function and homeostatic maintenance, and create a functional diversity of the gastrointestinal tract. PMID:26046848

Robo-AO Discovery and Basic Characterization of Wide Multiple Star Systems in the Pleiades, Praesepe, and NGC 2264 Clusters

NASA Astrophysics Data System (ADS)

Hillenbrand, Lynne A.; Zhang, Celia; Riddle, Reed L.; Baranec, Christoph; Ziegler, Carl; Law, Nicholas M.; Stauffer, John

2018-02-01

We identify and roughly characterize 66 candidate binary star systems in the Pleiades, Praesepe, and NGC 2264 star clusters, based on robotic adaptive optics imaging data obtained using Robo-AO at the Palomar 60″ telescope. Only ∼10% of our imaged pairs were previously known. We detect companions at red optical wavelengths, with physical separations ranging from a few tens to a few thousands of au. A three-sigma contrast curve generated for each final image provides upper limits to the brightness ratios for any undetected putative companions. The observations are sensitive to companions with a maximum contrast of ∼6m at larger separations. At smaller separations, the mean (best) raw contrast at 2″ is 3.ͫ8 (6m), at 1″ is 3.ͫ0 (4.ͫ5), and at 0.″5 is 1.ͫ9 (3m). Point-spread function subtraction can recover nearly the full contrast in the closer separations. For detected candidate binary pairs, we report separations, position angles, and relative magnitudes. Theoretical isochrones appropriate to the Pleiades and Praesepe clusters are then used to determine the corresponding binary mass ratios, which range from 0.2 to 0.9 in q={m}2/{m}1. For our sample of roughly solar-mass (FGK type) stars in NGC 2264 and sub-solar-mass (K and early M-type) primaries in the Pleiades and Praesepe, the overall binary frequency is measured at ∼15.5% ± 2%. However, this value should be considered a lower limit to the true binary fraction within the specified separation and mass ratio ranges in these clusters, given that complex and uncertain corrections for sensitivity and completeness have not been applied.

CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

NASA Astrophysics Data System (ADS)

Franke, R.

2016-11-01

In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

Accurate prediction of secondary metabolite gene clusters in filamentous fungi.

PubMed

Andersen, Mikael R; Nielsen, Jakob B; Klitgaard, Andreas; Petersen, Lene M; Zachariasen, Mia; Hansen, Tilde J; Blicher, Lene H; Gotfredsen, Charlotte H; Larsen, Thomas O; Nielsen, Kristian F; Mortensen, Uffe H

2013-01-02

Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.

Drinker Types, Harm, and Policy-Related Variables: Results from the 2011 International Alcohol Control Study in New Zealand.

PubMed

Wall, Martin; Casswell, Sally

2017-05-01

The aim was to identify a typology of drinkers in New Zealand based on alcohol consumption, beverage choice, and public versus private drinking locations and investigate the relationship between drinker types, harms experienced, and policy-related variables. Model-based cluster analysis of male and female drinkers including volumes of alcohol consumed in the form of beer, wine, spirits, and ready-to-drinks (RTDs) in off- and on-premise settings. Cluster membership was then related to harm measures: alcohol dependence, self-rated health; and to 3 policy-relevant variables: liking for alcohol adverts, price paid for alcohol, and time of purchase. Males and females were analyzed separately. Men fell into 4 and women into 14 clearly discriminated clusters. The male clusters consumed a relatively high proportion of alcohol in the form of beer. Women had a number of small extreme clusters and some consumed mainly spirits-based RTDs, while others drank mainly wine. Those in the higher consuming clusters were more likely to have signs of alcohol dependency, to report lower satisfaction with their health, to like alcohol ads, and to have purchased late at night. Consumption patterns are sufficiently distinctive to identify typologies of male and female alcohol consumers. Women drinkers are more heterogeneous than men. The clusters relate differently to policy-related variables. Copyright © 2017 by the Research Society on Alcoholism.

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.

The Multiple Faces of Non-Cystic Fibrosis Bronchiectasis. A Cluster Analysis Approach.

PubMed

Martínez-García, Miguel Á; Vendrell, Montserrat; Girón, Rosa; Máiz-Carro, Luis; de la Rosa Carrillo, David; de Gracia, Javier; Olveira, Casilda

2016-09-01

The clinical presentation and prognosis of non-cystic fibrosis bronchiectasis are both very heterogeneous. To identify different clinical phenotypes for non-cystic fibrosis bronchiectasis and their impact on prognosis. Using a standardized protocol, we conducted a multicenter observational cohort study at six Spanish centers with patients diagnosed with non-cystic fibrosis bronchiectasis before December 31, 2005, with a 5-year follow-up from the bronchiectasis diagnosis. A cluster analysis was used to classify the patients into homogeneous groups by means of significant variables corresponding to different aspects of bronchiectasis (clinical phenotypes): age, sex, body mass index, smoking habit, dyspnea, macroscopic appearance of sputum, number of exacerbations, chronic colonization with Pseudomonas aeruginosa, FEV1, number of pulmonary lobes affected, idiopathic bronchiectasis, and associated chronic obstructive pulmonary disease. Survival analysis (Kaplan-Meier method and log-rank test) was used to evaluate the comparative survival of the different subgroups. A total of 468 patients with a mean age of 63 (15.9) years were analyzed. Of these, 58% were females, 39.7% had idiopathic bronchiectasis, and 29.3% presented with chronic Pseudomonas aeruginosa colonization. Cluster analysis showed four clinical phenotypes: (1) younger women with mild disease, (2) older women with mild disease, (3) older patients with severe disease who had frequent exacerbations, and (4) older patients with severe disease who did not have frequent exacerbations. The follow-up period was 54 months, during which there were 95 deaths. Mortality was low in the first and second groups (3.9% and 7.6%, respectively) and high for the third (37%) and fourth (40.8%) groups. The third cluster had a higher proportion of respiratory deaths than the fourth (77.8% vs. 34.4%; P < 0.001). Using cluster analysis, it is possible to separate patients with bronchiectasis into distinct clinical phenotypes with different prognoses.

Latent profile and cluster analysis of infant temperament: Comparisons across person-centered approaches.

PubMed

Gartstein, Maria A; Prokasky, Amanda; Bell, Martha Ann; Calkins, Susan; Bridgett, David J; Braungart-Rieker, Julia; Leerkes, Esther; Cheatham, Carol L; Eiden, Rina D; Mize, Krystal D; Jones, Nancy Aaron; Mireault, Gina; Seamon, Erich

2017-10-01

There is renewed interest in person-centered approaches to understanding the structure of temperament. However, questions concerning temperament types are not frequently framed in a developmental context, especially during infancy. In addition, the most common person-centered techniques, cluster analysis (CA) and latent profile analysis (LPA), have not been compared with respect to derived temperament types. To address these gaps, we set out to identify temperament types for younger and older infants, comparing LPA and CA techniques. Multiple data sets (N = 1,356; 672 girls, 677 boys) with maternal ratings of infant temperament obtained using the Infant Behavior Questionnaire-Revised (Gartstein & Rothbart, 2003) were combined. All infants were between 3 and 12 months of age (M = 7.85; SD = 3.00). Due to rapid development in the first year of life, LPA and CA were performed separately for younger (n = 731; 3 to 8 months of age) and older (n = 625; 9 to 12 months of age) infants. Results supported 3-profile/cluster solutions as optimal for younger infants, and 5-profile/cluster solutions for the older subsample, indicating considerable differences between early/mid and late infancy. LPA and CA solutions produced relatively comparable types for younger and older infants. Results are discussed in the context of developmental changes unique to the end of the first year of life, which likely account for the present findings. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Chemometric expertise of the quality of groundwater sources for domestic use.

PubMed

Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

2015-01-01

In the present study 49 representative sites have been selected for the collection of water samples from central water supplies with different geographical locations in the region of Kavala, Northern Greece. Ten physicochemical parameters (pH, electric conductivity, nitrate, chloride, sodium, potassium, total alkalinity, total hardness, bicarbonate and calcium) were analyzed monthly, in the period from January 2010 to December 2010. Chemometric methods were used for monitoring data mining and interpretation (cluster analysis, principal components analysis and source apportioning by principal components regression). The clustering of the chemical indicators delivers two major clusters related to the water hardness and the mineral components (impacted by sea, bedrock and acidity factors). The sampling locations are separated into three major clusters corresponding to the spatial distribution of the sites - coastal, lowland and semi-mountainous. The principal components analysis reveals two latent factors responsible for the data structures, which are also an indication for the sources determining the groundwater quality of the region (conditionally named "mineral" factor and "water hardness" factor). By the apportionment approach it is shown what the contribution is of each of the identified sources to the formation of the total concentration of each one of the chemical parameters. The mean values of the studied physicochemical parameters were found to be within the limits given in the 98/83/EC Directive. The water samples are appropriate for human consumption. The results of this study provide an overview of the hydrogeological profile of water supply system for the studied area.

[Identification and phylogenetic analysis of one strain of Lactobacillus delbrueckii subsp. bulgaricus separated from yoghourt].

PubMed

Wang, Chuan; Zhang, Chaowu; Pei, Xiaofang; Liu, Hengchuan

2007-11-01

For being further applied and studied, one strain of Lactobacillus delbrueckii subsp. bulgaricus (wch9901) separated from yoghourt which had been identified by phenotype characteristic analysis was identified by 16S rDNA and phylogenetic analyzed. The 16S rDNA of wch9901 was amplified with the genomic DNA of wch9901 as template, and the conservative sequences of the 16S rDNA as primers. Inserted 16S rDNA amplified into clonal vector pGEM-T under the function of T4 DNA ligase to construct recombined plasmid pGEM-wch9901 16S rDNA. The recombined plasmid was identified by restriction enzyme digestion, and the eligible plasmid was presented to sequencing company for DNA sequencing. Nucleic acid sequence was blast in GenBank and phylogenetic tree was constructed using neighbor-joining method of distance methods by Mega3.1 soft. Results of blastn showed that the homology of 16S rDNA of wch9901 with the 16S rDNA of Lactobacillus delbrueckii subsp. bulgaricus strains was higher than 96%. On the phylogenetic tree, wch9901 formed a separate branch and located between Lactobacillus delbrueckii subsp. bulgaricus LGM2 evolution branch and another evolution branch which was composed of Lactobacillus delbrueckii subsp. bulgaricus DL2 evolution cluster and Lactobacillus delbrueckii subsp. bulgaricus JSQ evolution cluster. The distance between wch9901 evolution branch and Lactobacillus delbrueckii subsp. bulgaricus LGM2 evolution branch was the closest. wch9901 belonged to Lactobacillus delbrueckii subsp. bulgaricus. wch9901 showed the closest evolution relationship to Lactobacillus delbrueckii subsp. bulgaricus LGM2.

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

Bonamigo, M.; Grillo, C.; Ettori, S.

We present a novel approach for a combined analysis of X-ray and gravitational lensing data and apply this technique to the merging galaxy cluster MACS J0416.1–2403. The method exploits the information on the intracluster gas distribution that comes from a fit of the X-ray surface brightness and then includes the hot gas as a fixed mass component in the strong-lensing analysis. With our new technique, we can separate the collisional from the collision-less diffuse mass components, thus obtaining a more accurate reconstruction of the dark matter distribution in the core of a cluster. We introduce an analytical description of themore » X-ray emission coming from a set of dual pseudo-isothermal elliptical mass distributions, which can be directly used in most lensing softwares. By combining Chandra observations with Hubble Frontier Fields imaging and Multi Unit Spectroscopic Explorer spectroscopy in MACS J0416.1–2403, we measure a projected gas-to-total mass fraction of approximately 10% at 350 kpc from the cluster center. Compared to the results of a more traditional cluster mass model (diffuse halos plus member galaxies), we find a significant difference in the cumulative projected mass profile of the dark matter component and that the dark matter over total mass fraction is almost constant, out to more than 350 kpc. In the coming era of large surveys, these results show the need of multiprobe analyses for detailed dark matter studies in galaxy clusters.« less

Characterization and analysis of temporal and spatial variations in habitat and macroinvertebrate community structure, Fountain Creek basin, Colorado Springs and vicinity, Colorado, 1998-2001

USGS Publications Warehouse

Bruce, James F.

2002-01-01

The Fountain Creek Basin in and around Colorado Springs, Colorado, is affected by various land- and water-use activities. Biological, hydrological, water-quality, and land-use data were collected at 10 sites in the Fountain Creek Basin from April 1998 through April 2001 to provide a baseline characterization of macroinvertebrate communities and habitat conditions for comparison in subsequent studies; and to assess variation in macroinvertebrate community structure relative to habitat quality. Analysis of variance results indicated that instream and riparian variables were not affected by season, but significant differences were found among sites. Nine metrics were used to describe and evaluate macroinvertebrate community structure. Statistical analysis indicated that for six of the nine metrics, significant variability occurred between spring and fall seasons for 60 percent of the sites. Cluster analysis (unweighted pair group method average) using macroinvertebrate presence-absence data showed a well-defined separation between spring and fall samples. Six of the nine metrics had significant spatial variation. Cluster analysis using Sorenson?s Coefficient of Community values computed from macroinvertebrate density (number of organisms per square meter) data showed that macroinvertebrate community structure was more similar among tributary sites than main-stem sites. Canonical correspondence analysis identified a substrate particle-size gradient from site-specific species-abundance data and environmental correlates that decreased the 10 sites to 5 site clusters and their associated taxa.

Inductive Sensor Performance in Partial Discharges and Noise Separation by Means of Spectral Power Ratios

PubMed Central

Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo

2014-01-01

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. PMID:24556674

Classification of natural and supernatural causes of mental distress. Development of a Mental Distress Explanatory Model Questionnaire.

PubMed

Eisenbruch, M

1990-11-01

This paper describes the background and development of a Mental Distress Explanatory Model Questionnaire designed to explore how people from different cultures explain mental distress. A 45-item questionnaire was developed with items derived from the Murdock et al. categories, with additional items covering western notions of physiological causation and stress. The questionnaire was administered to 261 people, mostly college students. Multi-dimensional scaling analysis shows four clusters of mental distress: a) stress; b) western physiological; c) nonwestern physiological; and d) supernatural. These clusters form two dimensions: western physiological vs. supernatural and impersonal vs. personalistic explanations. Natural and stress items are separated from supernatural and nonwestern physiological items along the first dimension. Brain damage, physical illness, and genetic defects have the greatest separation along the first dimension. Being hot, the body being out of balance, and wind currents passing through the body most strongly represent the non-western physiological category. The questionnaire has the potential to be used for community health screening and for monitoring patient care, as well as with students in the health sciences and with health practitioners.

Measuring Spatial Dependence for Infectious Disease Epidemiology

PubMed Central

Grabowski, M. Kate; Cummings, Derek A. T.

2016-01-01

Global spatial clustering is the tendency of points, here cases of infectious disease, to occur closer together than expected by chance. The extent of global clustering can provide a window into the spatial scale of disease transmission, thereby providing insights into the mechanism of spread, and informing optimal surveillance and control. Here the authors present an interpretable measure of spatial clustering, τ, which can be understood as a measure of relative risk. When biological or temporal information can be used to identify sets of potentially linked and likely unlinked cases, this measure can be estimated without knowledge of the underlying population distribution. The greater our ability to distinguish closely related (i.e., separated by few generations of transmission) from more distantly related cases, the more closely τ will track the true scale of transmission. The authors illustrate this approach using examples from the analyses of HIV, dengue and measles, and provide an R package implementing the methods described. The statistic presented, and measures of global clustering in general, can be powerful tools for analysis of spatially resolved data on infectious diseases. PMID:27196422

Identification of Staphylococcus spp. using (GTG)₅-PCR fingerprinting.

PubMed

Svec, Pavel; Pantůček, Roman; Petráš, Petr; Sedláček, Ivo; Nováková, Dana

2010-12-01

A group of 212 type and reference strains deposited in the Czech Collection of Microorganisms (Brno, Czech Republic) and covering 41 Staphylococcus species comprising 21 subspecies was characterised using rep-PCR fingerprinting with the (GTG)₅ primer in order to evaluate this method for identification of staphylococci. All strains were typeable using the (GTG)₅ primer and generated PCR products ranging from 200 to 4500 bp. Numerical analysis of the obtained fingerprints revealed (sub)species-specific clustering corresponding with the taxonomic position of analysed strains. Taxonomic position of selected strains representing the (sub)species that were distributed over multiple rep-PCR clusters was verified and confirmed by the partial rpoB gene sequencing. Staphylococcus caprae, Staphylococcus equorum, Staphylococcus sciuri, Staphylococcus piscifermentans, Staphylococcus xylosus, and Staphylococcus saprophyticus revealed heterogeneous fingerprints and each (sub)species was distributed over several clusters. However, representatives of the remaining Staphylococcus spp. were clearly separated in single (sub)species-specific clusters. These results showed rep-PCR with the (GTG)₅ primer as a fast and reliable method applicable for differentiation and straightforward identification of majority of Staphylococcus spp. Copyright © 2010 Elsevier GmbH. All rights reserved.

Apparatus for simultaneously disreefing a centrally reefed clustered parachute system

DOEpatents

Johnson, Donald W.

1988-01-01

A single multi-line cutter is connected to each of a cluster of parachutes by a separate short tether line that holds the parachutes, initially reefed by closed loop reefing lines, close to one another. The closed loop reefing lines and tether lines, one from each parachute, are disposed within the cutter to be simultaneously cut by its actuation when a central line attached between the payload and the cutter is stretched upon deployment of the cluster. A pyrotechnic or electronic time delay may be included in the cutter to delay the actual simultaneous cutting of all lines until the clustered parachutes attain a measure of stability prior to being disreefed. A second set of reefing lines and second tether lines may be provided for each parachute, to enable a two-stage, separately timed, step-by-step disreefing.

Apparatus for simultaneously disreefing a centrally reefed clustered parachute system

DOEpatents

Johnson, D.W.

1988-06-21

A single multi-line cutter is connected to each of a cluster of parachutes by a separate short tether line that holds the parachutes, initially reefed by closed loop reefing lines, close to one another. The closed loop reefing lines and tether lines, one from each parachute, are disposed within the cutter to be simultaneously cut by its actuation when a central line attached between the payload and the cutter is stretched upon deployment of the cluster. A pyrotechnic or electronic time delay may be included in the cutter to delay the actual simultaneous cutting of all lines until the clustered parachutes attain a measure of stability prior to being disreefed. A second set of reefing lines and second tether lines may be provided for each parachute, to enable a two-stage, separately timed, step-by-step disreefing. 13 figs.

Characterization of genome sequences and clinical features of coxsackievirus A6 strains collected in Hyogo, Japan in 1999-2013.

PubMed

Ogi, Miki; Yano, Yoshihiko; Chikahira, Masatsugu; Takai, Denshi; Oshibe, Tomohiro; Arashiro, Takeshi; Hanaoka, Nozomu; Fujimoto, Tsuguto; Hayashi, Yoshitake

2017-08-01

Coxsackievirus A6 (CV-A6) is an enterovirus, which is known to cause herpangina. However, since 2009 it has frequently been isolated from children with hand, foot, and mouth disease (HFMD). In Japan, CV-A6 has been linked to HFMD outbreaks in 2011 and 2013. In this study, the full-length genome sequencing of CV-A6 strains were analyzed to identify the association with clinical manifestations. Five thousand six hundred and twelve children with suspected enterovirus infection (0-17 years old) between 1999 and 2013 in Hyogo Prefecture, Japan, were enrolled. Enterovirus infection was confirmed with reverse transcriptase-PCR in 753 children (791 samples), 127 of whom (133 samples) were positive for CV-A6 based on the direct sequencing of the VP4 region. The complete genomes of CV-A6 from 22 positive patients with different clinical manifestations were investigated. A phylogenetic analysis divided these 22 strains into two clusters based on the VP1 region; cluster I contained strains collected in 1999-2009 and mostly related to herpangina, and cluster II contained strains collected in 2011-2013 and related to HFMD outbreak. Based on the full-length polyprotein analysis, the amino acid differences between the strains in cluster I and II were 97.7 ± 0.28%. Amino acid differences were detected in 17 positions within the polyprotein. Strains collected in 1999-2009 and those in 2011-2013 were separately clustered by phylogenetic analysis based on 5'UTR and 3Dpol region, as well as VP1 region. In conclusion, HFMD outbreaks by CV-A6 were recently frequent in Japan and the accumulation of genomic change might be associated with the clinical course. © 2017 Wiley Periodicals, Inc.

Two Introductions of Lyme Disease into Connecticut: A Geospatial Analysis of Human Cases from 1984 to 2012.

PubMed

Xue, Ling; Scoglio, Caterina; McVey, D Scott; Boone, Rebecca; Cohnstaedt, Lee W

2015-09-01

Lyme disease has become the most prevalent vector-borne disease in the United States and results in morbidity in humans, especially children. We used historical case distributions to explain vector-borne disease introductions and subsequent geographic expansion in the absence of disease vector data. We used geographic information system analysis of publicly available Connecticut Department of Public Health case data from 1984, 1985, and 1991 to 2012 for the 169 towns in Connecticut to identify the yearly clusters of Lyme disease cases. Our analysis identified the spatial and temporal origins of two separate introductions of Lyme disease into Connecticut and identified the subsequent direction and rate of spread. We defined both epidemic clusters of cases using significant long-term spatial autocorrelation. The incidence-weighted geographic mean analysis indicates a northern trend of geographic expansion for both epidemic clusters. In eastern Connecticut, as the epidemic progressed, the yearly shift in the geographic mean (rate of epidemic expansion) decreased each year until spatial equilibrium was reached in 2007. The equilibrium indicates a transition from epidemic Lyme disease spread to stable endemic transmission, and we associate this with a reduction in incidence. In western Connecticut, the parabolic distribution of the yearly geographic mean indicates that following the establishment of Lyme disease (1988) the epidemic quickly expanded northward and established equilibrium in 2009.

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.

Discrete Cosine Transform Image Coding With Sliding Block Codes

NASA Astrophysics Data System (ADS)

Divakaran, Ajay; Pearlman, William A.

1989-11-01

A transform trellis coding scheme for images is presented. A two dimensional discrete cosine transform is applied to the image followed by a search on a trellis structured code. This code is a sliding block code that utilizes a constrained size reproduction alphabet. The image is divided into blocks by the transform coding. The non-stationarity of the image is counteracted by grouping these blocks in clusters through a clustering algorithm, and then encoding the clusters separately. Mandela ordered sequences are formed from each cluster i.e identically indexed coefficients from each block are grouped together to form one dimensional sequences. A separate search ensues on each of these Mandela ordered sequences. Padding sequences are used to improve the trellis search fidelity. The padding sequences absorb the error caused by the building up of the trellis to full size. The simulations were carried out on a 256x256 image ('LENA'). The results are comparable to any existing scheme. The visual quality of the image is enhanced considerably by the padding and clustering.

NGC 2548: clumpy spatial and kinematic structure in an intermediate-age Galactic cluster

NASA Astrophysics Data System (ADS)

Vicente, Belén; Sánchez, Néstor; Alfaro, Emilio J.

2016-09-01

NGC 2548 is a ˜400-500 Myr old open cluster with evidence of spatial substructures likely caused by its interaction with the Galactic disc. In this work we use precise astrometric data from the Carte du Ciel - San Fernando (CdC-SF) catalogue to study the clumpy structure in this cluster. We confirm the fragmented structure of NGC 2548 but, additionally, the relatively high precision of our kinematic data lead us to the first detection of substructures in the proper motion space of a stellar cluster. There are three spatially separated cores each of which has its own counterpart in the proper motion distribution. The two main cores lie nearly parallel to the Galactic plane whereas the third one is significantly fainter than the others and it moves towards the Galactic plane separating from the rest of the cluster. We derive core positions and proper motions, as well as the stars belonging to each core.

A Feasibility Study of View-independent Gait Identification

DTIC Science & Technology

2012-03-01

ice skates . For walking, the footprint records for single pixels form clusters that are well separated in space and time. (Any overlap of contact...Pattern Recognition 2007, 1-8. Cheng M-H, Ho M-F & Huang C-L (2008), "Gait Analysis for Human Identification Through Manifold Learning and HMM... Learning and Cybernetics 2005, 4516-4521 Moeslund T B & Granum E (2001), "A Survey of Computer Vision-Based Human Motion Capture", Computer Vision

[Helgoland (Germany): hemogenetic study of an island population].

PubMed

Schmidt, H D; Scheil, H G; Winkelbauer, S

2001-03-01

24 haemogenetic markers (5 erythrocyte antigenes, 6 polymorphisms of serum proteins, 12 polymorphisms of red cell enzymes) had been studied in up to 80 individuals from the island of Helgoland (Germany). The cluster analysis separates clearly the Helgoland sample from the neighbouring populations as well as from European standard data. This special position is interpreted partly by genetic peculiarities developed in the course of time, partly as a consequence of genetic drift.

Clustering by neurocognition for fine-mapping of the schizophrenia susceptibility loci on chromosome 6p

PubMed Central

Lin, Sheng-Hsiang; Liu, Chih-Min; Liu, Yu-Li; Fann, Cathy Shen-Jang; Hsiao, Po-Chang; Wu, Jer-Yuarn; Hung, Shuen-Iu; Chen, Chun-Houh; Wu, Han-Ming; Jou, Yuh-Shan; Liu, Shi K.; Hwang, Tzung J.; Hsieh, Ming H.; Chang, Chien-Ching; Yang, Wei-Chih; Lin, Jin-Jia; Chou, Frank Huang-Chih; Faraone, Stephen V.; Tsuang, Ming T.; Hwu, Hai-Gwo; Chen, Wei J.

2009-01-01

Chromosome 6p is one of the most commonly implicated regions in the genome-wide linkage scans of schizophrenia, whereas further association studies for markers in this region were inconsistent likely due to heterogeneity. This study aimed to identify more homogeneous subgroups of families for fine mapping on regions around markers D6S296 and D6S309 (both in 6p24.3) as well as D6S274 (in 6p22.3) by means of similarity in neurocognitive functioning. A total of 160 families of patients with schizophrenia comprising at least two affected siblings who had data for 8 neurocognitive test variables of the Continuous Performance Test (CPT) and the Wisconsin Card Sorting Test (WCST) were subjected to cluster analysis with data visualization using the test scores of both affected siblings. Family clusters derived were then used separately in family-based association tests for 64 single nucleotide polymorphisms covering the region of 6p24.3 and 6p22.3. Three clusters were derived from the family-based clustering, with deficit cluster 1 representing deficit on the CPT, deficit cluster 2 representing deficit on both the CPT and the WCST, and a third cluster of non-deficit. After adjustment using false discovery rate for multiple testing, SNP rs13873 and haplotype rs1225934-rs13873 on BMP6-TXNDC5 genes were significantly associated with schizophrenia for the deficit cluster 1 but not for the deficit cluster 2 or non-deficit cluster. Our results provide further evidence that the BMP6-TXNDC5 locus on 6p24.3 may play a role in the selective impairments on sustained attention of schizophrenia. PMID:19694819

Do key dimensions of seed and seedling functional trait variation capture variation in recruitment probability?

PubMed

Larson, Julie E; Sheley, Roger L; Hardegree, Stuart P; Doescher, Paul S; James, Jeremy J

2016-05-01

Seedling recruitment is a critical driver of population dynamics and community assembly, yet we know little about functional traits that define different recruitment strategies. For the first time, we examined whether trait relatedness across germination and seedling stages allows the identification of general recruitment strategies which share core functional attributes and also correspond to recruitment outcomes in applied settings. We measured six seed and eight seedling traits (lab- and field-collected, respectively) for 47 varieties of dryland grasses and used principal component analysis (PCA) and cluster analysis to identify major dimensions of trait variation and to isolate trait-based recruitment groups, respectively. PCA highlighted some links between seed and seedling traits, suggesting that relative growth rate and root elongation rate are simultaneously but independently associated with seed mass and initial root mass (first axis), and with leaf dry matter content, specific leaf area, coleoptile tissue density and germination rate (second axis). Third and fourth axes captured separate tradeoffs between hydrothermal time and base water potential for germination, and between specific root length and root mass ratio, respectively. Cluster analysis separated six recruitment types along dimensions of germination and growth rates, but classifications did not correspond to patterns of germination, emergence or recruitment in the field under either of two watering treatments. Thus, while we have begun to identify major threads of functional variation across seed and seedling stages, our understanding of how this variation influences demographic processes-particularly germination and emergence-remains a key gap in functional ecology.

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.

Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration

USGS Publications Warehouse

Pyne, Matthew I.; Carlisle, Daren M.; Konrad, Christopher P.; Stein, Eric D.

2017-01-01

Regional classification of streams is an early step in the Ecological Limits of Hydrologic Alteration framework. Many stream classifications are based on an inductive approach using hydrologic data from minimally disturbed basins, but this approach may underrepresent streams from heavily disturbed basins or sparsely gaged arid regions. An alternative is a deductive approach, using watershed climate, land use, and geomorphology to classify streams, but this approach may miss important hydrological characteristics of streams. We classified all stream reaches in California using both approaches. First, we used Bayesian and hierarchical clustering to classify reaches according to watershed characteristics. Streams were clustered into seven classes according to elevation, sedimentary rock, and winter precipitation. Permutation-based analysis of variance and random forest analyses were used to determine which hydrologic variables best separate streams into their respective classes. Stream typology (i.e., the class that a stream reach is assigned to) is shaped mainly by patterns of high and mean flow behavior within the stream's landscape context. Additionally, random forest was used to determine which hydrologic variables best separate minimally disturbed reference streams from non-reference streams in each of the seven classes. In contrast to stream typology, deviation from reference conditions is more difficult to detect and is largely defined by changes in low-flow variables, average daily flow, and duration of flow. Our combined deductive/inductive approach allows us to estimate flow under minimally disturbed conditions based on the deductive analysis and compare to measured flow based on the inductive analysis in order to estimate hydrologic change.

Pt-Zn Clusters on Stoichiometric MgO(100) and TiO2(110): Dramatically Different Sintering Behavior

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

Dadras, Mostafa J.; Shen, Lu; Alexandrova, Anastassia N.

2015-03-02

Zn was suggested to be a promising additive to Pt in the catalysis of dehydrogenation reactions. In this work, mixed Pt-Zn clusters deposited on two simple oxides, MgO(100) and TiO2(110), were investigated. The stability of these systems against cluster sintering, one of the major mechanisms of catalyst deactivation, is simulated using a Metropolis Monte Carlo scheme under the assumption of the Ostwald ripening mechanism. Particle migration, association to and dissociation from clusters, and evaporation and redeposition of monomers were all included in the simulations. Simulations are done at several high temperatures relevant to reactions of catalytic dehydrogenation. The effect ofmore » temperature is included via both the Metropolis algorithm and the Boltzmann-weighted populations of the global and thermally accessible local minima on the density functional theory potential energy surfaces of clusters of all sizes and compositions up to tetramers. On both surfaces, clusters are shown to sinter quite rapidly. However, the resultant compositions of the clusters most resistant to sintering are quite different on the two supports. On TiO2(110), Pt and Zn appear to phase separate, preferentially forming clusters rich in just one or the other metal. On MgO(100), Pt and Zn remain well-mixed and form a range of bimetallic clusters of various compositions that appear relatively stable. However, Zn is more easily lost from MgO through evaporation. These phenomena were rationalized by several means of chemical bonding analysis.« less

Assessing the genome level diversity of Listeria monocytogenes from contaminated ice cream and environmental samples linked to a listeriosis outbreak in the United States.

PubMed

Chen, Yi; Luo, Yan; Curry, Phillip; Timme, Ruth; Melka, David; Doyle, Matthew; Parish, Mickey; Hammack, Thomas S; Allard, Marc W; Brown, Eric W; Strain, Errol A

2017-01-01

A listeriosis outbreak in the United States implicated contaminated ice cream produced by one company, which operated 3 facilities. We performed single nucleotide polymorphism (SNP)-based whole genome sequencing (WGS) analysis on Listeria monocytogenes from food, environmental and clinical sources, identifying two clusters and a single branch, belonging to PCR serogroup IIb and genetic lineage I. WGS Cluster I, representing one outbreak strain, contained 82 food and environmental isolates from Facility I and 4 clinical isolates. These isolates differed by up to 29 SNPs, exhibited 9 pulsed-field gel electrophoresis (PFGE) profiles and multilocus sequence typing (MLST) sequence type (ST) 5 of clonal complex 5 (CC5). WGS Cluster II contained 51 food and environmental isolates from Facility II, 4 food isolates from Facility I and 5 clinical isolates. Among them the isolates from Facility II and clinical isolates formed a clade and represented another outbreak strain. Isolates in this clade differed by up to 29 SNPs, exhibited 3 PFGE profiles and ST5. The only isolate collected from Facility III belonged to singleton ST489, which was in a single branch separate from Clusters I and II, and was not associated with the outbreak. WGS analyses clustered together outbreak-associated isolates exhibiting multiple PFGE profiles, while differentiating them from epidemiologically unrelated isolates that exhibited outbreak PFGE profiles. The complete genome of a Cluster I isolate allowed the identification and analyses of putative prophages, revealing that Cluster I isolates differed by the gain or loss of three putative prophages, causing the banding pattern differences among all 3 AscI-PFGE profiles observed in Cluster I isolates. WGS data suggested that certain ice cream varieties and/or production lines might have contamination sources unique to them. The SNP-based analysis was able to distinguish CC5 as a group from non-CC5 isolates and differentiate among CC5 isolates from different outbreaks/incidents.

Assessing the genome level diversity of Listeria monocytogenes from contaminated ice cream and environmental samples linked to a listeriosis outbreak in the United States

PubMed Central

Chen, Yi; Luo, Yan; Curry, Phillip; Timme, Ruth; Melka, David; Doyle, Matthew; Parish, Mickey; Hammack, Thomas S.; Allard, Marc W.; Brown, Eric W.; Strain, Errol A.

2017-01-01

A listeriosis outbreak in the United States implicated contaminated ice cream produced by one company, which operated 3 facilities. We performed single nucleotide polymorphism (SNP)-based whole genome sequencing (WGS) analysis on Listeria monocytogenes from food, environmental and clinical sources, identifying two clusters and a single branch, belonging to PCR serogroup IIb and genetic lineage I. WGS Cluster I, representing one outbreak strain, contained 82 food and environmental isolates from Facility I and 4 clinical isolates. These isolates differed by up to 29 SNPs, exhibited 9 pulsed-field gel electrophoresis (PFGE) profiles and multilocus sequence typing (MLST) sequence type (ST) 5 of clonal complex 5 (CC5). WGS Cluster II contained 51 food and environmental isolates from Facility II, 4 food isolates from Facility I and 5 clinical isolates. Among them the isolates from Facility II and clinical isolates formed a clade and represented another outbreak strain. Isolates in this clade differed by up to 29 SNPs, exhibited 3 PFGE profiles and ST5. The only isolate collected from Facility III belonged to singleton ST489, which was in a single branch separate from Clusters I and II, and was not associated with the outbreak. WGS analyses clustered together outbreak-associated isolates exhibiting multiple PFGE profiles, while differentiating them from epidemiologically unrelated isolates that exhibited outbreak PFGE profiles. The complete genome of a Cluster I isolate allowed the identification and analyses of putative prophages, revealing that Cluster I isolates differed by the gain or loss of three putative prophages, causing the banding pattern differences among all 3 AscI-PFGE profiles observed in Cluster I isolates. WGS data suggested that certain ice cream varieties and/or production lines might have contamination sources unique to them. The SNP-based analysis was able to distinguish CC5 as a group from non-CC5 isolates and differentiate among CC5 isolates from different outbreaks/incidents. PMID:28166293

Genetic Characterization of Turkish Snake Melon (Cucumis melo L. subsp. melo flexuosus Group) Accessions Revealed by SSR Markers.

PubMed

Solmaz, Ilknur; Kacar, Yildiz Aka; Simsek, Ozhan; Sari, Nebahat

2016-08-01

Snake melon is an important cucurbit crop especially in the Southeastern and the Mediterranean region of Turkey. It is consumed as fresh or pickled. The production is mainly done with the local landraces in the country. Turkey is one of the secondary diversification centers of melon and possesses valuable genetic resources which have different morphological characteristics in case of snake melon. Genetic diversity of snake melon genotypes collected from different regions of Turkey and reference genotypes obtained from World Melon Gene Bank in Avignon-France was examined using 13 simple sequence repeat (SSR) markers. A total of 69 alleles were detected, with an average of 5.31 alleles per locus. The polymorphism information content of SSR markers ranged from 0.19 to 0.57 (average 0.38). Based on cluster analysis, two major groups were defined. The first major group included only one accession (61), while the rest of all accessions grouped in the second major group and separated into different sub-clusters. Based on SSR markers, cluster analysis indicated that considerably high genetic variability exists among the examined accessions; however, Turkish snake melon accessions were grouped together with the reference snake melon accessions.

Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction

ERIC Educational Resources Information Center

Trivedi, Shubhendu; Pardos, Zachary A.; Sarkozy, Gabor N.; Heffernan, Neil T.

2012-01-01

Learning a more distributed representation of the input feature space is a powerful method to boost the performance of a given predictor. Often this is accomplished by partitioning the data into homogeneous groups by clustering so that separate models could be trained on each cluster. Intuitively each such predictor is a better representative of…

How do binary separations depend on cloud initial conditions?

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.; Zinnecker, H.

2003-11-01

We explore the consequences of a star formation scenario in which the isothermal collapse of a rotating, star-forming core is followed by prompt fragmentation into a cluster containing a small number (N <~ 10) of protostars and/or substellar objects. The subsequent evolution of the cluster is assumed to be dominated by dynamical interactions among cluster members, and this establishes the final properties of the binary and multiple systems. The characteristic scale of the fragmenting core is determined by the cloud initial conditions (such as temperature, angular momentum and mass), and we are able to relate the separation distributions of the final binary population to the properties of the star-forming core. Because the fragmentation scale immediately after the isothermal collapse is typically a factor of 3-10 too large, we conjecture that fragmentation into small clusters followed by dynamical evolution is required to account for the observed binary separation distributions. Differences in the environmental properties of the cores are expected to imprint differences on the characteristic dimensions of the binary systems they form. Recent observations of hierarchical systems, differences in binary characteristics among star forming regions and systematic variations in binary properties with primary mass can be interpreted in the context of this scenario.

Cardiometabolic Risk Clustering in Spinal Cord Injury: Results of Exploratory Factor Analysis

PubMed Central

2013-01-01

Background: Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. Objective: The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. Methods: One hundred twenty-one subjects (mean 37 ± 12 years; range, 18–73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). Results: The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3–factor model in persons with paraplegia (65.4% variance) and a 4–factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Conclusions: Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism. PMID:23960702

Optimization of b-value distribution for biexponential diffusion-weighted MR imaging of normal prostate.

PubMed

Jambor, Ivan; Merisaari, Harri; Aronen, Hannu J; Järvinen, Jukka; Saunavaara, Jani; Kauko, Tommi; Borra, Ronald; Pesola, Marko

2014-05-01

To determine the optimal b-value distribution for biexponential diffusion-weighted imaging (DWI) of normal prostate using both a computer modeling approach and in vivo measurements. Optimal b-value distributions for the fit of three parameters (fast diffusion Df, slow diffusion Ds, and fraction of fast diffusion f) were determined using Monte-Carlo simulations. The optimal b-value distribution was calculated using four individual optimization methods. Eight healthy volunteers underwent four repeated 3 Tesla prostate DWI scans using both 16 equally distributed b-values and an optimized b-value distribution obtained from the simulations. The b-value distributions were compared in terms of measurement reliability and repeatability using Shrout-Fleiss analysis. Using low noise levels, the optimal b-value distribution formed three separate clusters at low (0-400 s/mm2), mid-range (650-1200 s/mm2), and high b-values (1700-2000 s/mm2). Higher noise levels resulted into less pronounced clustering of b-values. The clustered optimized b-value distribution demonstrated better measurement reliability and repeatability in Shrout-Fleiss analysis compared with 16 equally distributed b-values. The optimal b-value distribution was found to be a clustered distribution with b-values concentrated in the low, mid, and high ranges and was shown to improve the estimation quality of biexponential DWI parameters of in vivo experiments. Copyright © 2013 Wiley Periodicals, Inc.

Preliminary Analysis of Two Years of the Massive Collision Monitoring Activity

NASA Technical Reports Server (NTRS)

McKnight, Darren; Matney, Mark; Walbert, Kris; Behrend, Sophie; Casey, Patrick; Speaks, Seth

2017-01-01

It is hypothesized that the interactions between many of the most massive derelicts in low Earth orbit are more frequent than modeled by the traditional combination of kinetic theory of gases and Poisson probability distribution function. This is suggested by the fact that there are clusters of derelicts where members' inclinations are nearly identical and their apogees/perigees overlap significantly resulting in periodic synchronization of the objects' orbits. In order to address this proposition, an experiment was designed and conducted over the last two years. Results from this monitoring and characterization experiment are presented with implications for proposed debris remediation strategies. Four separate clusters of massive derelicts were examined that are centered around 775km, 850km, 975km, and 1500km, respectively. In aggregate, the constituents of these clusters contain around 500 objects and about 800,000kg of mass; this equates to a third of all derelict mass in LEO. Preliminary analysis indicates that encounter rates over this time period for these objects are greater than is estimated by traditional techniques. Hypothesized dependencies between latitude of encounter, relative velocity, frequency of encounters, inclination, and differential semi-major axis were established and verified. This experiment also identified specific repeatable cluster dynamics that may reduce the cost/risk and enhance the effectiveness of debris remediation activities and also enable new operational debris remediation options.

Final Report of the Evaluation of the 1969-1970 Benjamin Franklin Cluster Program: Programs and Patterns for Disadvantaged High School Students. ESEA Title I.

ERIC Educational Resources Information Center

Hoffman, Louis J.

The Cluster Program at Benjamin Franklin High School, funded under Title I of the 1965 Elementary Secondary Education Act, is designed to be a school within a school in which 249 ninth grade students attend classes in two separate clusters. Each cluster is formulated such that all students receive instruction from five teachers in classes whose…

Artificial neural network modeling and cluster analysis for organic facies and burial history estimation using well log data: A case study of the South Pars Gas Field, Persian Gulf, Iran

NASA Astrophysics Data System (ADS)

Alizadeh, Bahram; Najjari, Saeid; Kadkhodaie-Ilkhchi, Ali

2012-08-01

Intelligent and statistical techniques were used to extract the hidden organic facies from well log responses in the Giant South Pars Gas Field, Persian Gulf, Iran. Kazhdomi Formation of Mid-Cretaceous and Kangan-Dalan Formations of Permo-Triassic Data were used for this purpose. Initially GR, SGR, CGR, THOR, POTA, NPHI and DT logs were applied to model the relationship between wireline logs and Total Organic Carbon (TOC) content using Artificial Neural Networks (ANN). The correlation coefficient (R2) between the measured and ANN predicted TOC equals to 89%. The performance of the model is measured by the Mean Squared Error function, which does not exceed 0.0073. Using Cluster Analysis technique and creating a binary hierarchical cluster tree the constructed TOC column of each formation was clustered into 5 organic facies according to their geochemical similarity. Later a second model with the accuracy of 84% was created by ANN to determine the specified clusters (facies) directly from well logs for quick cluster recognition in other wells of the studied field. Each created facies was correlated to its appropriate burial history curve. Hence each and every facies of a formation could be scrutinized separately and directly from its well logs, demonstrating the time and depth of oil or gas generation. Therefore potential production zone of Kazhdomi probable source rock and Kangan- Dalan reservoir formation could be identified while well logging operations (especially in LWD cases) were in progress. This could reduce uncertainty and save plenty of time and cost for oil industries and aid in the successful implementation of exploration and exploitation plans.

Concentrations of trace elements and iron in the Arctic soils of Belyi Island (the Kara Sea, Russia): patterns of variation across landscapes.

PubMed

Moskovchenko, D V; Kurchatova, A N; Fefilov, N N; Yurtaev, A A

2017-05-01

The concentrations of several trace elements and iron were determined in 26 soil samples from Belyi Island in the Kara Sea (West Siberian sector of Russian Arctic). The major types of soils predominating in the soil cover were sampled. The concentrations of trace elements (mg kg -1 ) varied within the following ranges: 119-561 for Mn, 9.5-126 for Zn, 0.082-2.5 for Cd, <0.5-19.2 for Cu, <0.5-132 for Pb, 0.011-0.081 for Hg, <0.5-10.3 for Co, and 7.6-108 for Cr; the concentration of Fe varied from 3943 to 37,899 mg kg -1 . The impact of particular soil properties (pH, carbon and nitrogen contents, particle-size distribution) on metal concentrations was analyzed by the methods of correlation, cluster, and factor analyses. The correlation analysis showed that metal concentrations are negatively correlated with the sand content and positively correlated with the contents of silt and clay fractions. The cluster analysis allowed separation of the soils into three clusters. Cluster I included the soils with the high organic matter content formed under conditions of poor drainage; cluster II, the low-humus sandy soils of the divides and slopes; and cluster III, saline soils of coastal marshes. It was concluded that the geomorphic position largely controls the soil properties. The obtained data were compared with data on metal concentrations in other regions of the Russian Arctic. In general, the concentrations of trace elements in the studied soils were within the ranges typical of the background Arctic territories. However, some soils of Belyi Island contained elevated concentrations of Pb and Cd.

The nif Gene Operon of the Methanogenic Archaeon Methanococcus maripaludis

PubMed Central

Kessler, Peter S.; Blank, Carrine; Leigh, John A.

1998-01-01

Nitrogen fixation occurs in two domains, Archaea and Bacteria. We have characterized a nif (nitrogen fixation) gene cluster in the methanogenic archaeon Methanococcus maripaludis. Sequence analysis revealed eight genes, six with sequence similarity to known nif genes and two with sequence similarity to glnB. The gene order, nifH, ORF105 (similar to glnB), ORF121 (similar to glnB), nifD, nifK, nifE, nifN, and nifX, was the same as that found in part in other diazotrophic methanogens and except for the presence of the glnB-like genes, also resembled the order found in many members of the Bacteria. Using transposon insertion mutagenesis, we determined that an 8-kb region required for nitrogen fixation corresponded to the nif gene cluster. Northern analysis revealed the presence of either a single 7.6-kb nif mRNA transcript or 10 smaller mRNA species containing portions of the large transcript. Polar effects of transposon insertions demonstrated that all of these mRNAs arose from a single promoter region, where transcription initiated 80 bp 5′ to nifH. Distinctive features of the nif gene cluster include the presence of the six primary nif genes in a single operon, the placement of the two glnB-like genes within the cluster, the apparent physical separation of the cluster from any other nif genes that might be in the genome, the fragmentation pattern of the mRNA, and the regulation of expression by a repression mechanism described previously. Our study and others with methanogenic archaea reporting multiple mRNAs arising from gene clusters with only a single putative promoter sequence suggest that mRNA processing following transcription may be a common occurrence in methanogens. PMID:9515920

Distinguishing fear versus distress symptomatology in pediatric OCD

PubMed Central

Rozenman, Michelle; Peris, Tara; Bergman, R. Lindsey; Chang, Susanna; O’Neill, Joseph; McCracken, James T.; Piacentini, John

2018-01-01

Prior research has identified OCD subtypes or “clusters” of symptoms that differentially relate to clinical features of the disorder. Given the high comorbidity between OCD and anxiety, OCD symptom clusters may more broadly associate with fear and/or distress internalizing constructs. This study examines fear and distress dimensions, including physical concerns (fear), separation anxiety (fear), perfectionism (distress), and anxious coping (distress), as predictors of previously empirically-derived OCD symptom clusters in a sample of 215 youth diagnosed with primary OCD (ages 7 to 17, mean age = 12.25). Self-reported separation fears predicted membership in Cluster 1 (aggressive, sexual, religious, somatic obsessions, and checking compulsions) while somatic/autonomic fears predicted membership in Cluster 2 (symmetry obsessions and ordering, counting, repeating compulsions). Results highlight the diversity of pediatric OCD symptoms and their differential association with fear, suggesting the need to carefully assess both OCD and global fear constructs that might be directly targeted in treatment. PMID:27225633

The Atacama Cosmology Telescope: Relation Between Galaxy Cluster Optical Richness and Sunyaev-Zel'dovich Effect

NASA Technical Reports Server (NTRS)

Sehgal, Neelima; Addison, Graeme; Battaglia, Nick; Battistelli, Elia S.; Bond, J. Richard; Das, Sudeep; Devlin, Mark J.; Dunkley, Joanna; Duenner, Rolando; Gralla, Megan;

An off-axis galaxy cluster merger: Abell 0141

NASA Astrophysics Data System (ADS)

Caglar, Turgay

2018-04-01

We present structural analysis results of Abell 0141 (z = 0.23) based on X-ray data. The X-ray luminosity map demonstrates that Abell 0141 (A0141) is a bimodal galaxy cluster, which is separated on the sky by ˜0.65 Mpc with an elongation along the north-south direction. The optical galaxy density map also demonstrates this bimodality. We estimate sub-cluster ICM temperatures of 5.17^{+0.20}_{-0.19} keV for A0141N and 5.23^{+0.24}_{-0.23} keV for A0141S. We obtain X-ray morphological parameters w = 0.034 ± 0.004, c = 0.113 ± 0.004, and w = 0.039 ± 0.004, c = 0.104 ± 0.005 for A0141N and A0141S, respectively. The resulting X-ray morphological parameters indicate that both sub-clusters are moderately disturbed non-cool core structures. We find a slight brightness jump in the bridge region, and yet, there is still an absence of strong X-ray emitting gas between sub-clusters. We discover a significantly hotspot (˜10 keV) between sub-clusters, and a Mach number M = 1.69^{+0.40}_{-0.37} is obtained by using the temperature jump condition. However, we did not find direct evidence for shock-heating between sub-clusters. We estimate the sub-clusters' central entropies as K0 > 100 keV cm2, which indicates that the sub-clusters are not cool cores. We find some evidence that the system undergoes an off-axis collision; however, the cores of each sub-clusters have not yet been destroyed. Due to the orientation of X-ray tails of sub-clusters, we suggest that the northern sub-cluster moves through the south-west direction, and the southern cluster moves through the north-east direction. In conclusion, we are witnessing an earlier phase of close core passage between sub-clusters.

The First Photometric Analysis of the Open Clusters Dolidze 32 and 36

NASA Astrophysics Data System (ADS)

Amin, M. Y.; Elsanhory, W. H.; Haroon, A. A.

2018-06-01

We present a first study of two open clusters Dolidze 32 and Dolidze 36 in the near-infrared region JHKs with the aid of PPMXL catalog. In our study, we used a method able to separate open cluster stars from those that belong to the stellar background. Our results of calculations indicate that for both cluster Dolidze 32 and Dolidze 36 the number of probable member is 286 and 780, respectively. We have estimated the cluster center for Dolidze 32 and Dolidze 36 are α = 18h41m4s.188 , δ = -04°04'57''.144 , α = 20h02m29s.95 , δ = 42°05'49''.2 , respectively. The limiting radius for both clusters Dolidze 32 and Dolidze 36 is about 0.94 ± 0.03 pc and 0.81 ± 0.03 pc, respectively. The Color Magnitude Diagram allows us to estimate the reddening E(B - V) = 1.41 ± 0.03 mag. for Dolidze 32 and E(B - V) = 0.19 ± 0.04 mag. for Dolidze 36 in such a way that the distance modulus (m - M) is 11.36 ± 0.02 and 10.10 ± 0.03 for both clusters, respectively. On the other hand, the luminosity and mass functions of these two open clusters, Dolidze 32 and Dolidze 36, have been estimated, showing that the estimated masses are 437 ± 21 M⊙ and 678 ± 26 M⊙, respectively, while the mass function slopes are -2.56 ± 0.62 and -2.01 ± 0.70 for Dolidze 32 and Dolidze 36, respectively. Finally, the dynamical state of these two clusters shows that only Dolidze 36 can be considered as a dynamically relaxed cluster.

Clinical and epidemiological analysis of Campylobacter fetus subsp. fetus infections in humans and comparative genetic analysis with strains isolated from cattle.

PubMed

Escher, Robert; Brunner, Colette; von Steiger, Niklaus; Brodard, Isabelle; Droz, Sara; Abril, Carlos; Kuhnert, Peter

2016-05-14

Campylobacter fetus subspecies fetus (CFF) is an important pathogen for both cattle and humans. We performed a systematic epidemiological and clinical study of patients and evaluated the genetic relatedness of 17 human and 17 bovine CFF isolates by using different genotyping methods. In addition, the serotype, the dissemination of the genomic island containing a type IV secretion system (T4SS) and resistance determinants for tetracycline and streptomycin were also evaluated. The isolates from patients diagnosed with CFF infection as well as those from faecal samples of healthy calves were genotyped using pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), as well as single locus sequence typing (SLST) targeting cmp1 and cmp2 genes encoding two major outer membrane proteins in CFF. The presence of the genomic island and identification of serotype was determined by PCRs targeting genes of the T4SS and the sap locus, respectively. Tetracycline and streptomycin resistance phenotypes were determined by minimal inhibitory concentration. Clinical data obtained from medical records and laboratory data were supplemented by data obtained via telephone interviews with the patients and treating physicians. PFGE analysis defined two major clusters; cluster A containing 16 bovine (80 %) isolates and cluster B containing 13 human (92 %) isolates, suggesting a host preference. Further genotypic analysis using MLST, SLST as well as sap and T4SS PCR showed the presence of genotypically identical isolates in cattle and humans. The low diversity observed within the cmp alleles of CFF corroborates the clonal nature of this pathogen. The genomic island containing the tetracycline and streptomycin resistance determinants was found in 55 % of the isolates in cluster A and correlated with phenotypic antibiotic resistance. Most human and bovine isolates were separated on two phylogenetic clusters. However, several human and bovine isolates were identical by diverse genotyping methods, indicating a possible link between strains from these two hosts.

MC 2: Dynamical Analysis of the Merging Galaxy Cluster MACS J1149.5+2223

DOE PAGES

Golovich, Nathan; Dawson, William A.; Wittman, David; ...

2016-10-31

Here, we present an analysis of the merging cluster MACS J1149.5+2223 using archival imaging from Subaru/Suprime-Cam and multi-object spectroscopy from Keck/DEIMOS and Gemini/GMOS. We employ two- and three-dimensional substructure tests and determine that MACS J1149.5+2223 is composed of two separate mergers among three subclusters occurring ~1 Gyr apart. The primary merger gives rise to elongated X-ray morphology and a radio relic in the southeast. The brightest cluster galaxy is a member of the northern subcluster of the primary merger. This subcluster is very massive (more » $${16.7}_{-1.60}^{+1.25}\\times {10}^{14}\\,{M}_{\\odot }$$). The southern subcluster is also very massive ($${10.8}_{-3.54}^{+3.37}\\times {10}^{14}\\,{M}_{\\odot }$$), yet it lacks an associated X-ray surface brightness peak, and it has been unidentified previously despite the detailed study of this Frontier Field cluster. A secondary merger is occurring in the north along the line of sight (LOS) with a third, less massive subcluster ($${1.20}_{-0.34}^{+0.19}\\times {10}^{14}\\,{M}_{\\odot }$$). We perform a Monte Carlo dynamical analysis on the main merger and estimate a collision speed at pericenter of $${2770}_{-310}^{+610}$$ km s -1. We show the merger to be returning from apocenter with core passage occurring $${1.16}_{-0.25}^{+0.50}$$ Gyr before the observed state. We identify the LOS merging subcluster in a strong lensing analysis in the literature and show that it is likely bound to MACS J1149 despite having reached an extreme collision velocity of ~4000 km s -1.« less

MC2: Dynamical Analysis of the Merging Galaxy Cluster MACS J1149.5+2223

NASA Astrophysics Data System (ADS)

Golovich, Nathan; Dawson, William A.; Wittman, David; Ogrean, Georgiana; van Weeren, Reinout; Bonafede, Annalisa

2016-11-01

We present an analysis of the merging cluster MACS J1149.5+2223 using archival imaging from Subaru/Suprime-Cam and multi-object spectroscopy from Keck/DEIMOS and Gemini/GMOS. We employ two- and three-dimensional substructure tests and determine that MACS J1149.5+2223 is composed of two separate mergers among three subclusters occurring ˜1 Gyr apart. The primary merger gives rise to elongated X-ray morphology and a radio relic in the southeast. The brightest cluster galaxy is a member of the northern subcluster of the primary merger. This subcluster is very massive ({16.7}-1.60+1.25× {10}14 {M}⊙ ). The southern subcluster is also very massive ({10.8}-3.54+3.37× {10}14 {M}⊙ ), yet it lacks an associated X-ray surface brightness peak, and it has been unidentified previously despite the detailed study of this Frontier Field cluster. A secondary merger is occurring in the north along the line of sight (LOS) with a third, less massive subcluster ({1.20}-0.34+0.19× {10}14 {M}⊙ ). We perform a Monte Carlo dynamical analysis on the main merger and estimate a collision speed at pericenter of {2770}-310+610 km s-1. We show the merger to be returning from apocenter with core passage occurring {1.16}-0.25+0.50 Gyr before the observed state. We identify the LOS merging subcluster in a strong lensing analysis in the literature and show that it is likely bound to MACS J1149 despite having reached an extreme collision velocity of ˜4000 km s-1.

Titanium Oxo Cluster with Six Peripheral Ferrocene Units and Its Photocurrent Response Properties for Saccharides.

PubMed

Hou, Jin-Le; Luo, Wen; Guo, Yao; Zhang, Ping; Yang, Shen; Zhu, Qin-Yu; Dai, Jie

2017-06-05

A unique titanium oxo cluster with a ferrocene ligand was synthesized and characterized by single crystal X-ray analysis. Six ferrocene carboxylates coordinate to a D 3d Ti 6 O 6 core to be a redox active cluster 1, [Ti 6 O 6 (O i Pr) 6 (O 2 CFc) 6 ]. An analogue 2, [Ti 6 O 6 (O i Pr) 6 (O 2 C i Bu) 6 ], where the redox active ferrocene group is replaced by isobutyrate, is also reported as a contrast. The six ferrocene moieties in 1 are structurally identical to give a main redox wave at E 1/2 = 0.62 V in dichloromethane investigated by cyclic voltammetry. Photocurrent responses using electrodes of clusters 1 and 2 were studied, and the response properties of 1 are better than those of 2. The electronic spectra and theoretical calculations indicate that charge transfer occurs from ferrocene to Ti(IV) in 1, and the presence of the ferrocene moiety gives efficient electron excitation and charge separation. Cluster 1 is a cooperative system of TiO cluster and redox active ferrocene. Photocurrent response properties of an electrode of 1 for four saccharides, glucose, fructose, maltose, and sucrose, were tested, and only reducing sugars were responsive. The electrode of 2 is also photocurrent responsive to saccharides, but the current densities are lower than those of redox active 1.

Revisiting the monster: the mass profile of the galaxy cluster Abell 3827 using dynamical and strong lensing constrains

NASA Astrophysics Data System (ADS)

Rodrigo Carrasco Damele, Eleazar; Verdugo, Tomas

2018-01-01

The galaxy cluster Abell 3827 is one of the most massive clusters know at z ≦ 0.1 (Richness class 2, BM typeI, X-ray LX = 2.4 x 1044 erg s-1). The Brightest Cluster Galaxy (BCG) in Abell 3827 is perhaps the most extreme example of ongoing galaxy cannibalism. The multi-component BCG hosts the stellar remnants nuclei of at least four bright elliptical galaxies embedded in a common assymetric halo extended up to 15 kpc. The most notorious characteristic of the BCG is the existence of a unique strong gravitational lens system located within the inner 15 kpc region. A mass estimation of the galaxy based on strong lensing model was presented in Carrasco et al (2010, ApJL, 715, 160). Moreover, the exceptional strong lensing lens system in Abell 3827 and the location of the four bright galaxies has been used to measure for the first time small physical separations between dark and ordinary matter (Williams et al. 2011, MNRAS, 415, 448, Massey et al. 2015, MNRAS, 449, 3393). In this contribution, we present a detailed strong lensing and dynamical analysis of the cluster Abell 3827 based on spectroscopic redshift of the lensed features and from ~70 spectroscopically confirmed member galaxies inside 0.5 x 0.5 Mpc from the cluster center.

CLASH-VLT: DISSECTING THE FRONTIER FIELDS GALAXY CLUSTER MACS J0416.1-2403 WITH ∼800 SPECTRA OF MEMBER GALAXIES

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

Balestra, I.; Sartoris, B.; Girardi, M.

2016-06-01

We present VIMOS-Very Large Telescope (VLT) spectroscopy of the Frontier Fields cluster MACS J0416.1-2403 ( z  = 0.397). Taken as part of the CLASH-VLT survey, the large spectroscopic campaign provided more than 4000 reliable redshifts over ∼600 arcmin{sup 2}, including ∼800 cluster member galaxies. The unprecedented sample of cluster members at this redshift allows us to perform a highly detailed dynamical and structural analysis of the cluster out to ∼2.2 r {sub 200} (∼4 Mpc). Our analysis of substructures reveals a complex system composed of a main massive cluster ( M {sub 200} ∼ 0.9 × 10{sup 15} M {sub ⊙} and σ{sub V,r200} ∼ 1000 km s{supmore » −1}) presenting two major features: (i) a bimodal velocity distribution, showing two central peaks separated by Δ V {sub rf} ∼ 1100 km s{sup −1} with comparable galaxy content and velocity dispersion, and (ii) a projected elongation of the main substructures along the NE–SW direction, with a prominent sub-clump ∼600 kpc SW of the center and an isolated BCG approximately halfway between the center and the SW clump. We also detect a low-mass structure at z  ∼ 0.390, ∼10′ south of the cluster center, projected at ∼3 Mpc, with a relative line-of-sight velocity of Δ V{sub rf} ∼ −1700 km s{sup −1}. The cluster mass profile that we obtain through our dynamical analysis deviates significantly from the “universal” NFW, being best fit by a Softened Isothermal Sphere model instead. The mass profile measured from the galaxy dynamics is found to be in relatively good agreement with those obtained from strong and weak lensing, as well as with that from the X-rays, despite the clearly unrelaxed nature of the cluster. Our results reveal an overall complex dynamical state of this massive cluster and support the hypothesis that the two main subclusters are being observed in a pre-collisional phase, in agreement with recent findings from radio and deep X-ray data. In this article, we also release the entire redshift catalog of 4386 sources in the field of this cluster, which includes 60 identified Chandra X-ray sources and 105 JVLA radio sources.« less

Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.

PubMed

Labounek, René; Bridwell, David A; Mareček, Radek; Lamoš, Martin; Mikl, Michal; Slavíček, Tomáš; Bednařík, Petr; Baštinec, Jaromír; Hluštík, Petr; Brázdil, Milan; Jan, Jiří

2018-01-01

Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

Relating Regime Structure to Probability Distribution and Preferred Structure of Small Errors in a Large Atmospheric GCM

NASA Astrophysics Data System (ADS)

Straus, D. M.

2007-12-01

The probability distribution (pdf) of errors is followed in identical twin studies using the COLA T63 AGCM, integrated with observed SST for 15 recent winters. 30 integrations per winter (for 15 winters) are available with initial errors that are extremely small. The evolution of the pdf is tested for multi-modality, and the results interpreted in terms of clusters / regimes found in: (a) the set of 15x30 integrations mentioned, and (b) a larger ensemble of 55x15 integrations made with the same GCM using the same SSTs. The mapping of pdf evolution and clusters is also carried out for each winter separately, using the clusters found in the 55-member ensemble for the same winter alone. This technique yields information on the change in regimes caused by different boundary forcing (Straus and Molteni, 2004; Straus, Corti and Molteni, 2006). Analysis of the growing errors in terms of baroclinic and barotropic components allows for interpretation of the corresponding instabilities.

Connecting the Particles in the Box - Controlled Fusion of Hexamer Nanocrystal Clusters within an AB6 Binary Nanocrystal Superlattice

PubMed Central

Treml, Benjamin E.; Lukose, Binit; Clancy, Paulette; Smilgies, Detlef-M; Hanrath, Tobias

2014-01-01

Binary nanocrystal superlattices present unique opportunities to create novel interconnected nanostructures by partial fusion of specific components of the superlattice. Here, we demonstrate the binary AB6 superlattice of PbSe and Fe2O3 nanocrystals as a model system to transform the central hexamer of PbSe nanocrystals into a single fused particle. We present detailed structural analysis of the superlattices by combining high-resolution X-ray scattering and electron microscopy. Molecular dynamics simulations show optimum separation of nanocrystals in agreement with the experiment and provide insights into the molecular configuration of surface ligands. We describe the concept of nanocrystal superlattices as a versatile ‘nanoreactor' to create and study novel materials based on precisely defined size, composition and structure of nanocrystals into a mesostructured cluster. We demonstrate ‘controlled fusion' of nanocrystals in the clusters in reactions initiated by thermal treatment and pulsed laser annealing. PMID:25339169

Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies.

PubMed

Huang, Yangxin; Lu, Xiaosun; Chen, Jiaqing; Liang, Juan; Zangmeister, Miriam

2017-10-27

Longitudinal and time-to-event data are often observed together. Finite mixture models are currently used to analyze nonlinear heterogeneous longitudinal data, which, by releasing the homogeneity restriction of nonlinear mixed-effects (NLME) models, can cluster individuals into one of the pre-specified classes with class membership probabilities. This clustering may have clinical significance, and be associated with clinically important time-to-event data. This article develops a joint modeling approach to a finite mixture of NLME models for longitudinal data and proportional hazard Cox model for time-to-event data, linked by individual latent class indicators, under a Bayesian framework. The proposed joint models and method are applied to a real AIDS clinical trial data set, followed by simulation studies to assess the performance of the proposed joint model and a naive two-step model, in which finite mixture model and Cox model are fitted separately.

Measuring spatially varying, multispectral, ultraviolet bidirectional reflectance distribution function with an imaging spectrometer

NASA Astrophysics Data System (ADS)

Li, Hongsong; Lyu, Hang; Liao, Ningfang; Wu, Wenmin

2016-12-01

The bidirectional reflectance distribution function (BRDF) data in the ultraviolet (UV) band are valuable for many applications including cultural heritage, material analysis, surface characterization, and trace detection. We present a BRDF measurement instrument working in the near- and middle-UV spectral range. The instrument includes a collimated UV light source, a rotation stage, a UV imaging spectrometer, and a control computer. The data captured by the proposed instrument describe spatial, spectral, and angular variations of the light scattering from a sample surface. Such a multidimensional dataset of an example sample is captured by the proposed instrument and analyzed by a k-mean clustering algorithm to separate surface regions with same material but different surface roughnesses. The clustering results show that the angular dimension of the dataset can be exploited for surface roughness characterization. The two clustered BRDFs are fitted to a theoretical BRDF model. The fitting results show good agreement between the measurement data and the theoretical model.

Seven Sisters Get WISE

NASA Image and Video Library

2010-07-16

This image shows the famous Pleiades cluster of stars as seen through the eyes of NASA Wide-field Infrared Survey Explorer; they are what astronomers call an open cluster of stars, loosely bound to each other to eventually go their separate ways.

Clustering of unhealthy behaviors in the aerobics center longitudinal study.

PubMed

Héroux, Mariane; Janssen, Ian; Lee, Duck-chul; Sui, Xuemei; Hebert, James R; Blair, Steven N

2012-04-01

Clustering of unhealthy behaviors has been reported in previous studies; however the link with all-cause mortality and differences between those with and without chronic disease requires further investigation. To observe the clustering effects of unhealthy diet, fitness, smoking, and excessive alcohol consumption in adults with and without chronic disease and to assess all-cause mortality risk according to the clustering of unhealthy behaviors. Participants were 13,621 adults (aged 20-84) from the Aerobics Center Longitudinal Study. Four health behaviors were observed (diet, fitness, smoking, and drinking). Baseline characteristics of the study population and bivariate relations between pairs of the health behaviors were evaluated separately for those with and without chronic disease using cross-tabulation and a chi-square test. The odds of partaking in unhealthy behaviors were also calculated. Latent class analysis (LCA) was used to assess clustering. Cox regression was used to assess the relationship between the behaviors and mortality. The four health behaviors were related to each other. LCA results suggested that two classes existed. Participants in class 1 had a higher probability of partaking in each of the four unhealthy behaviors than participants in class 2. No differences in health behavior clustering were found between participants with and without chronic disease. Mortality risk increased relative to the number of unhealthy behaviors participants engaged in. Unhealthy behaviors cluster together irrespective of chronic disease status. Such findings suggest that multi-behavioral intervention strategies can be similar in those with and without chronic disease.

Atlas of nonribosomal peptide and polyketide biosynthetic pathways reveals common occurrence of nonmodular enzymes.

PubMed

Wang, Hao; Fewer, David P; Holm, Liisa; Rouhiainen, Leo; Sivonen, Kaarina

2014-06-24

Nonribosomal peptides and polyketides are a diverse group of natural products with complex chemical structures and enormous pharmaceutical potential. They are synthesized on modular nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) enzyme complexes by a conserved thiotemplate mechanism. Here, we report the widespread occurrence of NRPS and PKS genetic machinery across the three domains of life with the discovery of 3,339 gene clusters from 991 organisms, by examining a total of 2,699 genomes. These gene clusters display extraordinarily diverse organizations, and a total of 1,147 hybrid NRPS/PKS clusters were found. Surprisingly, 10% of bacterial gene clusters lacked modular organization, and instead catalytic domains were mostly encoded as separate proteins. The finding of common occurrence of nonmodular NRPS differs substantially from the current classification. Sequence analysis indicates that the evolution of NRPS machineries was driven by a combination of common descent and horizontal gene transfer. We identified related siderophore NRPS gene clusters that encoded modular and nonmodular NRPS enzymes organized in a gradient. A higher frequency of the NRPS and PKS gene clusters was detected from bacteria compared with archaea or eukarya. They commonly occurred in the phyla of Proteobacteria, Actinobacteria, Firmicutes, and Cyanobacteria in bacteria and the phylum of Ascomycota in fungi. The majority of these NRPS and PKS gene clusters have unknown end products highlighting the power of genome mining in identifying novel genetic machinery for the biosynthesis of secondary metabolites.

Circular Mixture Modeling of Color Distribution for Blind Stain Separation in Pathology Images.

PubMed

Li, Xingyu; Plataniotis, Konstantinos N

2017-01-01

In digital pathology, to address color variation and histological component colocalization in pathology images, stain decomposition is usually performed preceding spectral normalization and tissue component segmentation. This paper examines the problem of stain decomposition, which is a naturally nonnegative matrix factorization (NMF) problem in algebra, and introduces a systematical and analytical solution consisting of a circular color analysis module and an NMF-based computation module. Unlike the paradigm of existing stain decomposition algorithms where stain proportions are computed from estimated stain spectra using a matrix inverse operation directly, the introduced solution estimates stain spectra and stain depths via probabilistic reasoning individually. Since the proposed method pays extra attentions to achromatic pixels in color analysis and stain co-occurrence in pixel clustering, it achieves consistent and reliable stain decomposition with minimum decomposition residue. Particularly, aware of the periodic and angular nature of hue, we propose the use of a circular von Mises mixture model to analyze the hue distribution, and provide a complete color-based pixel soft-clustering solution to address color mixing introduced by stain overlap. This innovation combined with saturation-weighted computation makes our study effective for weak stains and broad-spectrum stains. Extensive experimentation on multiple public pathology datasets suggests that our approach outperforms state-of-the-art blind stain separation methods in terms of decomposition effectiveness.

Shock Heating of the Merging Galaxy Cluster A521

NASA Technical Reports Server (NTRS)

Bourdin, H.; Mazzotta, P.; Markevitch, M.; Giacintucci, S.; Brunetti, G.

2013-01-01

A521 is an interacting galaxy cluster located at z = 0.247, hosting a low-frequency radio halo connected to an eastern radio relic. Previous Chandra observations hinted at the presence of an X-ray brightness edge at the position of the relic, which may be a shock front. We analyze a deep observation of A521 recently performed with XMM-Newton in order to probe the cluster structure up to the outermost regions covered by the radio emission. The cluster atmosphere exhibits various brightness and temperature anisotropies. In particular, two cluster cores appear to be separated by two cold fronts. We find two shock fronts, one that was suggested by Chandra and that is propagating to the east, and another to the southwestern cluster outskirt. The two main interacting clusters appear to be separated by a shock-heated region, which exhibits a spatial correlation with the radio halo. The outer edge of the radio relic coincides spatially with a shock front, suggesting that this shock is responsible for the generation of cosmic-ray electrons in the relic. The propagation direction and Mach number of the shock front derived from the gas density jump, M = 2.4 +/- 0.2, are consistent with expectations from the radio spectral index, under the assumption of Fermi I acceleration mechanism.

Clustering of brain tumor cells: a first step for understanding tumor recurrence

NASA Astrophysics Data System (ADS)

Khain, Evgeniy; Nowicki, M. O.; Chiocca, E. A.; Lawler, S. E.; Schneider-Mizell, C. M.; Sander, L. M.

2012-02-01

Glioblastoma tumors are highly invasive; therefore the overall prognosis of patients remains poor, despite major improvements in treatment techniques. Cancer cells detach from the inner tumor core and actively migrate away [1]; eventually these invasive cells might form clusters, which can develop to recurrent tumors. In vitro experiments in collagen gel [1] followed the clustering dynamics of different glioma cell lines. Based on the experimental data, we formulated a stochastic model for cell dynamics, which identified two mechanisms of clustering. First, there is a critical value of the strength of adhesion; above the threshold, large clusters grow from a homogeneous suspension of cells; below it, the system remains homogeneous, similarly to the ordinary phase separation. Second, when cells form a cluster, there is evidence that their proliferation rate increases. We confirmed the theoretical predictions in a separate cell migration experiment on a substrate and found that both mechanisms are crucial for cluster formation and growth [2]. In addition to their medical importance, these phenomena present exciting examples of pattern formation and collective cell behavior in intrinsically non-equilibrium systems [3]. [4pt] [1] A. M. Stein et al, Biophys. J., 92, 356 (2007). [0pt] [2] E. Khain et al, EPL 88, 28006 (2009). [0pt] [3] E. Khain et al, Phys. Rev. E. 83, 031920 (2011).

Geometry and topology of the space of sonar target echos.

PubMed

Robinson, Michael; Fennell, Sean; DiZio, Brian; Dumiak, Jennifer

2018-03-01

Successful synthetic aperture sonar target classification depends on the "shape" of the scatterers within a target signature. This article presents a workflow that computes a target-to-target distance from persistence diagrams, since the "shape" of a signature informs its persistence diagram in a structure-preserving way. The target-to-target distances derived from persistence diagrams compare favorably against those derived from spectral features and have the advantage of being substantially more compact. While spectral features produce clusters associated to each target type that are reasonably dense and well formed, the clusters are not well-separated from one another. In rather dramatic contrast, a distance derived from persistence diagrams results in highly separated clusters at the expense of some misclassification of outliers.

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

MC 2: A Deeper Look at ZwCl 2341.1+0000 with Bayesian Galaxy Clustering and Weak Lensing Analyses

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

Benson, B.; Wittman, D. M.; Golovich, N.

ZwCl 2341.1+0000, a merging galaxy cluster with disturbed X-ray morphology and widely separated (~3 Mpc) double radio relics, was thought to be an extremely massive (10 - 30 X 10 14M⊙) and complex system with little known about its merger history. We present JVLA 2-4 GHz observations of the cluster, along with new spectroscopy from our Keck/DEIMOS survey, and apply Gaussian Mixture Modeling to the three-dimensional distribution of 227 con rmed cluster galaxies. After adopting the Bayesian Information Criterion to avoid over tting, which we discover can bias total dynamical mass estimates high, we nd that a three-substructure model withmore » a total dynamical mass estimate of 9:39 ± 0:81 X 10 14M⊙ is favored. We also present deep Subaru imaging and perform the rst weak lensing analysis on this system, obtaining a weak lensing mass estimate of 5:57±2:47X10 14M⊙. This is a more robust estimate because it does not depend on the dynamical state of the system, which is disturbed due to the merger. Our results indicate that ZwCl 2341.1+0000 is a multiple merger system comprised of at least three substructures, with the main merger that produced the radio relics occurring near to the plane of the sky, and a younger merger in the North occurring closer to the line of sight. Dynamical modeling of the main merger reproduces observed quantities (relic positions and polarizations, subcluster separation and radial velocity difference), if the merger axis angle of ~10 +34 -6 degrees and the collision speed at pericenter is ~1900 +300 -200 km/s.« less

MC 2: A Deeper Look at ZwCl 2341.1+0000 with Bayesian Galaxy Clustering and Weak Lensing Analyses

DOE PAGES

Benson, B.; Wittman, D. M.; Golovich, N.; ...

2017-05-16

ZwCl 2341.1+0000, a merging galaxy cluster with disturbed X-ray morphology and widely separated (~3 Mpc) double radio relics, was thought to be an extremely massive (10 - 30 X 10 14M⊙) and complex system with little known about its merger history. We present JVLA 2-4 GHz observations of the cluster, along with new spectroscopy from our Keck/DEIMOS survey, and apply Gaussian Mixture Modeling to the three-dimensional distribution of 227 con rmed cluster galaxies. After adopting the Bayesian Information Criterion to avoid over tting, which we discover can bias total dynamical mass estimates high, we nd that a three-substructure model withmore » a total dynamical mass estimate of 9:39 ± 0:81 X 10 14M⊙ is favored. We also present deep Subaru imaging and perform the rst weak lensing analysis on this system, obtaining a weak lensing mass estimate of 5:57±2:47X10 14M⊙. This is a more robust estimate because it does not depend on the dynamical state of the system, which is disturbed due to the merger. Our results indicate that ZwCl 2341.1+0000 is a multiple merger system comprised of at least three substructures, with the main merger that produced the radio relics occurring near to the plane of the sky, and a younger merger in the North occurring closer to the line of sight. Dynamical modeling of the main merger reproduces observed quantities (relic positions and polarizations, subcluster separation and radial velocity difference), if the merger axis angle of ~10 +34 -6 degrees and the collision speed at pericenter is ~1900 +300 -200 km/s.« less

75 FR 41523 - Delphi Corporation, a Subsidiary of Delphi Holdings, LLC, Including On-Site Leased Workers From...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-16

... workers are engaged in the production of fuel modules, instrument clusters, and air meters. The review... production of instrument clusters, separated from employment on or after March 30, 2006 through May 15, 2009... date established for TA-W-70,988 to read May 16, 2009 for workers producing instrument clusters and...

Differentiation of Shewanella putrefaciens and Shewanella alga on the basis of whole-cell protein profiles, ribotyping, phenotypic characterization, and 16S rRNA gene sequence analysis.

PubMed Central

Vogel, B F; Jørgensen, K; Christensen, H; Olsen, J E; Gram, L

1997-01-01

Seventy-six presumed Shewanella putrefaciens isolates from fish, oil drillings, and clinical specimens, the type strain of Shewanella putrefaciens (ATCC 8071), the type strain of Shewanella alga (IAM 14159), and the type strain of Shewanella hanedai (ATCC 33224) were compared by several typing methods. Numerical analysis of sodium dodecyl sulfate-polyacrylamide gel electrophoresis of whole-cell protein and ribotyping patterns showed that the strains were separated into two distinct clusters with 56% +/- 10% and 40% +/- 14% similarity for whole-cell protein profiling and ribotyping, respectively. One cluster consisted of 26 isolates with 52 to 55 mol% G + C and included 15 human isolates, mostly clinical specimens, 8 isolates from marine waters, and the type strain of S. alga. This homogeneous cluster of mesophilic, halotolerant strains was by all analyses identical to the recently defined species S. alga (U. Simidu et al., Int. J. Syst. Bacteriol, 40:331-336, 1990). Fifty-two typically psychrotolerant strains formed the other, more heterogeneous major cluster, with 43 to 47 mol% G + C. The type strain of S. putrefaciens was included in this group. The two groups were confirmed by 16S rRNA gene sequence analysis. It is concluded that the isolates must be considered two different species, S. alga and S. putrefaciens, and that most mesophilic isolates formerly identified as S. putrefaciens belong to S. alga. The ecological role and potential pathogenicity of S. alga can be evaluated only if the organism is correctly identified. PMID:9172338

Deep Brain Stimulation of the Subthalamic Nucleus Improves Lexical Switching in Parkinsons Disease Patients.

PubMed

Vonberg, Isabelle; Ehlen, Felicitas; Fromm, Ortwin; Kühn, Andrea A; Klostermann, Fabian

2016-01-01

Reduced verbal fluency (VF) has been reported in patients with Parkinson's disease (PD), especially those treated by Deep Brain Stimulation of the subthalamic nucleus (STN DBS). To delineate the nature of this dysfunction we aimed at identifying the particular VF-related operations modified by STN DBS. Eleven PD patients performed VF tasks in their STN DBS ON and OFF condition. To differentiate VF-components modulated by the stimulation, a temporal cluster analysis was performed, separating production spurts (i.e., 'clusters' as correlates of automatic activation spread within lexical fields) from slower cluster transitions (i.e., 'switches' reflecting set-shifting towards new lexical fields). The results were compared to those of eleven healthy control subjects. PD patients produced significantly more switches accompanied by shorter switch times in the STN DBS ON compared to the STN DBS OFF condition. The number of clusters and time intervals between words within clusters were not affected by the treatment state. Although switch behavior in patients with DBS ON improved, their task performance was still lower compared to that of healthy controls. Beyond impacting on motor symptoms, STN DBS seems to influence the dynamics of cognitive procedures. Specifically, the results are in line with basal ganglia roles for cognitive switching, in the particular case of VF, from prevailing lexical concepts to new ones.

Brain structure and function correlates of cognitive subtypes in schizophrenia.

PubMed

Geisler, Daniel; Walton, Esther; Naylor, Melissa; Roessner, Veit; Lim, Kelvin O; Charles Schulz, S; Gollub, Randy L; Calhoun, Vince D; Sponheim, Scott R; Ehrlich, Stefan

2015-10-30

Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

MACS J0553.4-3342: a young merging galaxy cluster caught through the eyes of Chandra and HST

NASA Astrophysics Data System (ADS)

Pandge, M. B.; Bagchi, Joydeep; Sonkamble, S. S.; Parekh, Viral; Patil, M. K.; Dabhade, Pratik; Navale, Nilam R.; Raychaudhury, Somak; Jacob, Joe

2017-12-01

We present a detailed analysis of a young merging galaxy cluster MACS J0553.4-3342 (z=0.43) from Chandra X-ray and Hubble Space Telescope archival data. X-ray observations confirm that the X-ray emitting intra-cluster medium (ICM) in this system is among the hottest (average T = 12.1 ± 0.6 keV) and most luminous known. Comparison of X-ray and optical images confirms that this system hosts two merging subclusters SC1 and SC2, separated by a projected distance of about 650 kpc. The subcluster SC2 is newly identified in this work, while another subcluster (SC0), previously thought to be a part of this merging system, is shown to be possibly a foreground object. Apart from two subclusters, we find a tail-like structure in the X-ray image, extending to a projected distance of ∼1 Mpc, along the north-east direction of the eastern subcluster (SC1). From a surface brightness analysis, we detect two sharp surface brightness edges at ∼40 (∼320 kpc) and ∼80 arcsec (∼640 kpc) to the east of SC1. The inner edge appears to be associated with a merger-driven cold front, while the outer one is likely to be due to a shock front, the presence of which, ahead of the cold front, makes this dynamically disturbed cluster interesting. Nearly all the early-type galaxies belonging to the two subclusters, including their brightest cluster galaxies, are part of a well-defined red sequence.

Contrasting behavior of heterochromatic and euchromatic chromosome portions and pericentric genome separation in pre-bouquet spermatocytes of hybrid mice.

PubMed

Scherthan, Harry; Schöfisch, Karina; Dell, Thomas; Illner, Doris

2014-12-01

The spatial distribution of parental genomes has attracted much interest because intranuclear chromosome distribution can modulate the transcriptome of cells and influence the efficacy of meiotic homologue pairing. Pairing of parental chromosomes is imperative to sexual reproduction as it translates into homologue segregation and genome haploidization to counteract the genome doubling at fertilization. Differential FISH tagging of parental pericentromeric genome portions and specific painting of euchromatic chromosome arms in Mus musculus (MMU) × Mus spretus (MSP) hybrid spermatogenesis disclosed a phase of homotypic non-homologous pericentromere clustering that led to parental pericentric genome separation from the pre-leptoteneup to zygotene stages. Preferential clustering of MMU pericentromeres correlated with particular enrichment of epigenetic marks (H3K9me3), HP1-γ and structural maintenance of chromosomes SMC6 complex proteins at the MMU major satellite DNA repeats. In contrast to the separation of heterochromatic pericentric genome portions, the euchromatic arms of homeologous chromosomes showed considerable presynaptic pairing already during leptotene stage of all mice investigated. Pericentric genome separation was eventually disbanded by telomere clustering that concentrated both parental pericentric genome portions in a limited nuclear sector of the bouquet nucleus. Our data disclose the differential behavior of pericentromeric heterochromatin and the euchromatic portions of the parental genomes during homologue search. Homotypic pericentromere clustering early in prophase I may contribute to the exclusion of large repetitive DNA domains from homology search, while the telomere bouquet congregates and registers spatially separated portions of the genome to fuel synapsis initiation and high levels of homologue pairing, thus contributing to the fidelity of meiosis and reproduction.

Coma cluster ultradiffuse galaxies are not standard radio galaxies

NASA Astrophysics Data System (ADS)

Struble, Mitchell F.

2018-02-01

Matching members in the Coma cluster catalogue of ultradiffuse galaxies (UDGs) from SUBARU imaging with a very deep radio continuum survey source catalogue of the cluster using the Karl G. Jansky Very Large Array (VLA) within a rectangular region of ∼1.19 deg2 centred on the cluster core reveals matches consistent with random. An overlapping set of 470 UDGs and 696 VLA radio sources in this rectangular area finds 33 matches within a separation of 25 arcsec; dividing the sample into bins with separations bounded by 5, 10, 20 and 25 arcsec finds 1, 4, 17 and 11 matches. An analytical model estimate, based on the Poisson probability distribution, of the number of randomly expected matches within these same separation bounds is 1.7, 4.9, 19.4 and 14.2, each, respectively, consistent with the 95 per cent Poisson confidence intervals of the observed values. Dividing the data into five clustercentric annuli of 0.1° and into the four separation bins, finds the same result. This random match of UDGs with VLA sources implies that UDGs are not radio galaxies by the standard definition. Those VLA sources having integrated flux >1 mJy at 1.4 GHz in Miller, Hornschemeier and Mobasher without SDSS galaxy matches are consistent with the known surface density of background radio sources. We briefly explore the possibility that some unresolved VLA sources near UDGs could be young, compact, bright, supernova remnants of Type Ia events, possibly in the intracluster volume.

Method for in-situ calibration of electrophoretic analysis systems

DOEpatents

Liu, Changsheng; Zhao, Hequan

2005-05-08

An electrophoretic system having a plurality of separation lanes is provided with an automatic calibration feature in which each lane is separately calibrated. For each lane, the calibration coefficients map a spectrum of received channel intensities onto values reflective of the relative likelihood of each of a plurality of dyes being present. Individual peaks, reflective of the influence of a single dye, are isolated from among the various sets of detected light intensity spectra, and these can be used to both detect the number of dye components present, and also to establish exemplary vectors for the calibration coefficients which may then be clustered and further processed to arrive at a calibration matrix for the system. The system of the present invention thus permits one to use different dye sets to tag DNA nucleotides in samples which migrate in separate lanes, and also allows for in-situ calibration with new, previously unused dye sets.

Clumpak: a program for identifying clustering modes and packaging population structure inferences across K.

PubMed

Kopelman, Naama M; Mayzel, Jonathan; Jakobsson, Mattias; Rosenberg, Noah A; Mayrose, Itay

2015-09-01

The identification of the genetic structure of populations from multilocus genotype data has become a central component of modern population-genetic data analysis. Application of model-based clustering programs often entails a number of steps, in which the user considers different modelling assumptions, compares results across different predetermined values of the number of assumed clusters (a parameter typically denoted K), examines multiple independent runs for each fixed value of K, and distinguishes among runs belonging to substantially distinct clustering solutions. Here, we present Clumpak (Cluster Markov Packager Across K), a method that automates the postprocessing of results of model-based population structure analyses. For analysing multiple independent runs at a single K value, Clumpak identifies sets of highly similar runs, separating distinct groups of runs that represent distinct modes in the space of possible solutions. This procedure, which generates a consensus solution for each distinct mode, is performed by the use of a Markov clustering algorithm that relies on a similarity matrix between replicate runs, as computed by the software Clumpp. Next, Clumpak identifies an optimal alignment of inferred clusters across different values of K, extending a similar approach implemented for a fixed K in Clumpp and simplifying the comparison of clustering results across different K values. Clumpak incorporates additional features, such as implementations of methods for choosing K and comparing solutions obtained by different programs, models, or data subsets. Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model-based analyses of population structure in population genetics and molecular ecology. © 2015 John Wiley & Sons Ltd.

Controlled assembly and single electron charging of monolayer protected Au144 clusters: an electrochemistry and scanning tunneling spectroscopy study

NASA Astrophysics Data System (ADS)

Bodappa, Nataraju; Fluch, Ulrike; Fu, Yongchun; Mayor, Marcel; Moreno-García, Pavel; Siegenthaler, Hans; Wandlowski, Thomas

2014-11-01

Single gold particles may serve as room temperature single electron memory units because of their size dependent electronic level spacing. Here, we present a proof-of-concept study by electrochemically controlled scanning probe experiments performed on tailor-made Au particles of narrow dispersity. In particular, the charge transport characteristics through chemically synthesized hexane-1-thiol and 4-pyridylbenzene-1-thiol mixed monolayer protected Au144 clusters (MPCs) by differential pulse voltammetry (DPV) and electrochemical scanning tunneling spectroscopy (EC-STS) are reported. The pyridyl groups exposed by the Au-MPCs enable their immobilization on Pt(111) substrates. By varying the humidity during their deposition, samples coated by stacks of compact monolayers of Au-MPCs or decorated with individual, laterally separated Au-MPCs are obtained. DPV experiments with stacked monolayers of Au144-MPCs and EC-STS experiments with laterally separated individual Au144-MPCs are performed both in aqueous and ionic liquid electrolytes. Lower capacitance values were observed for individual clusters compared to ensemble clusters. This trend remains the same irrespective of the composition of the electrolyte surrounding the Au144-MPC. However, the resolution of the energy level spacing of the single clusters is strongly affected by the proximity of neighboring particles.Single gold particles may serve as room temperature single electron memory units because of their size dependent electronic level spacing. Here, we present a proof-of-concept study by electrochemically controlled scanning probe experiments performed on tailor-made Au particles of narrow dispersity. In particular, the charge transport characteristics through chemically synthesized hexane-1-thiol and 4-pyridylbenzene-1-thiol mixed monolayer protected Au144 clusters (MPCs) by differential pulse voltammetry (DPV) and electrochemical scanning tunneling spectroscopy (EC-STS) are reported. The pyridyl groups exposed by the Au-MPCs enable their immobilization on Pt(111) substrates. By varying the humidity during their deposition, samples coated by stacks of compact monolayers of Au-MPCs or decorated with individual, laterally separated Au-MPCs are obtained. DPV experiments with stacked monolayers of Au144-MPCs and EC-STS experiments with laterally separated individual Au144-MPCs are performed both in aqueous and ionic liquid electrolytes. Lower capacitance values were observed for individual clusters compared to ensemble clusters. This trend remains the same irrespective of the composition of the electrolyte surrounding the Au144-MPC. However, the resolution of the energy level spacing of the single clusters is strongly affected by the proximity of neighboring particles. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03793f

Identification of suitable genes contributes to lung adenocarcinoma clustering by multiple meta-analysis methods.

PubMed

Yang, Ze-Hui; Zheng, Rui; Gao, Yuan; Zhang, Qiang

2016-09-01

With the widespread application of high-throughput technology, numerous meta-analysis methods have been proposed for differential expression profiling across multiple studies. We identified the suitable differentially expressed (DE) genes that contributed to lung adenocarcinoma (ADC) clustering based on seven popular multiple meta-analysis methods. Seven microarray expression profiles of ADC and normal controls were extracted from the ArrayExpress database. The Bioconductor was used to perform the data preliminary preprocessing. Then, DE genes across multiple studies were identified. Hierarchical clustering was applied to compare the classification performance for microarray data samples. The classification efficiency was compared based on accuracy, sensitivity and specificity. Across seven datasets, 573 ADC cases and 222 normal controls were collected. After filtering out unexpressed and noninformative genes, 3688 genes were remained for further analysis. The classification efficiency analysis showed that DE genes identified by sum of ranks method separated ADC from normal controls with the best accuracy, sensitivity and specificity of 0.953, 0.969 and 0.932, respectively. The gene set with the highest classification accuracy mainly participated in the regulation of response to external stimulus (P = 7.97E-04), cyclic nucleotide-mediated signaling (P = 0.01), regulation of cell morphogenesis (P = 0.01) and regulation of cell proliferation (P = 0.01). Evaluation of DE genes identified by different meta-analysis methods in classification efficiency provided a new perspective to the choice of the suitable method in a given application. Varying meta-analysis methods always present varying abilities, so synthetic consideration should be taken when providing meta-analysis methods for particular research. © 2015 John Wiley & Sons Ltd.

Genomic characterization and expression analysis of four apolipoprotein A-IV paralogs in Senegalese sole (Solea senegalensis Kaup).

PubMed

Roman-Padilla, J; Rodríguez-Rua, A; Claros, M G; Hachero-Cruzado, I; Manchado, M

2016-01-01

The apolipoprotein A-IV (ApoA-IV) plays a key role in lipid transport and feed intake regulation. In this work, four cDNA sequences encoding ApoA-IV paralogs were identified. Sequence analysis revealed conserved structural features including the common 33-codon block and nine repeated motifs. Gene structure analysis identified four exons and three introns except for apoA-IVAa1 (with only 3 exons). Synteny analysis showed that the four paralogs were structured into two clusters (cluster A containing apoA-IVAa1 and apoA-IVAa2 and cluster B with apoA-IVBa3 and apoA-IVBa4) linked to an apolipoprotein E. Phylogenetic analysis clearly separated the paralogs according to their cluster organization as well as revealed four subclades highly conserved in Acanthopterygii. Whole-mount analyses (WISH) in early larvae (0 and 1day post-hatch (dph)) showed that the four paralogs were mainly expressed in yolk syncytial layer surrounding the oil globules. Later, at 3 and 5dph, the four paralogs were mainly expressed in liver and intestine although with differences in their relative abundance and temporal expression patterns. Diet supply triggered the intensity of WISH signals in the intestine of the four paralogs. Quantification of mRNA abundance by qPCR using whole larvae only detected the induction by diet at 5dph. Moreover, transcript levels increased progressively with age except for apoA-IVAa2, which appeared as a low-expressed isoform. Expression analysis in juvenile tissues confirmed that the four paralogs were mainly expressed in liver and intestine and secondary in other tissues. The role of these ApoA-IV genes in lipid transport and the possible role of apoA-IVAa2 as a regulatory form are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Detection of a variable number of ribosomal DNA loci by fluorescent in situ hybridization in Populus species.

PubMed

Prado, E A; Faivre-Rampant, P; Schneider, C; Darmency, M A

1996-10-01

Fluorescent in situ hybridization (FISH) was applied to related Populus species (2n = 19) in order to detect rDNA loci. An interspecific variability in the number of hybridization sites was revealed using as probe an homologous 25S clone from Populus deltoides. The application of image analysis methods to measure fluorescence intensity of the hybridization signals has enabled us to characterize major and minor loci in the 18S-5.8S-25S rDNA. We identified one pair of such rDNA clusters in Populus alba; two pairs, one major and one minor, in both Populus nigra and P. deltoides; and three pairs in Populus balsamifera, (two major and one minor) and Populus euroamericana (one major and two minor). FISH results are in agreement with those based on RFLP analysis. The pBG13 probe containing 5S sequence from flax detected two separate clusters corresponding to the two size classes of units that coexist within 5S rDNA of most Populus species. Key words : Populus spp., fluorescent in situ hybridization, FISH, rDNA variability, image analysis.

Properties and behaviour of FAC currents in the inner magnetosphere

NASA Astrophysics Data System (ADS)

Yang, Junying; Dunlop, Malcolm; Yang, Yanyan; Xiong, Chao; Lühr, Hermann; Cao, Jinbin; Li, Liuyuan; Ma, Yuduan; Shen, Chao

2017-04-01

Cusp, region 1 and 2, and other large scale field-aligned currents (FACs), are sampled in situ by both the four Cluster spacecraft and by the three Swarm spacecraft at different altitudes, separated by a few to several Earth radii, and sometimes simultaneously. Here, the capability of Swarm-Cluster coordination for probing the behaviour of the field aligned currents (FACs) at medium and low orbits is explored. Joint signatures of R1 and R2 FACs (as well as cusp, R0 and NBZ currents) can be found and compared in terms of the magnetic signatures, using multi-spacecraft analysis where possible. Using the Swarm configuration, statistical correlation analysis of the local time variation of R1/R2 FACs can be shown and compared to standard MVA analysis. For context, we identify the associated auroral boundaries through application of a method to determine the FAC intensity gradients in order to interpret and resolve the R1 and R2 FACs. We also explore the relation of R2 FACs to the ring current properties measured in situ.

Detecting the influence of ornamental Berberis thunbergii var. atropurpurea in invasive populations of Berberis thunbergii (Berberidaceae) using AFLP1.

PubMed

Lubell, Jessica D; Brand, Mark H; Lehrer, Jonathan M; Holsinger, Kent E

2008-06-01

Japanese barberry (Berberis thunbergii DC.) is a widespread invasive plant that remains an important landscape shrub represented by ornamental, purple-leaved forms of the botanical variety atropurpurea. These forms differ greatly in appearance from feral plants, bringing into question whether they contribute to invasive populations or whether the invasions represent self-sustaining populations derived from the initial introduction of the species in the late 19th century. In this study we used amplified fragment length polymorphism (AFLP) markers to determine whether genetic contributions from B. t. var. atropurpurea are found within naturalized Japanese barberry populations in southern New England. Bayesian clustering of AFLP genotypes and principal coordinate analysis distinguished B. t. var. atropurpurea genotypes from 85 plants representing five invasive populations. While a single feral plant resembled B. t. var. atropurpurea phenotypically and fell within the same genetic cluster, all other naturalized plants sampled were genetically distinct from the purple-leaved genotypes. Seven plants from two different sites possessed morphology consistent with Berberis vulgaris (common barberry) or B. ×ottawensis (B. thunbergii × B. vulgaris). Genetic analysis placed these plants in two clusters separate from B. thunbergii. Although the Bayesian analysis indicated some introgression of B. t. var. atropurpurea and B. vulgaris, these genotypes have had limited influence on extant feral populations of B. thunbergii.

Users' perception as a tool to improve urban beach planning and management.

PubMed

Cervantes, Omar; Espejel, Ileana; Arellano, Evarista; Delhumeau, Sheila

2008-08-01

Four beaches that share physiographic characteristics (sandy, wide, and long) but differ in socioeconomic and cultural terms (three are located in northwestern Mexico and one in California, USA) were evaluated by beach users. Surveys (565) composed of 36 questions were handed out to beach users on weekends and holidays in 2005. The 25 questions that revealed the most information were selected by factor analysis and classified by cluster analysis. Beach users' preferences were assigned a value by comparing the present survey results with the characteristics of an "ideal" recreational urban beach. Cluster analysis separated three groups of questions: (a) services and infrastructure, (b) recreational activities, and (c) beach conditions. Cluster linkage distance (r=0.82, r=0.78, r=0.67) was used as a weight and multiplied by the value of beach descriptive factors. Mazatlán and Oceanside obtained the highest values because there are enough infrastructure and services; on the contrary, Ensenada and Rosarito were rated medium and low because infrastructure and services are lacking. The presently proposed method can contribute to improving current beach evaluations because the final score represents the beach users' evaluation of the quality of the beach. The weight considered in the present study marks the beach users' preferences among the studied beaches. Adding this weight to beach evaluation will contribute to more specific beach planning in which users' perception is considered.

Users' Perception as a Tool to Improve Urban Beach Planning and Management

NASA Astrophysics Data System (ADS)

Cervantes, Omar; Espejel, Ileana; Arellano, Evarista; Delhumeau, Sheila

2008-08-01

Four beaches that share physiographic characteristics (sandy, wide, and long) but differ in socioeconomic and cultural terms (three are located in northwestern Mexico and one in California, USA) were evaluated by beach users. Surveys (565) composed of 36 questions were handed out to beach users on weekends and holidays in 2005. The 25 questions that revealed the most information were selected by factor analysis and classified by cluster analysis. Beach users’ preferences were assigned a value by comparing the present survey results with the characteristics of an “ideal” recreational urban beach. Cluster analysis separated three groups of questions: (a) services and infrastructure, (b) recreational activities, and (c) beach conditions. Cluster linkage distance ( r = 0.82, r = 0.78, r = 0.67) was used as a weight and multiplied by the value of beach descriptive factors. Mazatlán and Oceanside obtained the highest values because there are enough infrastructure and services; on the contrary, Ensenada and Rosarito were rated medium and low because infrastructure and services are lacking. The presently proposed method can contribute to improving current beach evaluations because the final score represents the beach users’ evaluation of the quality of the beach. The weight considered in the present study marks the beach users’ preferences among the studied beaches. Adding this weight to beach evaluation will contribute to more specific beach planning in which users’ perception is considered.

The contribution of cluster and discriminant analysis to the classification of complex aquifer systems.

PubMed

Panagopoulos, G P; Angelopoulou, D; Tzirtzilakis, E E; Giannoulopoulos, P

2016-10-01

This paper presents an innovated method for the discrimination of groundwater samples in common groups representing the hydrogeological units from where they have been pumped. This method proved very efficient even in areas with complex hydrogeological regimes. The proposed method requires chemical analyses of water samples only for major ions, meaning that it is applicable to most of cases worldwide. Another benefit of the method is that it gives a further insight of the aquifer hydrogeochemistry as it provides the ions that are responsible for the discrimination of the group. The procedure begins with cluster analysis of the dataset in order to classify the samples in the corresponding hydrogeological unit. The feasibility of the method is proven from the fact that the samples of volcanic origin were separated into two different clusters, namely the lava units and the pyroclastic-ignimbritic aquifer. The second step is the discriminant analysis of the data which provides the functions that distinguish the groups from each other and the most significant variables that define the hydrochemical composition of the aquifer. The whole procedure was highly successful as the 94.7 % of the samples were classified to the correct aquifer system. Finally, the resulted functions can be safely used to categorize samples of either unknown or doubtful origin improving thus the quality and the size of existing hydrochemical databases.

ALE OF TWO CLUSTERS YIELDS SECRETS OF STAR BIRTH IN THE EARLY UNIVERSE

NASA Technical Reports Server (NTRS)

2002-01-01

This NASA Hubble Space Telescope (HST) image shows rich detail, previously only seen in neighboring star birth regions, in a pair of star clusters 166,000 light-years away in the Large Magellanic Cloud (LMC), in the southern constellation Doradus. The field of view is 130 light-years across and was taken with the Wide Field Planetary Camera 2. HST's unique capabilities -- ultraviolet sensitivity, ability to see faint stars, and high resolution -- have been utilized fully to identify three separate populations in this concentration of nearly 10,000 stars down to the 25th magnitude (more that twice as many as can be seen over the entire sky with the naked eye on a clear night on Earth). The field of view is only 130 light-years across. Previous observations with ground-based telescopes resolve less than 1,000 stars in the same region. About 60 percent of the stars belong to the dominant yellow cluster called NGC 1850, which is estimated to be 50 million years old. A scattering of white stars in the image are massive stars that are only about 4 million years old and represent about 20 percent of the stars in the image. (The remainder are field stars in the LMC.) Besides being much younger, the white stars are much more loosely distributed than the yellow cluster. The significant difference between the two cluster ages suggests these are two separate star groups that lie along the same line of sight. The younger, more open cluster probably lies 200 light-years beyond the older cluster. If it were in the foreground, then dust contained in the white cluster would obscure stars in the older yellow cluster. To observe two well-defined star populations separated by such a small gap of space is unusual. This juxtaposition suggests that supernova explosions in the older cluster might have triggered the birth of the younger cluster. This color composite image is assembled from exposures taken in ultraviolet, visible, and near-infrared light. Yellow stars correspond to Main Sequence stars (like our Sun) with average surface temperatures of 6000 Kelvin; red stars are cool giants and supergiants (3500 K); white stars are hot young stars (25,000 K or more) that are bright in ultraviolet. Credit: R. Gilmozzi, Space Telescope Science Institute/European Space Agency; Shawn Ewald, JPL; and NASA

Reconstruction of sediment transport pathways in modern microtidal sand flat by multiple classification analysis

NASA Astrophysics Data System (ADS)

Yamashita, S.; Nakajo, T.; Naruse, H.

2009-12-01

In this study, we statistically classified the grain size distribution of the bottom surface sediment on a microtidal sand flat to analyze the depositional processes of the sediment. Multiple classification analysis revealed that two types of sediment populations exist in the bottom surface sediment. Then, we employed the sediment trend model developed by Gao and Collins (1992) for the estimation of sediment transport pathways. As a result, we found that statistical discrimination of the bottom surface sediment provides useful information for the sediment trend model while dealing with various types of sediment transport processes. The microtidal sand flat along the Kushida River estuary, Ise Bay, central Japan, was investigated, and 102 bottom surface sediment samples were obtained. Then, their grain size distribution patterns were measured by the settling tube method, and each grain size distribution parameter (mud and gravel contents, mean grain size, coefficient of variance (CV), skewness, kurtosis, 5, 25, 50, 75, and 95 percentile) was calculated. Here, CV is the normalized sorting value divided by the mean grain size. Two classical statistical methods—principal component analysis (PCA) and fuzzy cluster analysis—were applied. The results of PCA showed that the bottom surface sediment of the study area is mainly characterized by grain size (mean grain size and 5-95 percentile) and the CV value, indicating predominantly large absolute values of factor loadings in primal component (PC) 1. PC1 is interpreted as being indicative of the grain-size trend, in which a finer grain-size distribution indicates better size sorting. The frequency distribution of PC1 has a bimodal shape and suggests the existence of two types of sediment populations. Therefore, we applied fuzzy cluster analysis, the results of which revealed two groupings of the sediment (Cluster 1 and Cluster 2). Cluster 1 shows a lower value of PC1, indicating coarse and poorly sorted sediments. Cluster 1 sediments are distributed around the branched channel from Kushida River and show an expanding distribution from the river mouth toward the northeast direction. Cluster 2 shows a higher value of PC1, indicating fine and well-sorted sediments; this cluster is distributed in a distant area from the river mouth, including the offshore region. Therefore, Cluster 1 and Cluster 2 are interpreted as being deposited by fluvial and wave processes, respectively. Finally, on the basis of this distribution pattern, the sediment trend model was applied in areas dominated separately by fluvial and wave processes. Resultant sediment transport patterns showed good agreement with those obtained by field observations. The results of this study provide an important insight into the numerical models of sediment transport.

Preparation and analysis of particulate metal deposits

NASA Technical Reports Server (NTRS)

Poppa, H.; Moorhead, D.; Heinemann, K.

1985-01-01

Small particles and clusters of palladium were grown by deposition from the vapor phase under ultrahigh vacuum conditions. Amorphous and crystalline support films of Al2O3 and ultrathin amorphous carbon films were used as substrate materials. The growth of the metal deposit was monitored in situ by scanning transmission diffraction of energy-filtered 100 kV electrons and high resolution transmission electron microscopy (TEM) analysis was performed in a separate instrument. It was established by in situ TEM, however, that the transfer of specimens in this case did not unduly affect the size and distribution of deposit particles. It was found that the cleanness, stoichiometry, crystallinity and structural perfection of the support surface play an essential role in determining the crystalline perfection and structure of the particles. The smallest palladium clusters reproducibly prepared contained not more than six atoms but size determinations below 1 nm average particle diameter are very problematic with conventional TEM. Palladium particles grown on carbon supports feature an impurity-stabilized mosaic structure.

Configural Scoring of Simulator Sickness, Cybersickness and Space Adaptation Syndrome: Similarities and Differences?

NASA Technical Reports Server (NTRS)

Kennedy, Robert S.; Drexler, Julie M.; Compton, Daniel E.; Stanney, Kay M.; Lanham, Susan; Harm, Deborah L.

2001-01-01

From a survey of ten U.S. Navy flight simulators a large number (N > 1,600 exposures) of self-reports of motion sickness symptomatology were obtained. Using these data, scoring algorithms were derived, which permit examination of groups of individuals that can be scored either for 1) their total sickness experience in a particular device; or, 2) according to three separable symptom clusters which emerged from a Factor Analysis. Scores from this total score are found to be proportional to other global motion sickness symptom checklist scores with which they correlate (r = 0.82). The factors that surfaced from the analysis include clusters of symptoms referable as nausea, oculomotor disturbances, and disorientation (N, 0, and D). The factor scores may have utility in differentiating the source of symptoms in different devices. The present chapter describes our experience with the use of both of these types of scores and illustrates their use with examples from flight simulators, space sickness and virtual environments.

Differences in community composition of bacteria in four glaciers in western China

NASA Astrophysics Data System (ADS)

An, L. Z.; Chen, Y.; Xiang, S.-R.; Shang, T.-C.; Tian, L.-D.

2010-06-01

Microbial community patterns vary in glaciers worldwide, presenting unique responses to global climatic and environmental changes. Four bacterial clone libraries were established by 16S rRNA gene amplification from four ice layers along the 42-m-long ice core MuztB drilled from the Muztag Ata Glacier. A total of 151 bacterial sequences obtained from the ice core MuztB were phylogenetically compared with the 71 previously reported sequences from three ice cores extracted from ice caps Malan, Dunde, and Puruogangri. Six phylogenetic clusters Flavisolibacter, Flexibacter (Bacteroidetes), Acinetobacter, Enterobacter (Gammaproteobacteria), Planococcus/Anoxybacillus (Firmicutes), and Propionibacter/Luteococcus (Actinobacteria) frequently occurred along the Muztag Ata Glacier profile, and their proportion varied by seasons. Sequence analysis showed that most of the sequences from the ice core clustered with those from cold environments, and the sequence clusters from the same glacier more closely grouped together than those from the geographically isolated glaciers. Moreover, bacterial communities from the same location or similarly aged ice formed a cluster, and were clearly separate from those from other geographically isolated glaciers. In summary, the findings provide preliminary evidence of zonal distribution of microbial community, and suggest biogeography of microorganisms in glacier ice.

Differences in community composition of bacteria in four deep ice sheets in western China

NASA Astrophysics Data System (ADS)

An, L.; Chen, Y.; Xiang, S.-R.; Shang, T.-C.; Tian, L.-De

2010-02-01

Microbial community patterns vary in glaciers world wide, presenting unique responses to global climatic and environmental changes. Four bacterial clone libraries were established by 16S rRNA gene amplification from four ice layers along the 42-m-long ice core MuztB drilled from the Muztag Ata Glacier. A total of 152 bacterial sequences obtained from the ice core MuztB were phylogenetically compared with the 71 previously reported sequences from three ice cores extracted from ice caps Malan, Dunde, and Puruoganri. The six functional clusters Flavisolibacter, Flexibacter (Bacteroidetes), Acinetobacter, Enterobacter (Gammaproteobacteria), Planococcus/Anoxybacillus (Firmicutes), and Propionibacter/Luteococcus (Actinobacteria) frequently occurred along the Muztag Ata Glacier profile. Sequence analysis showed that most of the sequences from the ice core clustered with those from cold environments, and the sequences from the same glacier formed a distinct cluster. Moreover, bacterial communities from the same location or similarly aged ice formed a cluster, and were clearly separate from those from other geographically isolated glaciers. In a summary, the findings provide preliminary evidence of zone distribution of microbial community, support our hypothesis of the spatial and temporal biogeography of microorganisms in glacial ice.

Comparing interfertility data with random amplified microsatellites DNA (RAMS) studies in Ganoderma Karst. Taxonomy.

PubMed

Nudin, Nur Fatihah Hasan; S, Siddiquee

2012-03-01

The taxonomy of the causal pathogen of basal stem rot of oil palms, Ganoderma is somewhat problematic at present. In order to determine the genetic distance relationship between G. boninense isolates and non-boninense isolates, a random amplified microsatellites DNA (RAMS) technique was carried out. The result was then compared with interfertility data of G. boninense that had been determined in previous mating studies to confirm the species of G. boninense. Dendrogram from cluster analysis based on UPGMA of RAMS data showed that two major clusters, I and II which separated at a genetic distance of 0.7935 were generated. Cluster I consisted of all the biological species G. boninense isolates namely CNLB, GSDK 3, PER 71, WD 814, GBL 3, GBL 6, OC, GH 02, 170 SL and 348781 while all non-boninense isolates namely G. ASAM, WRR, TFRI 129, G. RES, GJ, and CNLM were grouped together in cluster II. Although the RAMS markers showed polymorphisms in all the isolates tested, the results obtained were in agreement with the interfertility data. Therefore, the RAMS data could support the interfertility data for the identification of Ganoderma isolates.

Earthquake Declustering via a Nearest-Neighbor Approach in Space-Time-Magnitude Domain

NASA Astrophysics Data System (ADS)

Zaliapin, I. V.; Ben-Zion, Y.

2016-12-01

We propose a new method for earthquake declustering based on nearest-neighbor analysis of earthquakes in space-time-magnitude domain. The nearest-neighbor approach was recently applied to a variety of seismological problems that validate the general utility of the technique and reveal the existence of several different robust types of earthquake clusters. Notably, it was demonstrated that clustering associated with the largest earthquakes is statistically different from that of small-to-medium events. In particular, the characteristic bimodality of the nearest-neighbor distances that helps separating clustered and background events is often violated after the largest earthquakes in their vicinity, which is dominated by triggered events. This prevents using a simple threshold between the two modes of the nearest-neighbor distance distribution for declustering. The current study resolves this problem hence extending the nearest-neighbor approach to the problem of earthquake declustering. The proposed technique is applied to seismicity of different areas in California (San Jacinto, Coso, Salton Sea, Parkfield, Ventura, Mojave, etc.), as well as to the global seismicity, to demonstrate its stability and efficiency in treating various clustering types. The results are compared with those of alternative declustering methods.

Genomic fingerprinting of virulent and avirulent strains of Clavibacter michiganensis subspecies sepedonicus.

PubMed

Brown, Susan E; Reilley, Ann A; Knudson, Dennis L; Ishimaru, Carol A

2002-02-01

Genomic fingerprints of C. michiganensis subsp. sepedonicus were generated by CHEF gel electrophoresis of restriction digested high-molecular weight DNA. Low levels of intra-subspecific variation were detected by cluster analysis of the fingerprints. Four haplotypes were identified by genomic fingerprinting with HindIII, and eight were identified with EcoRI. Haplotypes generated with HindIII were less similar than those generated by EcoRI. Haplotypes generated with HindIII formed groups that corresponded well with plant reactions of the strains, but similar types of groupings were less apparent with haplotypes generated with EcoRI. When disease severity in eggplant and potato, population size in potato, and ability to induce a hypersensitive response (HR) in tobacco were overlaid onto dendograms of genetic similarity, avirulent HR-negative strains clustered separately from virulent HR-positive strains in both EcoRI and HindIII profiles. Avirulent HR-positive strains that lack pCS1 clustered with avirulent HR-negative strains in a EcoRI dendogram, but clustered with virulent HR-positive strains in a HindIII dendogram. Genomic fingerprinting of high-molecular weight DNA fragments provided a means for detecting genomic variability associated with virulence in C. michiganensis subsp. sepedonicus.

Principles of proportional recovery after stroke generalize to neglect and aphasia.

PubMed

Marchi, N A; Ptak, R; Di Pietro, M; Schnider, A; Guggisberg, A G

2017-08-01

Motor recovery after stroke can be characterized into two different patterns. A majority of patients recover about 70% of initial impairment, whereas some patients with severe initial deficits show little or no improvement. Here, we investigated whether recovery from visuospatial neglect and aphasia is also separated into two different groups and whether similar proportions of recovery can be expected for the two cognitive functions. We assessed 35 patients with neglect and 14 patients with aphasia at 3 weeks and 3 months after stroke using standardized tests. Recovery patterns were classified with hierarchical clustering and the proportion of recovery was estimated from initial impairment using a linear regression analysis. Patients were reliably clustered into two different groups. For patients in the first cluster (n = 40), recovery followed a linear model where improvement was proportional to initial impairment and achieved 71% of maximal possible recovery for both cognitive deficits. Patients in the second cluster (n = 9) exhibited poor recovery (<25% of initial impairment). Our findings indicate that improvement from neglect or aphasia after stroke shows the same dichotomy and proportionality as observed in motor recovery. This is suggestive of common underlying principles of plasticity, which apply to motor and cognitive functions. © 2017 EAN.

Evolution of Streptococcus pneumoniae and Its Close Commensal Relatives

PubMed Central

Kilian, Mogens; Poulsen, Knud; Blomqvist, Trinelise; Håvarstein, Leiv S.; Bek-Thomsen, Malene; Tettelin, Hervé; Sørensen, Uffe B. S.

2008-01-01

Streptococcus pneumoniae is a member of the Mitis group of streptococci which, according to 16S rRNA-sequence based phylogenetic reconstruction, includes 12 species. While other species of this group are considered prototypes of commensal bacteria, S. pneumoniae is among the most frequent microbial killers worldwide. Population genetic analysis of 118 strains, supported by demonstration of a distinct cell wall carbohydrate structure and competence pheromone sequence signature, shows that S. pneumoniae is one of several hundred evolutionary lineages forming a cluster separate from Streptococcus oralis and Streptococcus infantis. The remaining lineages of this distinct cluster are commensals previously collectively referred to as Streptococcus mitis and each represent separate species by traditional taxonomic standard. Virulence genes including the operon for capsule polysaccharide synthesis and genes encoding IgA1 protease, pneumolysin, and autolysin were randomly distributed among S. mitis lineages. Estimates of the evolutionary age of the lineages, the identical location of remnants of virulence genes in the genomes of commensal strains, the pattern of genome reductions, and the proportion of unique genes and their origin support the model that the entire cluster of S. pneumoniae, S. pseudopneumoniae, and S. mitis lineages evolved from pneumococcus-like bacteria presumably pathogenic to the common immediate ancestor of hominoids. During their adaptation to a commensal life style, most of the lineages gradually lost the majority of genes determining virulence and became genetically distinct due to sexual isolation in their respective hosts. PMID:18628950

A new approach to spike sorting for multi-neuronal activities recorded with a tetrode--how ICA can be practical.

PubMed

Takahashi, Susumu; Anzai, Yuichiro; Sakurai, Yoshio

2003-07-01

Multi-neuronal recording with a tetrode is a powerful technique to reveal neuronal interactions in local circuits. However, it is difficult to detect precise spike timings among closely neighboring neurons because the spike waveforms of individual neurons overlap on the electrode when more than two neurons fire simultaneously. In addition, the spike waveforms of single neurons, especially in the presence of complex spikes, are often non-stationary. These problems limit the ability of ordinary spike sorting to sort multi-neuronal activities recorded using tetrodes into their single-neuron components. Though sorting with independent component analysis (ICA) can solve these problems, it has one serious limitation that the number of separated neurons must be less than the number of electrodes. Using a combination of ICA and the efficiency of ordinary spike sorting technique (k-means clustering), we developed an automatic procedure to solve the spike-overlapping and the non-stationarity problems with no limitation on the number of separated neurons. The results for the procedure applied to real multi-neuronal data demonstrated that some outliers which may be assigned to distinct clusters if ordinary spike-sorting methods were used can be identified as overlapping spikes, and that there are functional connections between a putative pyramidal neuron and its putative dendrite. These findings suggest that the combination of ICA and k-means clustering can provide insights into the precise nature of functional circuits among neurons, i.e. cell assemblies.

Epizoic communities of prokaryotes on healthy and diseased scleractinian corals in Lingayen Gulf, Philippines.

PubMed

Arboleda, Mark; Reichardt, Wolfgang

2009-01-01

In search for microbiological indicators of coral health and coral diseases, community profiles of coral-associated epizoic prokaryotes were investigated because of their dual potential as a source of coral pathogens and their antagonists. In pairwise samples of visually healthy and diseased coral specimens from Bolinao Bay (Pangasinan, Philippines), mixed biofilm communities of ectoderm- and mucus-colonizing epizoic prokaryotes were compared using fluorescent in situ hybridization (FISH). Oligonucleotide probes targeted 13 phylotypes representing the main taxonomic groups of marine prokaryotes. Coral taxa tended to show specific community profiles. An attempt to separate the profiles of healthy and diseased specimens by applying principal component analysis (PCA) to a (nonselective) collection of corals (affected by various diseases) proved unsuccessful. On the other hand, separate PCA clusters were obtained from healthy and diseased corals belonging to a single species (Pocillopora damicornis) only. This cluster formation was dominated by principal component 1 with the genus Vibrio accounting for 18%. At the same time, reef-site-specific clusters were formed as well. At a reef site exposed to pollution from intensive fish cage (Chanos chanos) farming, healthy P. damicornis were mainly (93%) colonized by unicellular cyanobacteria. The formal calculation of diversity parameters suggested that evenness in particular was driven by both health status and reef site location. Despite the low resolution of taxonomic levels achieved with FISH probes targeting only large phylotype groups, significant differences between healthy and diseased corals and also between polluted and nonpolluted reef sites were observed.

Descriptor Fingerprints and Their Application to WhiteWine Clustering and Discrimination.

NASA Astrophysics Data System (ADS)

Bangov, I. P.; Moskovkina, M.; Stojanov, B. P.

2018-03-01

This study continues the attempt to use the statistical process for a large-scale analytical data. A group of 3898 white wines, each with 11 analytical laboratory benchmarks was analyzed by a fingerprint similarity search in order to be grouped into separate clusters. A characterization of the wine's quality in each individual cluster was carried out according to individual laboratory parameters.

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...

Quantitative Analysis and Comparison of Four Major Flavonol Glycosides in the Leaves of Toona sinensis (A. Juss.) Roemer (Chinese Toon) from Various Origins by High-Performance Liquid Chromatography-Diode Array Detector and Hierarchical Clustering Analysis

PubMed Central

Sun, Xiaoxiang; Zhang, Liting; Cao, Yaqi; Gu, Qinying; Yang, Huan; Tam, James P.

2016-01-01

Background: Toona sinensis (A. Juss.) Roemer is an endemic species of Toona genus native to Asian area. Its dried leaves are applied in the treatment of many diseases; however, few investigations have been reported for the quantitative analysis and comparison of major bioactive flavonol glycosides in the leaves harvested from various origins. Objective: To quantitatively analyze four major flavonol glycosides including rutinoside, quercetin-3-O-β-D-glucoside, quercetin-3-O-α-L-rhamnoside, and kaempferol-3-O-α-L-rhamnoside in the leaves from different production sites and classify them according to the content of these glycosides. Materials and Methods: A high-performance liquid chromatography-diode array detector (HPLC-DAD) method for their simultaneous determination was developed and validated for linearity, precision, accuracy, stability, and repeatability. Moreover, the method established was then employed to explore the difference in the content of these four glycosides in raw materials. Finally, a hierarchical clustering analysis was performed to classify 11 voucher specimens. Results: The separation was performed on a Waters XBridge Shield RP18 column (150 mm × 4.6 mm, 3.5 μm) kept at 35°C, and acetonitrile and H2O containing 0.30% trifluoroacetic acid as mobile phase was driven at 1.0 mL/min during the analysis. Ten microliters of solution were injected and 254 nm was selected to monitor the separation. A strong linear relationship between the peak area and concentration of four analytes was observed. And, the method was also validated to be repeatable, stable, precise, and accurate. Conclusion: An efficient and reliable HPLC-DAD method was established and applied in the assays for the samples from 11 origins successfully. Moreover, the content of those flavonol glycosides varied much among different batches, and the flavonoids could be considered as biomarkers to control the quality of Chinese Toon. SUMMARY Four major flavonol glycosides in the leaves of Toona sinensis were determined by HPLC-DAD and their contents were compared among various origins by HCA. Abbreviations used: HPLC-DAD: High-performance liquid chromatography-diode array detector, HCA: Hierarchical clustering analysis, MS: Mass spectrometry, RSD: Relative standard deviation. PMID:27279719

Using Fuzzy Clustering for Real-time Space Flight Safety

NASA Technical Reports Server (NTRS)

Lee, Charles; Haskell, Richard E.; Hanna, Darrin; Alena, Richard L.

2004-01-01

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Dynamically Allocated Virtual Clustering Management System Users Guide

DTIC Science & Technology

2016-11-01

provides usage instructions for the DAVC version 2.0 web application. 15. SUBJECT TERMS DAVC, Dynamically Allocated Virtual Clustering...This report provides usage instructions for the DAVC version 2.0 web application. This report is separated into the following sections, which detail

Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis.

PubMed

Cakir, Ebru; Kucuk, Ulku; Pala, Emel Ebru; Sezer, Ozlem; Ekin, Rahmi Gokhan; Cakmak, Ozgur

2017-05-01

Conventional cytomorphologic assessment is the first step to establish an accurate diagnosis in urinary cytology. In cytologic preparations, the separation of low-grade urothelial carcinoma (LGUC) from reactive urothelial proliferation (RUP) can be exceedingly difficult. The bladder washing cytologies of 32 LGUC and 29 RUP were reviewed. The cytologic slides were examined for the presence or absence of the 28 cytologic features. The cytologic criteria showing statistical significance in LGUC were increased numbers of monotonous single (non-umbrella) cells, three-dimensional cellular papillary clusters without fibrovascular cores, irregular bordered clusters, atypical single cells, irregular nuclear overlap, cytoplasmic homogeneity, increased N/C ratio, pleomorphism, nuclear border irregularity, nuclear eccentricity, elongated nuclei, and hyperchromasia (p ˂ 0.05), and the cytologic criteria showing statistical significance in RUP were inflammatory background, mixture of small and large urothelial cells, loose monolayer aggregates, and vacuolated cytoplasm (p ˂ 0.05). When these variables were subjected to a stepwise logistic regression analysis, four features were selected to distinguish LGUC from RUP: increased numbers of monotonous single (non-umbrella) cells, increased nuclear cytoplasmic ratio, hyperchromasia, and presence of small and large urothelial cells (p = 0.0001). By this logistic model of the 32 cases with proven LGUC, the stepwise logistic regression analysis correctly predicted 31 (96.9%) patients with this diagnosis, and of the 29 patients with RUP, the logistic model correctly predicted 26 (89.7%) patients as having this disease. There are several cytologic features to separate LGUC from RUP. Stepwise logistic regression analysis is a valuable tool for determining the most useful cytologic criteria to distinguish these entities. © 2017 APMIS. Published by John Wiley & Sons Ltd.

Kinetics of motility-induced phase separation and swim pressure

NASA Astrophysics Data System (ADS)

Patch, Adam; Yllanes, David; Marchetti, M. Cristina

Active Brownian particles (ABPs) represent a minimal model of active matter consisting of self-propelled spheres with purely repulsive interactions and rotational noise. We correlate the time evolution of the mean pressure towards its steady state value with the kinetics of motility-induced phase separation. For parameter values corresponding to phase separated steady states, we identify two dynamical regimes. The pressure grows monotonically in time during the initial regime of rapid cluster formation, overshooting its steady state value and then quickly relaxing to it, and remains constant during the subsequent slower period of cluster coalescence and coarsening. The overshoot is a distinctive feature of active systems. NSF-DMR-1305184, NSF-DGE-1068780, ACI-1341006, FIS2015-65078-C02, BIFI-ZCAM.

Simulation and Implementation of a Morphology-Tuned Gold Nano-Islands Integrated Plasmonic Sensor

PubMed Central

Ozhikandathil, Jayan; Packirisamy, Muthukumaran

2014-01-01

This work presents simulation, analysis and implementation of morphology tuning of gold nano-island structures deposited by a novel convective assembly technique. The gold nano-islands were simulated using 3D Finite-Difference Time-Domain (FDTD) techniques to investigate the effect of morphological changes and adsorption of protein layers on the localized surface plasmon resonance (LSPR) properties. Gold nano-island structures were deposited on glass substrates by a novel and low-cost convective assembly process. The structure formed by an uncontrolled deposition method resulted in a nano-cluster morphology, which was annealed at various temperatures to tune the optical absorbance properties by transforming the nano-clusters to a nano-island morphology by modifying the structural shape and interparticle separation distances. The dependence of the size and the interparticle separation distance of the nano-islands on the LSPR properties were analyzed in the simulation. The effect of adsorption of protein layer on the nano-island structures was simulated and a relation between the thickness and the refractive index of the protein layer on the LSPR peak was presented. Further, the sensitivity of the gold nano-island integrated sensor against refractive index was computed and compared with the experimental results. PMID:24932868

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.

Fast ground filtering for TLS data via Scanline Density Analysis

NASA Astrophysics Data System (ADS)

Che, Erzhuo; Olsen, Michael J.

2017-07-01

Terrestrial Laser Scanning (TLS) efficiently collects 3D information based on lidar (light detection and ranging) technology. TLS has been widely used in topographic mapping, engineering surveying, forestry, industrial facilities, cultural heritage, and so on. Ground filtering is a common procedure in lidar data processing, which separates the point cloud data into ground points and non-ground points. Effective ground filtering is helpful for subsequent procedures such as segmentation, classification, and modeling. Numerous ground filtering algorithms have been developed for Airborne Laser Scanning (ALS) data. However, many of these are error prone in application to TLS data because of its different angle of view and highly variable resolution. Further, many ground filtering techniques are limited in application within challenging topography and experience difficulty coping with some objects such as short vegetation, steep slopes, and so forth. Lastly, due to the large size of point cloud data, operations such as data traversing, multiple iterations, and neighbor searching significantly affect the computation efficiency. In order to overcome these challenges, we present an efficient ground filtering method for TLS data via a Scanline Density Analysis, which is very fast because it exploits the grid structure storing TLS data. The process first separates the ground candidates, density features, and unidentified points based on an analysis of point density within each scanline. Second, a region growth using the scan pattern is performed to cluster the ground candidates and further refine the ground points (clusters). In the experiment, the effectiveness, parameter robustness, and efficiency of the proposed method is demonstrated with datasets collected from an urban scene and a natural scene, respectively.

High Prevalence of Middle East Respiratory Coronavirus in Young Dromedary Camels in Jordan.

PubMed

van Doremalen, Neeltje; Hijazeen, Zaidoun S K; Holloway, Peter; Al Omari, Bilal; McDowell, Chester; Adney, Danielle; Talafha, Hani A; Guitian, Javier; Steel, John; Amarin, Nadim; Tibbo, Markos; Abu-Basha, Ehab; Al-Majali, Ahmad M; Munster, Vincent J; Richt, Juergen A

2017-02-01

Prevalence of Middle East respiratory syndrome coronavirus (MERS-CoV) was determined in 45 dromedary camels from two geographically separated herds in Jordan. Virus shedding was only detected in swabs obtained from the respiratory tract and primarily observed in camels younger than 3 years. MERS-CoV seroprevalence increased with age of camels. Bovine and sheep sera were seronegative. Phylogenetic analysis of partial S2 clustered the Jordanian MERS-CoV strains with contemporary MERS-CoV strains associated with nosocomial outbreaks.

Defense Mechanisms in Adolescence as Predictors of Adult Personality Disorders.

PubMed

Strandholm, Thea; Kiviruusu, Olli; Karlsson, Linnea; Miettunen, Jouko; Marttunen, Mauri

2016-05-01

Our study examines whether defense styles and separate defenses in depressed adolescent outpatients predict adult personality disorders (PDs). We obtained data from consecutive adolescent outpatients who participated in the Adolescent Depression Study at baseline and at the 8-year follow-up (N = 140). Defense styles were divided into mature, neurotic, image-distorting, and immature and a secondary set of analyses were made with separate defenses as predictors of a PD diagnosis. Neurotic, image-distorting, and immature defense styles in adolescence were associated with adulthood PDs. Neurotic defense style associated with cluster B diagnosis and image-distorting defense style associated with cluster A diagnosis. Separate defenses of displacement, isolation, and reaction formation were independent predictors of adult PD diagnosis even after adjusting for PD diagnosis in adolescence. Defense styles and separate defenses predict later PDs and could be used in the focusing of treatment interventions for adolescents.

VizieR Online Data Catalog: Abell 315 spectroscopic dataset (Biviano+, 2017)

NASA Astrophysics Data System (ADS)

Biviano, A.; Popesso, P.; Dietrich, J. P.; Zhang, Y.-Y.; Erfanianfar, G.; Romaniello, M.; Sartoris, B.

2017-03-01

Abell 315 was observed at the European Southern Observatory (ESO) Very Large Telescope (VLT) with the VIsible MultiObject Spectrograph (VIMOS). The VIMOS data were acquired using 8 separate pointings, plus 2 additional pointings required to provide the needed redundancy within the central region and to cover the gaps between the VIMOS quadrants. Catalog of galaxies with redshifts in the region of the cluster Abell 315, with flags indicating whether these galaxies are members of the cluster, members of substructures within the cluster, and with probabilities for the cluster members to belong to the main cluster structure. (1 data file).

Observing Globular Cluster RR Lyrae Variables with the BYU West Mountain Observatory

NASA Astrophysics Data System (ADS)

Jeffery, E. J.; Joner, M. D.

2016-06-01

We have utilized the 0.9-meter telescope of the Brigham Young University West Mountain Observatory to secure data on six northern hemisphere globular clusters. Here we present representative observations of RR Lyrae stars located in these clusters, including light curves. We compare light curves produced using both DAOPHOT and ISIS software packages. Light curve fitting is done with FITLC. We find that for well-separated stars, DAOPHOT and ISIS provide comparable results. However, for stars within the cluster core, ISIS provides superior results. These improved techniques will allow us to better measure the properties of cluster variable stars.

A study of the tolerance block approach to special stratification. [winter wheat in Kansas

NASA Technical Reports Server (NTRS)

Richardson, W. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Twelve winter wheat LACIE segments in Kansas were used to compare the performance of three clustering methods: (1) BCLUST, which uses a spectral distance function to accumulate clusters; (2) blocks-alone, which divides spectral space into equally populated blocks; and (3) block-seeds, which uses spectral means of blocks-alone as seeds for accumulating distance-type clusters. Both BCLUST and block-seeds performed equally well and outperformed blocks-alone significantly. Their average variance ratio of about 0.5 showed imperfect separation of wheat from non-wheat. This result points to the need to explore the achievable crop separability in the spectral/temporal domain, and suggest evaluating derived features rather than data channels as a means to achieve purer spectral strata.

Blind colour separation of H&E stained histological images by linearly transforming the colour space.

PubMed

Celis, R; Romo, D; Romero, E

2015-12-01

Blind source separation methods aim to split information into the original sources. In histology, each dye component attempts to specifically characterize different microscopic structures. In the case of the hematoxylin-eosin stain, universally used for routine examination, quantitative analysis may often require the inspection of different morphological signatures related mainly to nuclei patterns, but also to stroma distribution. Stain separation is usually a preprocessing operation that is transversal to different applications. This paper presents a novel colour separation method that finds the hematoxylin and eosin clusters by projecting the whole (r,g,b) space to a folded surface connecting the distributions of a series of [(r-b),g] planes that divide the cloud of H&E tones. The proposed method produces density maps closer to those obtained with the colour mixing matrices set by an expert, when comparing with the density maps obtained using nonnegative matrix factorization (NMF), independent component analysis (ICA) and a state-of-the-art method. The method has outperformed three baseline methods, NMF, Macenko and ICA, in about 8%, 12% and 52% for the eosin component, whereas this was about 4%, 8% and 26% for the hematoxylin component. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Beluga whale, Delphinapterus leucas, vocalizations from the Churchill River, Manitoba, Canada.

PubMed

Chmelnitsky, Elly G; Ferguson, Steven H

2012-06-01

Classification of animal vocalizations is often done by a human observer using aural and visual analysis but more efficient, automated methods have also been utilized to reduce bias and increase reproducibility. Beluga whale, Delphinapterus leucas, calls were described from recordings collected in the summers of 2006-2008, in the Churchill River, Manitoba. Calls (n=706) were classified based on aural and visual analysis, and call characteristics were measured; calls were separated into 453 whistles (64.2%; 22 types), 183 pulsed∕noisy calls (25.9%; 15 types), and 70 combined calls (9.9%; seven types). Measured parameters varied within each call type but less variation existed in pulsed and noisy call types and some combined call types than in whistles. A more efficient and repeatable hierarchical clustering method was applied to 200 randomly chosen whistles using six call characteristics as variables; twelve groups were identified. Call characteristics varied less in cluster analysis groups than in whistle types described by visual and aural analysis and results were similar to the whistle contours described. This study provided the first description of beluga calls in Hudson Bay and using two methods provides more robust interpretations and an assessment of appropriate methods for future studies.

Predicting lower mantle heterogeneity from 4-D Earth models

NASA Astrophysics Data System (ADS)

Flament, Nicolas; Williams, Simon; Müller, Dietmar; Gurnis, Michael; Bower, Dan J.

2016-04-01

The Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs), approximately ˜15000 km in diameter and 500-1000 km high, located under Africa and the Pacific Ocean. The spatial stability and chemical nature of these LLSVPs are debated. Here, we compare the lower mantle structure predicted by forward global mantle flow models constrained by tectonic reconstructions (Bower et al., 2015) to an analysis of five global tomography models. In the dynamic models, spanning 230 million years, slabs subducting deep into the mantle deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour (Rayleigh number Ra), mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify a set of equally-spaced points (average separation ˜0.45°) on the Earth's surface into two groups of points with similar variations in present-day temperature between 1000-2800 km depth, for each model case. Below ˜2400 km depth, this procedure reveals a high-temperature cluster in which mantle temperature is significantly larger than ambient and a low-temperature cluster in which mantle temperature is lower than ambient. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the African and Pacific LLSVPs revealed by a similar cluster analysis of five tomography models (Lekic et al., 2012). Model success is quantified by computing the accuracy and sensitivity of the predicted temperature clusters in predicting the low-velocity cluster obtained from tomography (Lekic et al., 2012). In these cases, the accuracy varies between 0.61-0.80, where a value of 0.5 represents the random case, and the sensitivity ranges between 0.18-0.83. The largest accuracies and sensitivities are obtained for models with Ra ≈ 5 x 107, no asthenosphere (or an asthenosphere restricted to the oceanic domain), and a basal layer ˜ 4% denser than ambient mantle. Increasing convective vigour (Ra ≈ 5 x 108) or decreasing the density of the basal layer decreases both the accuracy and sensitivity of the predicted lower mantle structure. References: D. J. Bower, M. Gurnis, N. Flament, Assimilating lithosphere and slab history in 4-D Earth models. Phys. Earth Planet. Inter. 238, 8-22 (2015). V. Lekic, S. Cottaar, A. Dziewonski, B. Romanowicz, Cluster analysis of global lower mantle tomography: A new class of structure and implications for chemical heterogeneity. Earth Planet. Sci. Lett. 357, 68-77 (2012).

Restless 5S: the re-arrangement(s) and evolution of the nuclear ribosomal DNA in land plants.

PubMed

Wicke, Susann; Costa, Andrea; Muñoz, Jesùs; Quandt, Dietmar

2011-11-01

Among eukaryotes two types of nuclear ribosomal DNA (nrDNA) organization have been observed. Either all components, i.e. the small ribosomal subunit, 5.8S, large ribosomal subunit, and 5S occur tandemly arranged or the 5S rDNA forms a separate cluster of its own. Generalizations based on data derived from just a few model organisms have led to a superimposition of structural and evolutionary traits to the entire plant kingdom asserting that plants generally possess separate arrays. This study reveals that plant nrDNA organization into separate arrays is not a distinctive feature, but rather assignable almost solely to seed plants. We show that early diverging land plants and presumably streptophyte algae share a co-localization of all rRNA genes within one repeat unit. This raises the possibility that the state of rDNA gene co-localization had occurred in their common ancestor. Separate rDNA arrays were identified for all basal seed plants and water ferns, implying at least two independent 5S rDNA transposition events during land plant evolution. Screening for 5S derived Cassandra transposable elements which might have played a role during the transposition events, indicated that this retrotransposon is absent in early diverging vascular plants including early fern lineages. Thus, Cassandra can be rejected as a primary mechanism for 5S rDNA transposition in water ferns. However, the evolution of Cassandra and other eukaryotic 5S derived elements might have been a side effect of the 5S rDNA cluster formation. Structural analysis of the intergenic spacers of the ribosomal clusters revealed that transposition events partially affect spacer regions and suggests a slightly different transcription regulation of 5S rDNA in early land plants. 5S rDNA upstream regulatory elements are highly divergent or absent from the LSU-5S spacers of most early divergent land plant lineages. Several putative scenarios and mechanisms involved in the concerted relocation of hundreds of 5S rRNA gene copies are discussed. Copyright © 2011 Elsevier Inc. All rights reserved.

AFLP analysis of Cynodon dactylon (L.) Pers. var. dactylon genetic variation.

PubMed

Wu, Y Q; Taliaferro, C M; Bai, G H; Anderson, M P

2004-08-01

Cynodon dactylon (L.) Pers. var. dactylon (common bermudagrass) is geographically widely distributed between about lat 45 degrees N and lat 45 degrees S, penetrating to about lat 53 degrees N in Europe. The extensive variation of morphological and adaptive characteristics of the taxon is substantially documented, but information is lacking on DNA molecular variation in geographically disparate forms. Accordingly, this study was conducted to assess molecular genetic variation and genetic relatedness among 28 C. dactylon var. dactylon accessions originating from 11 countries on 4 continents (Africa, Asia, Australia, and Europe). A fluorescence-labeled amplified fragment length polymorphism (AFLP) DNA profiling method was used to detect the genetic diversity and relatedness. On the basis of 443 polymorphic AFLP fragments from 8 primer combinations, the accessions were grouped into clusters and subclusters associating with their geographic origins. Genetic similarity coefficients (SC) for the 28 accessions ranged from 0.53 to 0.98. Accessions originating from Africa, Australia, Asia, and Europe formed major groupings as indicated by cluster and principal coordinate analysis. Accessions from Australia and Asia, though separately clustered, were relatively closely related and most distantly related to accessions of European origin. African accessions formed two distant clusters and had the greatest variation in genetic relatedness relative to accessions from other geographic regions. Sampling the full extent of genetic variation in C. dactylon var. dactylon would require extensive germplasm collection in the major geographic regions of its distributional range.

Lipopolysaccharide biosynthesis genes discriminate between Rubus- and Spiraeoideae-infective genotypes of Erwinia amylovora.

PubMed

Rezzonico, Fabio; Braun-Kiewnick, Andrea; Mann, Rachel A; Rodoni, Brendan; Goesmann, Alexander; Duffy, Brion; Smits, Theo H M

2012-10-01

Comparative genomic analysis revealed differences in the lipopolysaccharide (LPS) biosynthesis gene cluster between the Rubus-infecting strain ATCC BAA-2158 and the Spiraeoideae-infecting strain CFBP 1430 of Erwinia amylovora. These differences corroborate rpoB-based phylogenetic clustering of E. amylovora into four different groups and enable the discrimination of Spiraeoideae- and Rubus-infecting strains. The structure of the differences between the two groups supports the hypothesis that adaptation to Rubus spp. took place after species separation of E. amylovora and E. pyrifoliae that contrasts with a recently proposed scenario, based on CRISPR data, in which the shift to domesticated apple would have caused an evolutionary bottleneck in the Spiraeoideae-infecting strains of E. amylovora which would be a much earlier event. In the core region of the LPS biosynthetic gene cluster, Spiraeoideae-infecting strains encode three glycosyltransferases and an LPS ligase (Spiraeoideae-type waaL), whereas Rubus-infecting strains encode two glycosyltransferases and a different LPS ligase (Rubus-type waaL). These coding domains share little to no homology at the amino acid level between Rubus- and Spiraeoideae-infecting strains, and this genotypic difference was confirmed by polymerase chain reaction analysis of the associated DNA region in 31 Rubus- and Spiraeoideae-infecting strains. The LPS biosynthesis gene cluster may thus be used as a molecular marker to distinguish between Rubus- and Spiraeoideae-infecting strains of E. amylovora using primers designed in this study. © 2012 THE AUTHORS. MOLECULAR PLANT PATHOLOGY © 2012 BSPP AND BLACKWELL PUBLISHING LTD.

Live-cell superresolution microscopy reveals the organization of RNA polymerase in the bacterial nucleoid

PubMed Central

Stracy, Mathew; Lesterlin, Christian; Garza de Leon, Federico; Uphoff, Stephan; Zawadzki, Pawel; Kapanidis, Achillefs N.

2015-01-01

Despite the fundamental importance of transcription, a comprehensive analysis of RNA polymerase (RNAP) behavior and its role in the nucleoid organization in vivo is lacking. Here, we used superresolution microscopy to study the localization and dynamics of the transcription machinery and DNA in live bacterial cells, at both the single-molecule and the population level. We used photoactivated single-molecule tracking to discriminate between mobile RNAPs and RNAPs specifically bound to DNA, either on promoters or transcribed genes. Mobile RNAPs can explore the whole nucleoid while searching for promoters, and spend 85% of their search time in nonspecific interactions with DNA. On the other hand, the distribution of specifically bound RNAPs shows that low levels of transcription can occur throughout the nucleoid. Further, clustering analysis and 3D structured illumination microscopy (SIM) show that dense clusters of transcribing RNAPs form almost exclusively at the nucleoid periphery. Treatment with rifampicin shows that active transcription is necessary for maintaining this spatial organization. In faster growth conditions, the fraction of transcribing RNAPs increases, as well as their clustering. Under these conditions, we observed dramatic phase separation between the densest clusters of RNAPs and the densest regions of the nucleoid. These findings show that transcription can cause spatial reorganization of the nucleoid, with movement of gene loci out of the bulk of DNA as levels of transcription increase. This work provides a global view of the organization of RNA polymerase and transcription in living cells. PMID:26224838

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®

The Formation of Galaxies and Clusters.

ERIC Educational Resources Information Center

Gregory, Stephen; Morrison, Nancy D.

1985-01-01

Summarizes recent research on the formation of galaxies and clusters, focusing on research examining how the materials in galaxies seen today separated from the universal expansion and collapsed into stable bodies. A list of six nontechnical books and articles for readers with less background is included. (JN)

Genotypic Diversity of Phytophthora cinnamomi and P. plurivora in Maryland's Nurseries and Mid-Atlantic Forests.

PubMed

Beaulieu, Justine; Ford, Blaine; Balci, Yilmaz

2017-06-01

Genetic diversity of two Phytophthora spp.-P. cinnamomi (102 isolates), commonly encountered in Maryland nurseries and forests in the Mid-Atlantic United States, and P. plurivora (186 isolates), a species common in nurseries-was characterized using amplified fragment length polymorphism. Expected heterozygosity and other indices suggested a lower level of diversity among P. cinnamomi than P. plurivora isolates. Hierarchical clustering showed P. cinnamomi isolates separated into four clusters, and two of the largest clusters were closely related, containing 80% of the isolates. In contrast, P. plurivora isolates separated into six clusters, one of which included approximately 40% of the isolates. P. plurivora isolates recovered from the environment (e.g., soil and water) were genotypically more diverse than those found causing lesions. For both species, isolate origin (forest versus nursery or among nurseries) was a significant factor of heterozygosity. Clonal groups existed within P. cinnamomi and P. plurivora and included isolates from both forest and nurseries, suggesting that a pathway from nurseries to forests or vice versa exists.

A method for determining the radius of an open cluster from stellar proper motions

NASA Astrophysics Data System (ADS)

Sánchez, Néstor; Alfaro, Emilio J.; López-Martínez, Fátima

2018-04-01

We propose a method for calculating the radius of an open cluster in an objective way from an astrometric catalogue containing, at least, positions and proper motions. It uses the minimum spanning tree in the proper motion space to discriminate cluster stars from field stars and it quantifies the strength of the cluster-field separation by means of a statistical parameter defined for the first time in this paper. This is done for a range of different sampling radii from where the cluster radius is obtained as the size at which the best cluster-field separation is achieved. The novelty of this strategy is that the cluster radius is obtained independently of how its stars are spatially distributed. We test the reliability and robustness of the method with both simulated and real data from a well-studied open cluster (NGC 188), and apply it to UCAC4 data for five other open clusters with different catalogued radius values. NGC 188, NGC 1647, NGC 6603, and Ruprecht 155 yielded unambiguous radius values of 15.2 ± 1.8, 29.4 ± 3.4, 4.2 ± 1.7, and 7.0 ± 0.3 arcmin, respectively. ASCC 19 and Collinder 471 showed more than one possible solution, but it is not possible to know whether this is due to the involved uncertainties or due to the presence of complex patterns in their proper motion distributions, something that could be inherent to the physical object or due to the way in which the catalogue was sampled.

Evaluation of the separation characteristics of application-specific (volatile organic compounds) open-tubular columns for gas chromatography.

PubMed

Poole, Colin F; Qian, Jing; Kiridena, Waruna; Dekay, Colleen; Koziol, Wladyslaw W

2006-11-17

The solvation parameter model is used to characterize the separation characteristics of two application-specific open-tubular columns (Rtx-Volatiles and Rtx-VGC) and a general purpose column for the separation of volatile organic compounds (DB-WAXetr) at five equally spaced temperatures over the range 60-140 degrees C. System constant differences and retention factor correlation plots are then used to determine selectivity differences between the above columns and their closest neighbors in a large database of system constants and retention factors for forty-four open-tubular columns. The Rtx-Volatiles column is shown to have separation characteristics predicted for a poly(dimethyldiphenylsiloxane) stationary phase containing about 16% diphenylsiloxane monomer. The Rtx-VGC column has separation properties similar to the poly(cyanopropylphenyldimethylsiloxane) stationary phase containing 14% cyanopropylphenylsiloxane monomer DB-1701 for non-polar and dipolar/polarizable compounds but significantly different characteristics for the separation of hydrogen-bond acids. For all practical purposes the DB-WAXetr column is shown to be selectivity equivalent to poly(ethylene glycol) columns prepared using different chemistries for bonding and immobilizing the stationary phase. Principal component analysis and cluster analysis are then used to classify the system constants for the above columns and a sub-database of eleven open-tubular columns (DB-1, HP-5, DB-VRX, Rtx-20, DB-35, Rtx-50, Rtx-65, DB-1301, DB-1701, DB-200, and DB-624) commonly used for the separation of volatile organic compounds. A rationale basis for column selection based on differences in intermolecular interactions is presented as an aid to method development for the separation of volatile organic compounds.

Analysis of genetic relationships and identification of lily cultivars based on inter-simple sequence repeat markers.

PubMed

Cui, G F; Wu, L F; Wang, X N; Jia, W J; Duan, Q; Ma, L L; Jiang, Y L; Wang, J H

2014-07-29

Inter-simple sequence repeat (ISSR) markers were used to discriminate 62 lily cultivars of 5 hybrid series. Eight ISSR primers generated 104 bands in total, which all showed 100% polymorphism, and an average of 13 bands were amplified by each primer. Two software packages, POPGENE 1.32 and NTSYSpc 2.1, were used to analyze the data matrix. Our results showed that the observed number of alleles (NA), effective number of alleles (NE), Nei's genetic diversity (H), and Shannon's information index (I) were 1.9630, 1.4179, 0.2606, and 0.4080, respectively. The highest genetic similarity (0.9601) was observed between the Oriental x Trumpet and Oriental lilies, which indicated that the two hybrids had a close genetic relationship. An unweighted pair-group method with arithmetic means dendrogram showed that the 62 lily cultivars clustered into two discrete groups. The first group included the Oriental and OT cultivars, while the Asiatic, LA, and Longiflorum lilies were placed in the second cluster. The distribution of individuals in the principal component analysis was consistent with the clustering of the dendrogram. Fingerprints of all lily cultivars built from 8 primers could be separated completely. This study confirmed the effect and efficiency of ISSR identification in lily cultivars.

A relational structure of voluntary visual-attention abilities

PubMed Central

Skogsberg, KatieAnn; Grabowecky, Marcia; Wilt, Joshua; Revelle, William; Iordanescu, Lucica; Suzuki, Satoru

2015-01-01

Many studies have examined attention mechanisms involved in specific behavioral tasks (e.g., search, tracking, distractor inhibition). However, relatively little is known about the relationships among those attention mechanisms. Is there a fundamental attention faculty that makes a person superior or inferior at most types of attention tasks, or do relatively independent processes mediate different attention skills? We focused on individual differences in voluntary visual-attention abilities using a battery of eleven representative tasks. An application of parallel analysis, hierarchical-cluster analysis, and multidimensional scaling to the inter-task correlation matrix revealed four functional clusters, representing spatiotemporal attention, global attention, transient attention, and sustained attention, organized along two dimensions, one contrasting spatiotemporal and global attention and the other contrasting transient and sustained attention. Comparison with the neuroscience literature suggests that the spatiotemporal-global dimension corresponds to the dorsal frontoparietal circuit and the transient-sustained dimension corresponds to the ventral frontoparietal circuit, with distinct sub-regions mediating the separate clusters within each dimension. We also obtained highly specific patterns of gender difference, and of deficits for college students with elevated ADHD traits. These group differences suggest that different mechanisms of voluntary visual attention can be selectively strengthened or weakened based on genetic, experiential, and/or pathological factors. PMID:25867505

Anatomy of a Merger: A Deep Chandra Observation of Abell 115

NASA Astrophysics Data System (ADS)

Forman, William R.

2017-08-01

A deep Chandra observation of Abell 115 provides a unique probe of the anatomy of cluster mergers. The X-ray image shows two prominent subclusters, A115N (north) and A115S (south) with a projected separation of almost 1 Mpc. The X-ray subclusters each have ram-pressure stripped tails that unambiguously indicate the directions of motion. The central BCG of A115N hosts the radio source 3C28 which shows a pair of jets, almost perpendicular to the direction of the sucluster's motion. The jets terminate in lobes each of which has a "tail" pointing IN the direction of motion of the subcluster. The Chandra analysis provides details of the merger including the velocities of the subclusters both through analysis of the cold front and a weak shock. The motion of A115N through the cluster generates counter-rotating vortices in the subcluster gas that form the two radio tails. Hydrodynamic modeling yields circulation velocities within the A115N sub cluster. Thus, the radio emitting plasma acts as a dye tracing the motions of the X-ray emitting plasma. A115S shows two "cores", one coincident with the BCG and a second appears as a ram pressure stripped tail.

Skill and Working Memory.

DTIC Science & Technology

1982-04-30

clusters of rooms or areas. The fairly localized property of architectural patterns at the lowest level in the hierarchy is reminiscent of the localized...three digits. We have termed these clusters of groups "supergroups". Finally, when these supergroups became too large (more than 4 or 5 groups), SF...Supergroups -.> Clusters of Supergroups. Insert Figure 4 about here .... .... o.... In another study, run separately on SF and DD, after an hour’s

Low Divergence of Clonorchis sinensis in China Based on Multilocus Analysis

PubMed Central

Sun, Jiufeng; Huang, Yan; Huang, Huaiqiu; Liang, Pei; Wang, Xiaoyun; Mao, Qiang; Men, Jingtao; Chen, Wenjun; Deng, Chuanhuan; Zhou, Chenhui; Lv, Xiaoli; Zhou, Juanjuan; Zhang, Fan; Li, Ran; Tian, Yanli; Lei, Huali; Liang, Chi; Hu, Xuchu; Xu, Jin; Li, Xuerong; XinbingYu

2013-01-01

Clonorchis sinensis, an ancient parasite that infects a number of piscivorous mammals, attracts significant public health interest due to zoonotic exposure risks in Asia. The available studies are insufficient to reflect the prevalence, geographic distribution, and intraspecific genetic diversity of C. sinensis in endemic areas. Here, a multilocus analysis based on eight genes (ITS1, act, tub, ef-1a, cox1, cox3, nad4 and nad5 [4.986 kb]) was employed to explore the intra-species genetic construction of C. sinensis in China. Two hundred and fifty-six C. sinensis isolates were obtained from environmental reservoirs from 17 provinces of China. A total of 254 recognized Multilocus Types (MSTs) showed high diversity among these isolates using multilocus analysis. The comparison analysis of nuclear and mitochondrial phylogeny supports separate clusters in a nuclear dendrogram. Genetic differentiation analysis of three clusters (A, B, and C) showed low divergence within populations. Most isolates from clusters B and C are geographically limited to central China, while cluster A is extraordinarily genetically diverse. Further genetic analyses between different geographic distributions, water bodies and hosts support the low population divergence. The latter haplotype analyses were consistent with the phylogenetic and genetic differentiation results. A recombination network based on concatenated sequences showed a concentrated linkage recombination population in cox1, cox3, nad4 and nad5, with spatial structuring in ITS1. Coupled with the history record and archaeological evidence of C. sinensis infection in mummified desiccated feces, these data point to an ancient origin of C. sinensis in China. In conclusion, we present a likely phylogenetic structure of the C. sinensis population in mainland China, highlighting its possible tendency for biogeographic expansion. Meanwhile, ITS1 was found to be an effective marker for tracking C. sinensis infection worldwide. Thus, the present study improves our understanding of the global epidemiology and evolution of C. sinensis. PMID:23825605

Understanding Genetic Diversity and Population Structure of a Poa pratensis Worldwide Collection through Morphological, Nuclear and Chloroplast Diversity Analysis

PubMed Central

Russi, Luigi; Marconi, Gianpiero; Sharbel, Timothy F.; Veronesi, Fabio; Albertini, Emidio

2015-01-01

Poa pratensis L. is a forage and turf grass species well adapted to a wide range of mesic to moist habitats. Due to its genome complexity little is known regarding evolution, genome composition and intraspecific phylogenetic relationships of this species. In the present study we investigated the morphological and genetic diversity of 33 P. pratensis accessions from 23 different countries using both nuclear and chloroplast molecular markers as well as flow cytometry of somatic tissues. This with the aim of shedding light on the genetic diversity and phylogenetic relationships of the collection that includes both cultivated and wild materials. Morphological characterization showed that the most relevant traits able to distinguish cultivated from wild forms were spring growth habit and leaf colour. The genome size analysis revealed high variability both within and between accessions in both wild and cultivated materials. The sequence analysis of the trnL-F chloroplast region revealed a low polymorphism level that could be the result of the complex mode of reproduction of this species. In addition, a strong reduction of chloroplast SSR variability was detected in cultivated materials, where only two alleles were conserved out of the four present in wild accessions. Contrarily, at nuclear level, high variability exist in the collection where the analysis of 11 SSR loci allowed the detection of a total of 91 different alleles. A Bayesian analysis performed on nuclear SSR data revealed that studied materials belong to two main clusters. While wild materials are equally represented in both clusters, the domesticated forms are mostly belonging to cluster P2 which is characterized by lower genetic diversity compared to the cluster P1. In the Neighbour Joining tree no clear distinction was found between accessions with the exception of those from China and Mongolia that were clearly separated from all the others. PMID:25893249

SU-F-R-33: Can CT and CBCT Be Used Simultaneously for Radiomics Analysis

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

Luo, R; Wang, J; Zhong, H

2016-06-15

Purpose: To investigate whether CBCT and CT can be used in radiomics analysis simultaneously. To establish a batch correction method for radiomics in two similar image modalities. Methods: Four sites including rectum, bladder, femoral head and lung were considered as region of interest (ROI) in this study. For each site, 10 treatment planning CT images were collected. And 10 CBCT images which came from same site of same patient were acquired at first radiotherapy fraction. 253 radiomics features, which were selected by our test-retest study at rectum cancer CT (ICC>0.8), were calculated for both CBCT and CT images in MATLAB.more » Simple scaling (z-score) and nonlinear correction methods were applied to the CBCT radiomics features. The Pearson Correlation Coefficient was calculated to analyze the correlation between radiomics features of CT and CBCT images before and after correction. Cluster analysis of mixed data (for each site, 5 CT and 5 CBCT data are randomly selected) was implemented to validate the feasibility to merge radiomics data from CBCT and CT. The consistency of clustering result and site grouping was verified by a chi-square test for different datasets respectively. Results: For simple scaling, 234 of the 253 features have correlation coefficient ρ>0.8 among which 154 features haveρ>0.9 . For radiomics data after nonlinear correction, 240 of the 253 features have ρ>0.8 among which 220 features have ρ>0.9. Cluster analysis of mixed data shows that data of four sites was almost precisely separated for simple scaling(p=1.29 * 10{sup −7}, χ{sup 2} test) and nonlinear correction (p=5.98 * 10{sup −7}, χ{sup 2} test), which is similar to the cluster result of CT data (p=4.52 * 10{sup −8}, χ{sup 2} test). Conclusion: Radiomics data from CBCT can be merged with those from CT by simple scaling or nonlinear correction for radiomics analysis.« less

The Network Structure of Human Personality According to the NEO-PI-R: Matching Network Community Structure to Factor Structure

PubMed Central

Goekoop, Rutger; Goekoop, Jaap G.; Scholte, H. Steven

2012-01-01

Introduction Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. Aim To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). Methods 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. Results At facet level, NCS showed a best match (96.2%) with a ‘confirmatory’ 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with ‘confirmatory’ 5-FS and ‘exploratory’ 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. Conclusion We present the first optimized network graph of personality traits according to the NEO-PI-R: a ‘Personality Web’. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network. PMID:23284713

The network structure of human personality according to the NEO-PI-R: matching network community structure to factor structure.

PubMed

Goekoop, Rutger; Goekoop, Jaap G; Scholte, H Steven

2012-01-01

Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. At facet level, NCS showed a best match (96.2%) with a 'confirmatory' 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with 'confirmatory' 5-FS and 'exploratory' 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. We present the first optimized network graph of personality traits according to the NEO-PI-R: a 'Personality Web'. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network.

Cluster analyses of 20th century growth patterns in high elevation Great Basin bristlecone pine in the Snake Mountain Range, Nevada, USA

NASA Astrophysics Data System (ADS)

Tran, T. J.; Bruening, J. M.; Bunn, A. G.; Salzer, M. W.; Weiss, S. B.

2015-12-01

Great Basin bristlecone pine (Pinus longaeva) is a useful climate proxy because of the species' long lifespan (up to 5000 years) and the climatic sensitivity of its annually-resolved rings. Past studies have shown that growth of individual trees can be limited by temperature, soil moisture, or a combination of the two depending on biophysical setting at the scale of tens of meters. We extend recent research suggesting that trees vary in their growth response depending on their position on the landscape to analyze how growth patterns vary over time. We used hierarchical cluster analysis to examine the growth of 52 bristlecone pine trees near the treeline of Mount Washington, Nevada, USA. We classified growth of individual trees over the instrumental climate record into one of two possible scenarios: trees belonging to a temperature-sensitive cluster and trees belonging to a precipitation-sensitive cluster. The number of trees in the precipitation-sensitive cluster outnumbered the number of trees in the temperature-sensitive cluster, with trees in colder locations belonging to the temperature-sensitive cluster. When we separated the temporal range into two sections (1895-1949 and 1950-2002) spanning the length of the instrumental climate record, we found that most of the 52 trees remained loyal to their cluster membership (e.g., trees in the temperature-sensitive cluster in 1895-1949 were also in the temperature sensitive cluster in 1950-2002), though not without exception. Of those trees that do not remain consistent in cluster membership, the majority changed from temperature-sensitive to precipitation-sensitive as time progressed. This could signal a switch from temperature limitation to water limitation with warming climate. We speculate that topographic complexity in high mountain environments like Mount Washington might allow for climate refugia where growth response could remain constant over the Holocene.

An Intercomparison Between Radar Reflectivity and the IR Cloud Classification Technique for the TOGA-COARE Area

NASA Technical Reports Server (NTRS)

Carvalho, L. M. V.; Rickenbach, T.

1999-01-01

Satellite infrared (IR) and visible (VIS) images from the Tropical Ocean Global Atmosphere - Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) experiment are investigated through the use of Clustering Analysis. The clusters are obtained from the values of IR and VIS counts and the local variance for both channels. The clustering procedure is based on the standardized histogram of each variable obtained from 179 pairs of images. A new approach to classify high clouds using only IR and the clustering technique is proposed. This method allows the separation of the enhanced convection in two main classes: convective tops, more closely related to the most active core of the storm, and convective systems, which produce regions of merged, thick anvil clouds. The resulting classification of different portions of cloudiness is compared to the radar reflectivity field for intensive events. Convective Systems and Convective Tops are followed during their life cycle using the IR clustering method. The areal coverage of precipitation and features related to convective and stratiform rain is obtained from the radar for each stage of the evolving Mesoscale Convective Systems (MCS). In order to compare the IR clustering method with a simple threshold technique, two IR thresholds (Tir) were used to identify different portions of cloudiness, Tir=240K which roughly defines the extent of all cloudiness associated with the MCS, and Tir=220K which indicates the presence of deep convection. It is shown that the IR clustering technique can be used as a simple alternative to identify the actual portion of convective and stratiform rainfall.

New Asteroseismic Scaling Relations Based on the Hayashi Track Relation Applied to Red Giant Branch Stars in NGC 6791 and NGC 6819

NASA Astrophysics Data System (ADS)

Wu, T.; Li, Y.; Hekker, S.

2014-01-01

Stellar mass M, radius R, and gravity g are important basic parameters in stellar physics. Accurate values for these parameters can be obtained from the gravitational interaction between stars in multiple systems or from asteroseismology. Stars in a cluster are thought to be formed coevally from the same interstellar cloud of gas and dust. The cluster members are therefore expected to have some properties in common. These common properties strengthen our ability to constrain stellar models and asteroseismically derived M, R, and g when tested against an ensemble of cluster stars. Here we derive new scaling relations based on a relation for stars on the Hayashi track (\\sqrt{T_eff} \\sim g^pR^q) to determine the masses and metallicities of red giant branch stars in open clusters NGC 6791 and NGC 6819 from the global oscillation parameters Δν (the large frequency separation) and νmax (frequency of maximum oscillation power). The Δν and νmax values are derived from Kepler observations. From the analysis of these new relations we derive: (1) direct observational evidence that the masses of red giant branch stars in a cluster are the same within their uncertainties, (2) new methods to derive M and z of the cluster in a self-consistent way from Δν and νmax, with lower intrinsic uncertainties, and (3) the mass dependence in the Δν - νmax relation for red giant branch stars.

Suicide methods in children and adolescents.

PubMed

Kõlves, Kairi; de Leo, Diego

2017-02-01

There are notable differences in suicide methods between countries. The aim of this paper is to analyse and describe suicide methods in children and adolescents aged 10-19 years in different countries/territories worldwide. Suicide data by ICD-10 X codes were obtained from the WHO Mortality Database and population data from the World Bank. In total, 101 countries or territories, have data at least for 5 years in 2000-2009. Cluster analysis by suicide methods was performed for countries/territories with at least 10 suicide cases separately by gender (74 for males and 71 for females) in 2000-2009. The most frequent suicide method was hanging, followed by poisoning by pesticides for females and firearms for males. Cluster analyses of similarities in the country/territory level suicide method patterns by gender identified four clusters for both gender. Hanging and poisoning by pesticides defined the clusters of countries/territories by their suicide patterns in youth for both genders. In addition, a mixed method and a jumping from height cluster were identified for females and two mixed method clusters for males. A number of geographical similarities were observed. Overall, the patterns of suicide methods in children and adolescents reflect lethality, availability and acceptability of suicide means similarly to country specific patterns of all ages. Means restriction has very good potential in preventing youth suicides in different countries. It is also crucial to consider cognitive availability influenced by sensationalised media reporting and/or provision of technical details about specific methods.

An insight into the distribution, genetic diversity, and mycotoxin production of Aspergillus section Flavi in soils of pistachio orchards.

PubMed

Jamali, Mojdeh; Ebrahimi, Mohammad-Ali; Karimipour, Morteza; Shams-Ghahfarokhi, Masoomeh; Dinparast-Djadid, Navid; Kalantari, Sanaz; Pilehvar-Soltanahmadi, Yones; Amani, Akram; Razzaghi-Abyaneh, Mehdi

2012-01-01

In the present study, 193 Aspergillus strains were isolated from a total of 100 soil samples of pistachio orchards, which all of them were identified as Aspergillus flavus as the most abundant species of Aspergillus section Flavi existing in the environment. Approximately 59%, 81%, and 61% of the isolates were capable of producing aflatoxins (AFs), cyclopiazonic acid (CPA), and sclerotia, respectively. The isolates were classified into four chemotypes (I to IV) based on the ability to produce AFs and CPA. The resulting dendrogram of random amplified polymorphic DNA (RAPD) analysis of 24 selected A. flavus isolates demonstrated the formation of two separate clusters. Cluster 1 contained both aflatoxigenic and non-aflatoxigenic isolates (17 isolates), whereas cluster 2 comprised only aflatoxigenic isolates (7 isolates). All the isolates of cluster 2 produced significantly higher levels of AFs than those of cluster 1 and the isolates that produced both AFB(1) and AFB(2) were found only in cluster 2. RAPD genotyping allowed the differentiation of A. flavus from Aspergillus parasiticus as a closely related species within section Flavi. The present study has provided for the first time the relevant information on distribution and genetic diversity of different A. flavus populations from nontoxigenic to highly toxigenic enable to produce hazardous amounts of AFB(1) and CPA in soils of pistachio orchards. These fungi, either toxigenic or not-toxigenic, should be considered as potential threats for agriculture and public health.

Comparing Dark Energy Survey and HST –CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

DOE PAGES

Palmese, A.; Lahav, O.; Banerji, M.; ...

2016-08-20

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (5 filters) with those from the Hubble Space Telescope CLASH (17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25% of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensing studies with DES and CLASH. An analysismore » of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f*=7.0+-2.2x10^-3 within a radius of r_200c~3 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both datasets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the ~100 000 clusters that will be observed within this survey. The stacking of all the DES clusters would reduce the errors on f* estimates and deduce important information about galaxy evolution.« less

Comparing Dark Energy Survey and HST –CLASH observations of the galaxy cluster RXC J2248.7-4431: implications for stellar mass versus dark matter

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

Palmese, A.; Lahav, O.; Banerji, M.

We derive the stellar mass fraction in the galaxy cluster RXC J2248.7-4431 observed with the Dark Energy Survey (DES) during the Science Verification period. We compare the stellar mass results from DES (5 filters) with those from the Hubble Space Telescope CLASH (17 filters). When the cluster spectroscopic redshift is assumed, we show that stellar masses from DES can be estimated within 25% of CLASH values. We compute the stellar mass contribution coming from red and blue galaxies, and study the relation between stellar mass and the underlying dark matter using weak lensing studies with DES and CLASH. An analysismore » of the radial profiles of the DES total and stellar mass yields a stellar-to-total fraction of f*=7.0+-2.2x10^-3 within a radius of r_200c~3 Mpc. Our analysis also includes a comparison of photometric redshifts and star/galaxy separation efficiency for both datasets. We conclude that space-based small field imaging can be used to calibrate the galaxy properties in DES for the much wider field of view. The technique developed to derive the stellar mass fraction in galaxy clusters can be applied to the ~100 000 clusters that will be observed within this survey. The stacking of all the DES clusters would reduce the errors on f* estimates and deduce important information about galaxy evolution.« less

Model-free data analysis for source separation based on Non-Negative Matrix Factorization and k-means clustering (NMFk)

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Alexandrov, B.

2014-12-01

The identification of the physical sources causing spatial and temporal fluctuations of state variables such as river stage levels and aquifer hydraulic heads is challenging. The fluctuations can be caused by variations in natural and anthropogenic sources such as precipitation events, infiltration, groundwater pumping, barometric pressures, etc. The source identification and separation can be crucial for conceptualization of the hydrological conditions and characterization of system properties. If the original signals that cause the observed state-variable transients can be successfully "unmixed", decoupled physics models may then be applied to analyze the propagation of each signal independently. We propose a new model-free inverse analysis of transient data based on Non-negative Matrix Factorization (NMF) method for Blind Source Separation (BSS) coupled with k-means clustering algorithm, which we call NMFk. NMFk is capable of identifying a set of unique sources from a set of experimentally measured mixed signals, without any information about the sources, their transients, and the physical mechanisms and properties controlling the signal propagation through the system. A classical BSS conundrum is the so-called "cocktail-party" problem where several microphones are recording the sounds in a ballroom (music, conversations, noise, etc.). Each of the microphones is recording a mixture of the sounds. The goal of BSS is to "unmix'" and reconstruct the original sounds from the microphone records. Similarly to the "cocktail-party" problem, our model-freee analysis only requires information about state-variable transients at a number of observation points, m, where m > r, and r is the number of unknown unique sources causing the observed fluctuations. We apply the analysis on a dataset from the Los Alamos National Laboratory (LANL) site. We identify and estimate the impact and sources are barometric pressure and water-supply pumping effects. We also estimate the location of the water-supply pumping wells based on the available data. The possible applications of the NMFk algorithm are not limited to hydrology problems; NMFk can be applied to any problem where temporal system behavior is observed at multiple locations and an unknown number of physical sources are causing these fluctuations.

American and German attitudes towards cow-calf separation on dairy farms

PubMed Central

Busch, Gesa; Weary, Daniel M.; Spiller, Achim; von Keyserlingk, Marina A. G.

2017-01-01

Public concerns regarding the quality of life of farm animals are often focused on specific practices such as separating the cow and calf immediately after birth. The available scientific literature provides some evidence in support of this practice (including reduced acute responses to separation when it does occur), as well as evidence of disadvantages (such as increased risk of uterine disease in cows). The aim of this study is to systematically examine public views around this practice. Specifically, this study analyzes the views of American and German citizens to separation of cow and calf at birth using a quantitative segmentation approach. Although the majority of participants opposed early separation, a small proportion of our sample supported the practice. According to participants’ preference for early and later separation and their evaluation of different arguments for both practices, three clusters were identified. US participants were more likely to support early separation compared to German participants. The arguments presented for and against both practices caused different reactions in the three clusters, but did not appear to sway the opinions of most participants. The results show considerable opposition to the practice of early separation in large parts of the sample and suggest that the dairy industry should consider approaches to address this concern. PMID:28301604

OGLE II Eclipsing Binaries In The LMC: Analysis With Class

NASA Astrophysics Data System (ADS)

Devinney, Edward J.; Prsa, A.; Guinan, E. F.; DeGeorge, M.

2011-01-01

The Eclipsing Binaries (EBs) via Artificial Intelligence (EBAI) Project is applying machine learning techniques to elucidate the nature of EBs. Previously, Prsa, et al. applied artificial neural networks (ANNs) trained on physically-realistic Wilson-Devinney models to solve the light curves of the 1882 detached EBs in the LMC discovered by the OGLE II Project (Wyrzykowski, et al.) fully automatically, bypassing the need for manually-derived starting solutions. A curious result is the non-monotonic distribution of the temperature ratio parameter T2/T1, featuring a subsidiary peak noted previously by Mazeh, et al. in an independent analysis using the EBOP EB solution code (Tamuz, et al.). To explore this and to gain a fuller understanding of the multivariate EBAI LMC observational plus solutions data, we have employed automatic clustering and advanced visualization (CAV) techniques. Clustering the OGLE II data aggregates objects that are similar with respect to many parameter dimensions. Measures of similarity for example, could include the multidimensional Euclidean Distance between data objects, although other measures may be appropriate. Applying clustering, we find good evidence that the T2/T1 subsidiary peak is due to evolved binaries, in support of Mazeh et al.'s speculation. Further, clustering suggests that the LMC detached EBs occupying the main sequence region belong to two distinct classes. Also identified as a separate cluster in the multivariate data are stars having a Period-I band relation. Derekas et al. had previously found a Period-K band relation for LMC EBs discovered by the MACHO Project (Alcock, et al.). We suggest such CAV techniques will prove increasingly useful for understanding the large, multivariate datasets increasingly being produced in astronomy. We are grateful for the support of this research from NSF/RUI Grant AST-05-75042 f.

Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis.

PubMed

Momeni-Boroujeni, Amir; Yousefi, Elham; Somma, Jonathan

2017-12-01

Fine-needle aspiration (FNA) biopsy is an accurate method for the diagnosis of solid pancreatic masses. However, a significant number of cases still pose a diagnostic challenge. The authors have attempted to design a computer model to aid in the diagnosis of these biopsies. Images were captured of cell clusters on ThinPrep slides from 75 pancreatic FNA cases (20 malignant, 24 benign, and 31 atypical). A K-means clustering algorithm was used to segment the cell clusters into separable regions of interest before extracting features similar to those used for cytomorphologic assessment. A multilayer perceptron neural network (MNN) was trained and then tested for its ability to distinguish benign from malignant cases. A total of 277 images of cell clusters were obtained. K-means clustering identified 68,301 possible regions of interest overall. Features such as contour, perimeter, and area were found to be significantly different between malignant and benign images (P <.05). The MNN was 100% accurate for benign and malignant categories. The model's predictions from the atypical data set were 77% accurate. The results of the current study demonstrate that computer models can be used successfully to distinguish benign from malignant pancreatic cytology. The fact that the model can categorize atypical cases into benign or malignant with 77% accuracy highlights the great potential of this technology. Although further study is warranted to validate its clinical applications in pancreatic and perhaps other areas of cytology as well, the potential for improved patient outcomes using MNN for image analysis in pathology is significant. Cancer Cytopathol 2017;125:926-33. © 2017 American Cancer Society. © 2017 American Cancer Society.

Identification and Analysis of a Novel Gene Cluster Involves in Fe2+ Oxidation in Acidithiobacillus ferrooxidans ATCC 23270, a Typical Biomining Acidophile.

PubMed

Ai, Chenbing; Liang, Yuting; Miao, Bo; Chen, Miao; Zeng, Weimin; Qiu, Guanzhou

2018-07-01

Iron-oxidizing Acidithiobacillus spp. are applied worldwide in biomining industry to extract metals from sulfide minerals. They derive energy for survival through Fe 2+ oxidation and generate Fe 3+ for the dissolution of sulfide minerals. However, molecular mechanisms of their iron oxidation still remain elusive. A novel two-cytochrome-encoding gene cluster (named tce gene cluster) encoding a high-molecular-weight cytochrome c (AFE_1428) and a c 4 -type cytochrome c 552 (AFE_1429) in A. ferrooxidans ATCC 23270 was first identified in this study. Bioinformatic analysis together with transcriptional study showed that AFE_1428 and AFE_1429 were the corresponding paralog of Cyc2 (AFE_3153) and Cyc1 (AFE_3152) which were encoded by the extensively studied rus operon and had been proven involving in ferrous iron oxidation. Both AFE_1428 and AFE_1429 contained signal peptide and the classic heme-binding motif(s) as their corresponding paralog. The modeled structure of AFE_1429 showed high resemblance to Cyc1. AFE_1428 and AFE_1429 were preferentially transcribed as their corresponding paralogs in the presence of ferrous iron as sole energy source as compared with sulfur. The tce gene cluster is highly conserved in the genomes of four phylogenetic-related A. ferrooxidans strains that were originally isolated from different sites separated with huge geographical distance, which further implies the importance of this gene cluster. Collectively, AFE_1428 and AFE_1429 involve in Fe 2+ oxidation like their corresponding paralog by integrating with the metalloproteins encoded by rus operon. This study provides novel insights into the Fe 2+ oxidation mechanism in Fe 2+ -oxidizing A. ferrooxidans ssp.

Structures in magnetohydrodynamic turbulence: Detection and scaling

NASA Astrophysics Data System (ADS)

Uritsky, V. M.; Pouquet, A.; Rosenberg, D.; Mininni, P. D.; Donovan, E. F.

2010-11-01

We present a systematic analysis of statistical properties of turbulent current and vorticity structures at a given time using cluster analysis. The data stem from numerical simulations of decaying three-dimensional magnetohydrodynamic turbulence in the absence of an imposed uniform magnetic field; the magnetic Prandtl number is taken equal to unity, and we use a periodic box with grids of up to 15363 points and with Taylor Reynolds numbers up to 1100. The initial conditions are either an X -point configuration embedded in three dimensions, the so-called Orszag-Tang vortex, or an Arn’old-Beltrami-Childress configuration with a fully helical velocity and magnetic field. In each case two snapshots are analyzed, separated by one turn-over time, starting just after the peak of dissipation. We show that the algorithm is able to select a large number of structures (in excess of 8000) for each snapshot and that the statistical properties of these clusters are remarkably similar for the two snapshots as well as for the two flows under study in terms of scaling laws for the cluster characteristics, with the structures in the vorticity and in the current behaving in the same way. We also study the effect of Reynolds number on cluster statistics, and we finally analyze the properties of these clusters in terms of their velocity-magnetic-field correlation. Self-organized criticality features have been identified in the dissipative range of scales. A different scaling arises in the inertial range, which cannot be identified for the moment with a known self-organized criticality class consistent with magnetohydrodynamics. We suggest that this range can be governed by turbulence dynamics as opposed to criticality and propose an interpretation of intermittency in terms of propagation of local instabilities.

The spatio-temporal mapping of epileptic networks: Combination of EEG–fMRI and EEG source imaging

PubMed Central

Vulliemoz, S.; Thornton, R.; Rodionov, R.; Carmichael, D.W.; Guye, M.; Lhatoo, S.; McEvoy, A.W.; Spinelli, L.; Michel, C.M.; Duncan, J.S.; Lemieux, L.

2009-01-01

Simultaneous EEG–fMRI acquisitions in patients with epilepsy often reveal distributed patterns of Blood Oxygen Level Dependant (BOLD) change correlated with epileptiform discharges. We investigated if electrical source imaging (ESI) performed on the interictal epileptiform discharges (IED) acquired during fMRI acquisition could be used to study the dynamics of the networks identified by the BOLD effect, thereby avoiding the limitations of combining results from separate recordings. Nine selected patients (13 IED types identified) with focal epilepsy underwent EEG–fMRI. Statistical analysis was performed using SPM5 to create BOLD maps. ESI was performed on the IED recorded during fMRI acquisition using a realistic head model (SMAC) and a distributed linear inverse solution (LAURA). ESI could not be performed in one case. In 10/12 remaining studies, ESI at IED onset (ESIo) was anatomically close to one BOLD cluster. Interestingly, ESIo was closest to the positive BOLD cluster with maximal statistical significance in only 4/12 cases and closest to negative BOLD responses in 4/12 cases. Very small BOLD clusters could also have clinical relevance in some cases. ESI at later time frame (ESIp) showed propagation to remote sources co-localised with other BOLD clusters in half of cases. In concordant cases, the distance between maxima of ESI and the closest EEG–fMRI cluster was less than 33 mm, in agreement with previous studies. We conclude that simultaneous ESI and EEG–fMRI analysis may be able to distinguish areas of BOLD response related to initiation of IED from propagation areas. This combination provides new opportunities for investigating epileptic networks. PMID:19408351

Image Patch Analysis of Sunspots and Active Regions

NASA Astrophysics Data System (ADS)

Moon, K.; Delouille, V.; Hero, A.

2017-12-01

The flare productivity of an active region has been observed to be related to its spatial complexity. Separating active regions that are quiet from potentially eruptive ones is a key issue in space weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature does not use all of the information present in the observations. In our work, we present an image patch analysis for characterizing sunspots and active regions. We first propose fine-scale quantitative descriptors for an active region's complexity such as intrinsic dimension, and we relate them to the Mount Wilson classification. Second, we introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. To obtain this local geometry, we use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches using the singular value decomposition. The resulting factorizations of active regions can be compared via the definition of appropriate metrics on the factors. The distances obtained from these metrics are then used to cluster the active regions. Results. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the R-value.

Light and Heavy Element Abundance Variations in the Outer Halo Globular Cluster NGC 6229

NASA Astrophysics Data System (ADS)

Johnson, Christian I.; Caldwell, Nelson; Rich, R. Michael; Walker, Matthew G.

2017-10-01

NGC 6229 is a relatively massive outer halo globular cluster that is primarily known for exhibiting a peculiar bimodal horizontal branch morphology. Given the paucity of spectroscopic data on this cluster, we present a detailed chemical composition analysis of 11 red giant branch members based on high resolution (R ≈ 38,000), high S/N (>100) spectra obtained with the MMT-Hectochelle instrument. We find the cluster to have a mean heliocentric radial velocity of -{138.1}-1.0+1.0 {km} {{{s}}}-1, a small dispersion of {3.8}-0.7+1.0 {km} {{{s}}}-1, and a relatively low {(M/{L}{{V}})}⊙ ={0.82}-0.28+0.49. The cluster is moderately metal-poor with < [{Fe}/{{H}}]> =-1.13 dex and a modest dispersion of 0.06 dex. However, 18% (2/11) of the stars in our sample have strongly enhanced [La, Nd/Fe] ratios that are correlated with a small (˜0.05 dex) increase in [Fe/H]. NGC 6229 shares several chemical signatures with M75, NGC 1851, and the intermediate metallicity populations of ω Cen, which lead us to conclude that NGC 6229 is a lower mass iron-complex cluster. The light elements exhibit the classical (anti-)correlations that extend up to Si, but the cluster possesses a large gap in the O-Na plane that separates first and second generation stars. NGC 6229 also has unusually low [Na, Al/Fe] abundances that are consistent with an accretion origin. A comparison with M54 and other Sagittarius clusters suggests that NGC 6229 could also be the remnant core of a former dwarf spheroidal galaxy.

West Virginia US Department of Energy experimental program to stimulate competitive research. Section 2: Human resource development; Section 3: Carbon-based structural materials research cluster; Section 3: Data parallel algorithms for scientific computing

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

Not Available

1994-02-02

This report consists of three separate but related reports. They are (1) Human Resource Development, (2) Carbon-based Structural Materials Research Cluster, and (3) Data Parallel Algorithms for Scientific Computing. To meet the objectives of the Human Resource Development plan, the plan includes K--12 enrichment activities, undergraduate research opportunities for students at the state`s two Historically Black Colleges and Universities, graduate research through cluster assistantships and through a traineeship program targeted specifically to minorities, women and the disabled, and faculty development through participation in research clusters. One research cluster is the chemistry and physics of carbon-based materials. The objective of thismore » cluster is to develop a self-sustaining group of researchers in carbon-based materials research within the institutions of higher education in the state of West Virginia. The projects will involve analysis of cokes, graphites and other carbons in order to understand the properties that provide desirable structural characteristics including resistance to oxidation, levels of anisotropy and structural characteristics of the carbons themselves. In the proposed cluster on parallel algorithms, research by four WVU faculty and three state liberal arts college faculty are: (1) modeling of self-organized critical systems by cellular automata; (2) multiprefix algorithms and fat-free embeddings; (3) offline and online partitioning of data computation; and (4) manipulating and rendering three dimensional objects. This cluster furthers the state Experimental Program to Stimulate Competitive Research plan by building on existing strengths at WVU in parallel algorithms.« less

THE VERY MASSIVE STAR CONTENT OF THE NUCLEAR STAR CLUSTERS IN NGC 5253

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

Smith, L. J.; Crowther, P. A.; Calzetti, D.

2016-05-20

The blue compact dwarf galaxy NGC 5253 hosts a very young starburst containing twin nuclear star clusters, separated by a projected distance of 5 pc. One cluster (#5) coincides with the peak of the H α emission and the other (#11) with a massive ultracompact H ii region. A recent analysis of these clusters shows that they have a photometric age of 1 ± 1 Myr, in apparent contradiction with the age of 3–5 Myr inferred from the presence of Wolf-Rayet features in the cluster #5 spectrum. We examine Hubble Space Telescope ultraviolet and Very Large Telescope optical spectroscopy ofmore » #5 and show that the stellar features arise from very massive stars (VMSs), with masses greater than 100 M {sub ⊙}, at an age of 1–2 Myr. We further show that the very high ionizing flux from the nuclear clusters can only be explained if VMSs are present. We investigate the origin of the observed nitrogen enrichment in the circumcluster ionized gas and find that the excess N can be produced by massive rotating stars within the first 1 Myr. We find similarities between the NGC 5253 cluster spectrum and those of metal-poor, high-redshift galaxies. We discuss the presence of VMSs in young, star-forming galaxies at high redshift; these should be detected in rest-frame UV spectra to be obtained with the James Webb Space Telescope . We emphasize that population synthesis models with upper mass cutoffs greater than 100 M {sub ⊙} are crucial for future studies of young massive star clusters at all redshifts.« less

Child's positive and negative impacts on parents--a person-oriented approach to understanding temperament in preschool children with intellectual disabilities.

PubMed

Boström, P K; Broberg, M; Bodin, L

2011-01-01

Despite previous efforts to understand temperament in children with intellectual disability (ID), and how child temperament may affect parents, the approach has so far been unidimensional. Child temperament has been considered in relation to diagnosis, with the inherent risk of overlooking individual variation of children's temperament profiles within diagnostic groups. The aim of the present study was to identify temperamental profiles of children with ID, and investigate how these may affect parents in terms of positive and negative impacts. Parent-rated temperament in children with ID was explored through a person-oriented approach (cluster analysis). Children with ID (N=49) and typically developing (TD) children (N=82) aged between 4 and 6 years were clustered separately. Variation in temperament profiles was more prominent among children with ID than in TD children. Out of the three clusters found in the ID group, the disruptive, and passive/withdrawn clusters were distinctly different from clusters found in the TD group in terms of temperament, while the cluster active and outgoing was similar in shape and level of temperament ratings of TD children. Children within the disruptive cluster were described to have more negative and less positive impacts on mothers compared to children within the other clusters in the ID group. Mothers who describe their children as having disruptive temperament may be at particular risk for experiencing higher parenting stress as they report that the child has higher negative and lower positive impacts than other parents describe. The absence of a relationship between child temperament profile and positive or negative impact on fathers may indicate that fathers are less affected by child temperament. However, this relationship needs to be further explored. Copyright © 2011 Elsevier Ltd. All rights reserved.

Social influences on health-related behaviour clustering during adulthood in two British birth cohort studies.

PubMed

Mawditt, Claire; Sacker, Amanda; Britton, Annie; Kelly, Yvonne; Cable, Noriko

2018-05-01

Building upon evidence linking socio-economic position (SEP) in childhood and adulthood with health-related behaviours (HRB) in adulthood, we examined how pre-adolescent SEP predicted membership of three HRB clusters: "Risky", "Moderate Smokers" and "Mainstream" (the latter pattern consisting of more beneficial HRBs), that were detected in our previous work. Data were taken from two British cohorts (born in 1958 and 1970) in pre-adolescence (age 11 and 10, respectively) and adulthood (age 33 and 34). SEP constructs in pre-adolescence and adulthood were derived through Confirmatory Factor Analysis. Conceptualised paths from pre-adolescent SEP to HRB cluster membership via adult SEP in our path models were tested for statistical significance separately by gender and cohort. Adult SEP mediated the path between pre-adolescent SEP and adult HRB clusters. More disadvantaged SEP in pre-adolescence predicted more disadvantaged SEP in adulthood which was associated with membership of the "Risky" and "Moderate Smokers" clusters compared to the "Mainstream" cluster. For example, large positive indirect effects between pre-adolescent SEP and adult HRB via adult SEP were present (coefficient 1958 Women = 0.39; 1970 Women = 0.36, 1958 Men = 0.51; 1970 Men = 0.39; p < 0.01) when comparing "Risky" and "Mainstream" cluster membership. Amongst men we found a small significant direct association (p < 0.001) between pre-adolescent SEP and HRB cluster membership. Our findings suggest that associations between adult SEP and HRBs are not likely to be pre-determined by earlier social circumstances, providing optimism for interventions relevant to reducing social gradients in HRBs. Observing consistent findings across the cohorts implies the social patterning of adult lifestyles may persist across time. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Genetic diversity among eight Dendrolimus species in Eurasia (Lepidoptera: Lasiocampidae) inferred from mitochondrial COI and COII, and nuclear ITS2 markers.

PubMed

Kononov, Alexander; Ustyantsev, Kirill; Wang, Baode; Mastro, Victor C; Fet, Victor; Blinov, Alexander; Baranchikov, Yuri

2016-12-22

Moths of genus Dendrolimus (Lepidoptera: Lasiocampidae) are among the major pests of coniferous forests worldwide. Taxonomy and nomenclature of this genus are not entirely established, and there are many species with a controversial taxonomic position. We present a comparative evolutionary analysis of the most economically important Dendrolimus species in Eurasia. Our analysis was based on the nucleotide sequences of COI and COII mitochondrial genes and ITS2 spacer of nuclear ribosomal genes. All known sequences were extracted from GenBank. Additional 112 new sequences were identified for 28 specimens of D. sibiricus, D. pini, and D. superans from five regions of Siberia and the Russian Far East to be able to compare the disparate data from all previous studies. In total, 528 sequences were used in phylogenetic analysis. Two clusters of closely related species in Dendrolimus were found. The first cluster includes D. pini, D. sibiricus, and D. superans; and the second, D. spectabilis, D. punctatus, and D. tabulaeformis. Species D. houi and D. kikuchii appear to be the most basal in the genus. Genetic difference among the second cluster species is very low in contrast to the first cluster species. Phylogenetic position D. tabulaeformis as a subspecies was supported. It was found that D. sibiricus recently separated from D. superans. Integration of D. sibiricus mitochondrial DNA sequences and the spread of this species to the west of Eurasia have been established as the cause of the unjustified allocation of a new species: D. kilmez. Our study further clarifies taxonomic problems in the genus and gives more complete information on the genetic structure of D. pini, D. sibiricus, and D. superans.

Assessment of genetic diversity and phylogenetic relationships of Korean native chicken breeds using microsatellite markers

PubMed Central

Seo, Joo Hee; Lee, Jun Heon; Kong, Hong Sik

2017-01-01

Objective This study was conducted to investigate the basic information on genetic structure and characteristics of Korean Native chickens (NC) and foreign breeds through the analysis of the pure chicken populations and commercial chicken lines of the Hanhyup Company which are popular in the NC market, using the 20 microsatellite markers. Methods In this study, the genetic diversity and phylogenetic relationships of 445 NC from five different breeds (NC, Leghorn [LH], Cornish [CS], Rhode Island Red [RIR], and Hanhyup [HH] commercial line) were investigated by performing genotyping using 20 microsatellite markers. Results The highest genetic distance was observed between RIR and LH (18.9%), whereas the lowest genetic distance was observed between HH and NC (2.7%). In the principal coordinates analysis (PCoA) illustrated by the first component, LH was clearly separated from the other groups. The correspondence analysis showed close relationship among individuals belonging to the NC, CS, and HH lines. From the STRUCTURE program, the presence of 5 clusters was detected and it was found that the proportion of membership in the different clusters was almost comparable among the breeds with the exception of one breed (HH), although it was highest in LH (0.987) and lowest in CS (0.578). For the cluster 1 it was high in HH (0.582) and in CS (0.368), while for the cluster 4 it was relatively higher in HH (0.392) than other breeds. Conclusion Our study showed useful genetic diversity and phylogenetic relationship data that can be utilized for NC breeding and development by the commercial chicken industry to meet consumer demands. PMID:28335091

Evaluation of Fourier transform infrared (FT-IR) spectroscopy and chemometrics as a rapid approach for sub-typing Escherichia coli O157:H7 isolates.

PubMed

Davis, R; Paoli, G; Mauer, L J

2012-09-01

The importance of tracking outbreaks of foodborne illness and the emergence of new virulent subtypes of foodborne pathogens have created the need for rapid and reliable sub-typing methods for Escherichia coli O157:H7. Fourier transform infrared (FT-IR) spectroscopy coupled with multivariate statistical analyses was used for sub-typing 30 strains of E. coli O157:H7 that had previously been typed by multilocus variable number tandem repeat analysis (MLVA) and pulsed field gel electrophoresis (PFGE). Hierarchical cluster analysis (HCA) and canonical variate analysis (CVA) of the FT-IR spectra resulted in the clustering of the same or similar MLVA types and separation of different MLVA types of E. coli O157:H7. The developed FT-IR method showed better discriminatory power than PFGE in sub-typing E. coli O157:H7. Results also indicated the spectral relatedness between different outbreak strains. However, the grouping of some strains was not in complete agreement with the clustering based on PFGE and MLVA. Additionally, HCA of the spectra differentiated the strains into 30 sub-clusters, indicating the high specificity and suitability of the method for strain level identification. Strains were also classified (97% correct) based on the type of Shiga toxin present using CVA of the spectra. This study demonstrated that FT-IR spectroscopy is suitable for rapid (≤16 h) and economical sub-typing of E. coli O157:H7 with comparable accuracy to MLVA typing. This is the first report of using an FT-IR-based method for sub-typing E. coli O157:H7. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial variation of volcanic rock geochemistry in the Virunga Volcanic Province: Statistical analysis of an integrated database

NASA Astrophysics Data System (ADS)

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

2017-10-01

We present an integrated, spatially-explicit database of existing geochemical major-element analyses available from (post-) colonial scientific reports, PhD Theses and international publications for the Virunga Volcanic Province, located in the western branch of the East African Rift System. This volcanic province is characterised by alkaline volcanism, including silica-undersaturated, alkaline and potassic lavas. The database contains a total of 908 geochemical analyses of eruptive rocks for the entire volcanic province with a localisation for most samples. A preliminary analysis of the overall consistency of the database, using statistical techniques on sets of geochemical analyses with contrasted analytical methods or dates, demonstrates that the database is consistent. We applied a principal component analysis and cluster analysis on whole-rock major element compositions included in the database to study the spatial variation of the chemical composition of eruptive products in the Virunga Volcanic Province. These statistical analyses identify spatially distributed clusters of eruptive products. The known geochemical contrasts are highlighted by the spatial analysis, such as the unique geochemical signature of Nyiragongo lavas compared to other Virunga lavas, the geochemical heterogeneity of the Bulengo area, and the trachyte flows of Karisimbi volcano. Most importantly, we identified separate clusters of eruptive products which originate from primitive magmatic sources. These lavas of primitive composition are preferentially located along NE-SW inherited rift structures, often at distance from the central Virunga volcanoes. Our results illustrate the relevance of a spatial analysis on integrated geochemical data for a volcanic province, as a complement to classical petrological investigations. This approach indeed helps to characterise geochemical variations within a complex of magmatic systems and to identify specific petrologic and geochemical investigations that should be tackled within a study area.

Safer sexual practices among African American women: intersectional socialisation and sexual assertiveness.

PubMed

Brown, Danice L; Blackmon, Sha'Kema; Shiflett, Alexandra

2018-06-01

Scholars have posited that childhood socialisation experiences may play a key role in influencing behaviours and attitudes that contribute to the acquisition of HIV. This study examined the links between past ethnic-racial and gender socialisation, sexual assertiveness and the safe sexual practices of African American college women utilising a cluster analytic approach. After identifying separate racial-gender and ethnic-gender socialisation profiles, results indicated that ethnic-gender socialisation cluster profiles were directly associated with sexual assertiveness and safer sex behaviour. Greater levels of ethnic socialisation and low traditional gender role socialisation were found to be associated with greater sexual assertiveness and safer sex behaviour. Further analysis showed that sexual assertiveness mediated the links between the identified ethnic-gender socialisation profiles and safer sex behaviour. Implications for policy and programme development are discussed.

A high degree of genetic diversity is revealed in Isatis spp. (dyer's woad) by amplified fragment length polymorphism (AFLP).

PubMed

Gilbert (nee Stoker), G.; Garton, S.; Karam, A.; Arnold, M.; Karp, A.; Edwards, J.; Cooke, T.; Barker, A.

2002-05-01

Genetic diversity in 38 genotypes, representing 28 individual genotypes from five landraces of Isatis tinctoria (three German: Tubingen, Potsdam and Erfurt, one Swiss and one English), five genotypes of Isatis indigotica (Chinese woad) and five genotypes of Isatis glauca, were investigated using AFLP analysis. Five primer combinations detected a total of 502 fragments of which 436 (86.9%) were polymorphic. The level of polymorphism recorded within each species was 29.8, 86.9 and 35.8% for I. indigotica, I. tinctoria and I. glauca, respectively. Clearly, genetic diversity within I. tinctoria was greater than that observed in I. indigotica or I. glauca. Cluster analyses of the AFLP data using UPGMA and PCO revealed the complete separation of the genotypes of each species into distinct groups. I. indigotica separated as an entirely independent group, whereas I. glauca formed a separate cluster within the I. tinctoria group. Indeed, I. tinctoria and I. glauca are more closely related to each other than either is to I. indigotica. In addition, the genotypes of each landrace, apart from one from the English group, were clearly discriminated. However, the anomalous genotype did associate with the rest of its group when it was linked with the Erfurt group. These results provide new and useful information about the make-up of the Isatis genome, which has not previously been evaluated. They will be useful in the selection of plant material for variety development and conservation of the gene-pool.

Organic dairy farmers put more emphasis on production traits than conventional farmers.

PubMed

Slagboom, M; Kargo, M; Edwards, D; Sørensen, A C; Thomasen, J R; Hjortø, L

2016-12-01

The overall aim of this research was to characterize the preferences of Danish dairy farmers for improvements in breeding goal traits. The specific aims were (1) to investigate the presence of heterogeneity in farmers' preferences by means of cluster analysis, and (2) to associate these clusters with herd characteristics and production systems (organic or conventional). We established a web-based survey to characterize the preferences of farmers for improvements in 10 traits, by means of pairwise rankings. We also collected a considerable number of herd characteristics. Overall, 106 organic farmers and 290 conventional farmers answered the survey, all with Holstein cows. The most preferred trait improvement was cow fertility, and the least preferred was calving difficulty. By means of cluster analysis, we identified 4 distinct clusters of farmers and named them according to the trait improvements that were most preferred: Health and Fertility, Production and Udder Health, Survival, and Fertility and Production. Some herd characteristics differed between clusters; for example, farmers in the Survival cluster had twice the percentage of dead cows in their herds compared with the other clusters, and farmers that gave the highest ranking to cow and heifer fertility had the lowest conception rate in their herds. This finding suggests that farmers prefer to improve traits that are more problematic in their herd. The proportion of organic and conventional farmers also differed between clusters; we found a higher proportion of organic farmers in the production-based clusters. When we analyzed organic and conventional data separately, we found that organic farmers ranked production traits higher than conventional farmers. The herds of organic farmers had lower milk yields and lower disease incidences, which might explain the high ranking of milk production and the low ranking of disease traits. This study shows that heterogeneity exists in farmers' preferences for improvements in breeding goal traits, that organic and conventional farmers differ in their preferences, and that herd characteristics can be linked to different farmer clusters. The results of this study could be used for the future development of breeding goals in Danish Holstein cows and for the development of customized total merit indices based on farmer preferences. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Most high-grade neuroendocrine tumours of the lung are likely to secondarily develop from pre-existing carcinoids: innovative findings skipping the current pathogenesis paradigm.

PubMed

Pelosi, Giuseppe; Bianchi, Fabrizio; Dama, Elisa; Simbolo, Michele; Mafficini, Andrea; Sonzogni, Angelica; Pilotto, Sara; Harari, Sergio; Papotti, Mauro; Volante, Marco; Fontanini, Gabriella; Mastracci, Luca; Albini, Adriana; Bria, Emilio; Calabrese, Fiorella; Scarpa, Aldo

2018-04-01

Among lung neuroendocrine tumours (Lung-NETs), typical carcinoid (TC) and atypical carcinoid (AC) are considered separate entities as opposed to large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC). By means of two-way clustering analysis of previously reported next-generation sequencing data on 148 surgically resected Lung-NETs, six histology-independent clusters (C1 → C6) accounting for 68% of tumours were identified. Low-grade Lung-NETs were likely to evolve into high-grade tumours following two smoke-related paths. Tumour composition of the first path (C5 → C1 → C6) was coherent with the hypothesis of an evolution of TC to LCNEC, even with a conversion of SCLC-featuring tumours to LCNEC. The second path (C4 → C2-C3) had a tumour composition supporting the evolution of AC to SCLC-featuring tumours. The relevant Ki-67 labelling index varied accordingly, with median values being 5%, 9% and 50% in the cluster sequence C5 → C1 → C6, 12% in cluster C4 and 50-60% in cluster C2-C3. This proof-of-concept study suggests an innovative view on the progression of pre-existing TC or AC to high-grade NE carcinomas in most Lung-NET instances.

A Systematic Analysis of Caustic Methods for Galaxy Cluster Masses

NASA Astrophysics Data System (ADS)

Gifford, Daniel; Miller, Christopher; Kern, Nicholas

2013-08-01

We quantify the expected observed statistical and systematic uncertainties of the escape velocity as a measure of the gravitational potential and total mass of galaxy clusters. We focus our attention on low redshift (z <=0.15) clusters, where large and deep spectroscopic datasets currently exist. Utilizing a suite of Millennium Simulation semi-analytic galaxy catalogs, we find that the dynamical mass, as traced by either the virial relation or the escape velocity, is robust to variations in how dynamical friction is applied to "orphan" galaxies in the mock catalogs (i.e., those galaxies whose dark matter halos have fallen below the resolution limit). We find that the caustic technique recovers the known halo masses (M 200) with a third less scatter compared to the virial masses. The bias we measure increases quickly as the number of galaxies used decreases. For N gal > 25, the scatter in the escape velocity mass is dominated by projections along the line-of-sight. Algorithmic uncertainties from the determination of the projected escape velocity profile are negligible. We quantify how target selection based on magnitude, color, and projected radial separation can induce small additional biases into the escape velocity masses. Using N gal = 150 (25), the caustic technique has a per cluster scatter in ln (M|M 200) of 0.3 (0.5) and bias 1% ± 3} (16% ± 5}) for clusters with masses >1014 M ⊙ at z < 0.15.

Quantitative analysis of impact of awareness-raising activities on organic solid waste separation behaviour in Balikpapan City, Indonesia.

PubMed

Murase, Noriaki; Murayama, Takehiko; Nishikizawa, Shigeo; Sato, Yuriko

2017-10-01

Many cities in Indonesia are under pressure to reduce solid waste and dispose of it properly. In response to this pressure, the Japan International Cooperation Agency and the Indonesian Government have implemented a solid waste separation and collection project to reduce solid waste in the target area (810 households) of Balikpapan City. We used a cluster randomised controlled trial method to measure the impact of awareness-raising activities that were introduced by the project on residents' organic solid waste separation behaviour. The level of properly separated organic solid waste increased by 6.0% in areas that conducted awareness-raising activities. Meanwhile, the level decreased by 3.6% in areas that did not conduct similar activities. Therefore, in relative comparison, awareness-raising increased the level by 9.6%. A comparison among small communities in the target area confirmed that awareness-raising activities had a significant impact on organic solid waste separation. High frequencies of monitoring at waste stations and door-to-door visits by community members had a positive impact on organic solid waste separation. A correlation between the proximity of environmental volunteers' houses to waste stations and a high level of separation was also confirmed. The awareness-raising activities introduced by the project led to a significant increase in the separation of organic solid waste.

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

Sehgal, Neelima; Hlozek, Renee; Addison, Graeme

We present the measured Sunyaev-Zel'dovich (SZ) flux from 474 optically selected MaxBCG clusters that fall within the Atacama Cosmology Telescope (ACT) Equatorial survey region. The ACT Equatorial region used in this analysis covers 510 deg{sup 2} and overlaps Stripe 82 of the Sloan Digital Sky Survey. We also present the measured SZ flux stacked on 52 X-ray-selected MCXC clusters that fall within the ACT Equatorial region and an ACT Southern survey region covering 455 deg{sup 2}. We find that the measured SZ flux from the X-ray-selected clusters is consistent with expectations. However, we find that the measured SZ flux frommore » the optically selected clusters is both significantly lower than expectations and lower than the recovered SZ flux measured by the Planck satellite. Since we find a lower recovered SZ signal than Planck, we investigate the possibility that there is a significant offset between the optically selected brightest cluster galaxies (BCGs) and the SZ centers, to which ACT is more sensitive due to its finer resolution. Such offsets can arise due to either an intrinsic physical separation between the BCG and the center of the gas concentration or from misidentification of the cluster BCG. We find that the entire discrepancy for both ACT and Planck can be explained by assuming that the BCGs are offset from the SZ maxima with a uniform random distribution between 0 and 1.5 Mpc. Such large offsets between gas peaks and BCGs for optically selected cluster samples seem unlikely given that we find the physical separation between BCGs and X-ray peaks for an X-ray-selected subsample of MaxBCG clusters to have a much narrower distribution that peaks within 0.2 Mpc. It is possible that other effects are lowering the ACT and Planck signals by the same amount, with offsets between BCGs and SZ peaks explaining the remaining difference between ACT and Planck measurements. Several effects that can lower the SZ signal equally for both ACT and Planck, but not explain the difference in measured signals, include a larger percentage of false detections in the MaxBCG sample, a lower normalization of the mass-richness relation, radio or infrared galaxy contamination of the SZ flux, and a low intrinsic SZ signal. In the latter two cases, the effects would need to be preferentially more significant in the optically selected MaxBCG sample than in the MCXC X-ray sample.« less

Imprints of dynamical interactions on brown dwarf pairing statistics and kinematics

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.

2003-03-01

We present statistically robust predictions of brown dwarf properties arising from dynamical interactions during their early evolution in small clusters. Our conclusions are based on numerical calculations of the internal cluster dynamics as well as on Monte-Carlo models. Accounting for recent observational constraints on the sub-stellar mass function and initial properties in fragmenting star forming clumps, we derive multiplicity fractions, mass ratios, separation distributions, and velocity dispersions. We compare them with observations of brown dwarfs in the field and in young clusters. Observed brown dwarf companion fractions around 15 +/- 7% for very low-mass stars as reported recently by Close et al. (\\cite{CSFB03}) are consistent with certain dynamical decay models. A significantly smaller mean separation distribution for brown dwarf binaries than for binaries of late-type stars can be explained by similar specific energy at the time of cluster formation for all cluster masses. Due to their higher velocity dispersions, brown-dwarfs and low-mass single stars will undergo time-dependent spatial segregation from higher-mass stars and multiple systems. This will cause mass functions and binary statistics in star forming regions to vary with the age of the region and the volume sampled.

The separate and combined effects of baryon physics and neutrino free streaming on large-scale structure

NASA Astrophysics Data System (ADS)

Mummery, Benjamin O.; McCarthy, Ian G.; Bird, Simeon; Schaye, Joop

2017-10-01

We use the cosmo-OWLS and bahamas suites of cosmological hydrodynamical simulations to explore the separate and combined effects of baryon physics (particularly feedback from active galactic nuclei, AGN) and free streaming of massive neutrinos on large-scale structure. We focus on five diagnostics: (I) the halo mass function, (II) halo mass density profiles, (III) the halo mass-concentration relation, (IV) the clustering of haloes and (v) the clustering of matter, and we explore the extent to which the effects of baryon physics and neutrino free streaming can be treated independently. Consistent with previous studies, we find that both AGN feedback and neutrino free streaming suppress the total matter power spectrum, although their scale and redshift dependences differ significantly. The inclusion of AGN feedback can significantly reduce the masses of groups and clusters, and increase their scale radii. These effects lead to a decrease in the amplitude of the mass-concentration relation and an increase in the halo autocorrelation function at fixed mass. Neutrinos also lower the masses of groups and clusters while having no significant effect on the shape of their density profiles (thus also affecting the mass-concentration relation and halo clustering in a qualitatively similar way to feedback). We show that, with only a small number of exceptions, the combined effects of baryon physics and neutrino free streaming on all five diagnostics can be estimated to typically better than a few per cent accuracy by treating these processes independently (I.e. by multiplying their separate effects).

Relative dispersion of clustered drifters in a small micro-tidal estuary

NASA Astrophysics Data System (ADS)

Suara, Kabir; Chanson, Hubert; Borgas, Michael; Brown, Richard J.

2017-07-01

Small tide-dominated estuaries are affected by large scale flow structures which combine with the underlying bed generated smaller scale turbulence to significantly increase the magnitude of horizontal diffusivity. Field estimates of horizontal diffusivity and its associated scales are however rare due to limitations in instrumentation. Data from multiple deployments of low and high resolution clusters of GPS-drifters are used to examine the dynamics of a surface flow in a small micro-tidal estuary through relative dispersion analyses. During the field study, cluster diffusivity, which combines both large- and small-scale processes ranged between, 0.01 and 3.01 m2/s for spreading clusters and, -0.06 and -4.2 m2/s for contracting clusters. Pair-particle dispersion, Dp2, was scale dependent and grew as Dp2 ∼ t1.83 in streamwise and Dp2 ∼ t0.8 in cross-stream directions. At small separation scale, pair-particle (d < 0.5 m) relative diffusivity followed the Richardson's 4/3 power law and became weaker as separation scale increases. Pair-particle diffusivity was described as Kp ∼ d1.01 and Kp ∼ d0.85 in the streamwise and cross-stream directions, respectively for separation scales ranging from 0.1 to 10 m. Two methods were used to identify the mechanism responsible for dispersion within the channel. The results clearly revealed the importance of strain fields (stretching and shearing) in the spreading of particles within a small micro-tidal channel. The work provided input for modelling dispersion of passive particle in shallow micro-tidal estuaries where these were not previously experimentally studied.

Dissociation of doubly charged clusters of lithium acetate: Asymmetric fission and breakdown of the liquid drop model: Dissociation of doubly charged clusters of lithium acetate

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

Shukla, Anil

2016-06-08

Unimolecular and collision-induced dissociation of doubly charged lithium acetate clusters, (CH3COOLi)nLi22+, demonstrated that Coulomb fission via charge separation is the dominant dissociation process with no contribution from the neutral evaporation processes for all such ions from the critical limit to larger cluster ions, although latter process have normally been observed in all earlier studies. These results are clearly in disagreement with the Rayleigh’s liquid drop model that has been used successfully to predict the critical size and explain the fragmentation behavior of multiply charged clusters.

VizieR Online Data Catalog: NGC 6802 dwarf cluster members and non-members (Tang+, 2017)

NASA Astrophysics Data System (ADS)

Tang, B.; Geisler, D.; Friel, E.; Villanova, S.; Smiljanic, R.; Casey, A. R.; Randich, S.; Magrini, L.; San, Roman I.; Munoz, C.; Cohen, R. E.; Mauro, F.; Bragaglia, A.; Donati, P.; Tautvaisiene, G.; Drazdauskas, A.; Zenoviene, R.; Snaith, O.; Sousa, S.; Adibekyan, V.; Costado, M. T.; Blanco-Cuaresma, S.; Jimenez-Esteban, F.; Carraro, G.; Zwitter, T.; Francois, P.; Jofre, P.; Sordo, R.; Gilmore, G.; Flaccomio, E.; Koposov, S.; Korn, A. J.; Lanzafame, A. C.; Pancino, E.; Bayo, A.; Damiani, F.; Franciosini, E.; Hourihane, A.; Lardo, C.; Lewis, J.; Monaco, L.; Morbidelli, L.; Prisinzano, L.; Sacco, G.; Worley, C. C.; Zaggia, S.

2016-11-01

The dwarf stars in NGC 6802 observed by GIRAFFE spectrograph are separated into four tables: 1. cluster members in the lower main sequence; 2. cluster members in the upper main sequence; 3. non-member dwarfs in the lower main sequence; 4. non-member dwarfs in the upper main sequence. The star coordinates, V band magnitude, V-I color, and radial velocity are given. (4 data files).

Density-based clustering of small peptide conformations sampled from a molecular dynamics simulation.

PubMed

Kim, Minkyoung; Choi, Seung-Hoon; Kim, Junhyoung; Choi, Kihang; Shin, Jae-Min; Kang, Sang-Kee; Choi, Yun-Jaie; Jung, Dong Hyun

2009-11-01

This study describes the application of a density-based algorithm to clustering small peptide conformations after a molecular dynamics simulation. We propose a clustering method for small peptide conformations that enables adjacent clusters to be separated more clearly on the basis of neighbor density. Neighbor density means the number of neighboring conformations, so if a conformation has too few neighboring conformations, then it is considered as noise or an outlier and is excluded from the list of cluster members. With this approach, we can easily identify clusters in which the members are densely crowded in the conformational space, and we can safely avoid misclustering individual clusters linked by noise or outliers. Consideration of neighbor density significantly improves the efficiency of clustering of small peptide conformations sampled from molecular dynamics simulations and can be used for predicting peptide structures.

Breakup of a homeobox cluster after genome duplication in teleosts

PubMed Central

Mulley, John F.; Chiu, Chi-hua; Holland, Peter W. H.

2006-01-01

Several families of homeobox genes are arranged in genomic clusters in metazoan genomes, including the Hox, ParaHox, NK, Rhox, and Iroquois gene clusters. The selective pressures responsible for maintenance of these gene clusters are poorly understood. The ParaHox gene cluster is evolutionarily conserved between amphioxus and human but is fragmented in teleost fishes. We show that two basal ray-finned fish, Polypterus and Amia, each possess an intact ParaHox cluster; this implies that the selective pressure maintaining clustering was lost after whole-genome duplication in teleosts. Cluster breakup is because of gene loss, not transposition or inversion, and the total number of ParaHox genes is the same in teleosts, human, mouse, and frog. We propose that this homeobox gene cluster is held together in chordates by the existence of interdigitated control regions that could be separated after locus duplication in the teleost fish. PMID:16801555

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spike sorting based upon machine learning algorithms (SOMA).

PubMed

Horton, P M; Nicol, A U; Kendrick, K M; Feng, J F

2007-02-15

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would only identify a known number of clusters. Our extra techniques automatically identify the number of clusters within the dataset, and their sizes, thereby reducing the chance of misclassification. We also discuss a new pre-processing technique, which transforms the data into a higher dimensional feature space revealing separable clusters. Using principal component analysis (PCA) alone may not achieve this. Our new approach appends the features acquired using PCA with features describing the geometric shapes that constitute a spike waveform. To validate our new spike sorting approach, we have applied it to multi-electrode array datasets acquired from the rat olfactory bulb, and from the sheep infero-temporal cortex, and using simulated data. The SOMA sofware is available at http://www.sussex.ac.uk/Users/pmh20/spikes.

Designing and evaluating health systems level hypertension control interventions for African-Americans: lessons from a pooled analysis of three cluster randomized trials.

PubMed

Pavlik, Valory N; Chan, Wenyaw; Hyman, David J; Feldman, Penny; Ogedegbe, Gbenga; Schwartz, Joseph E; McDonald, Margaret; Einhorn, Paula; Tobin, Jonathan N

2015-01-01

African-Americans (AAs) have a high prevalence of hypertension and their blood pressure (BP) control on treatment still lags behind other groups. In 2004, NHLBI funded five projects that aimed to evaluate clinically feasible interventions to effect changes in medical care delivery leading to an increased proportion of AA patients with controlled BP. Three of the groups performed a pooled analysis of trial results to determine: 1) the magnitude of the combined intervention effect; and 2) how the pooled results could inform the methodology for future health-system level BP interventions. Using a cluster randomized design, the trials enrolled AAs with uncontrolled hypertension to test interventions targeting a combination of patient and clinician behaviors. The 12-month Systolic BP (SBP) and Diastolic BP (DBP) effects of intervention or control cluster assignment were assessed using mixed effects longitudinal regression modeling. 2,015 patients representing 352 clusters participated across the three trials. Pooled BP slopes followed a quadratic pattern, with an initial decline, followed by a rise toward baseline, and did not differ significantly between intervention and control clusters: SBP linear coefficient = -2.60±0.21 mmHg per month, p<0.001; quadratic coefficient = 0.167± 0.02 mmHg/month, p<0.001; group by time interaction group by time group x linear time coefficient=0.145 ± 0.293, p=0.622; group x quadratic time coefficient= -0.017 ± 0.026, p=0.525). RESULTS were similar for DBP. The individual sites did not have significant intervention effects when analyzed separately. Investigators planning behavioral trials to improve BP control in health systems serving AAs should plan for small effect sizes and employ a "run-in" period in which BP can be expected to improve in both experimental and control clusters.

Synthesis and Molecular Structure of a Novel Compound Containing a Carbonate-Bridged Hexacalcium Cluster Cation Assembled on a Trimeric Trititanium(IV)-Substituted Wells-Dawson Polyoxometalate.

PubMed

Hoshino, Takahiro; Isobe, Rina; Kaneko, Takuya; Matsuki, Yusuke; Nomiya, Kenji

2017-08-21

A novel compound containing a hexacalcium cluster cation, one carbonate anion, and one calcium cation assembled on a trimeric trititanium(IV)-substituted Wells-Dawson polyoxometalate (POM), [{Ca 6 (CO 3 )(μ 3 -OH)(OH 2 ) 18 }(P 2 W 15 Ti 3 O 61 ) 3 Ca(OH 2 ) 3 ] 19- (Ca 7 Ti 9 Trimer), was obtained as the Na 7 Ca 6 salt (NaCa-Ca 7 Ti 9 Trimer) by the reaction of calcium chloride with the monomeric trititanium(IV)-substituted Wells-Dawson POM species "[P 2 W 15 Ti 3 O 59 (OH) 3 ] 9- " (Ti 3 Monomer). Ti 3 Monomer was generated in situ under basic conditions from the separately prepared tetrameric species with bridging Ti(OH 2 ) 3 groups and an encapsulated Cl - ion, [{P 2 W 15 Ti 3 O 59 (OH) 3 } 4 {μ 3 -Ti(H 2 O) 3 } 4 Cl] 21- (Ti 16 Tetramer). The Na 7 Ca 6 salt of Ca 7 Ti 9 Trimer was characterized by complete elemental analysis, thermogravimetric (TG) and differential thermal analyses (DTA), FTIR, single-crystal X-ray structure analysis, and solution 183 W and 31 P NMR spectroscopy. X-ray crystallography revealed that the [Ca 6 (CO 3 )(μ 3 -OH)(OH 2 ) 18 ] 9+ cluster cation was composed of six calcium cations linked by one μ 6 -carbonato anion and one μ 3 -OH - anion. The cluster cation was assembled, together with one calcium ion, on a trimeric species composed of three tri-Ti(IV)-substituted Wells-Dawson subunits linked by Ti-O-Ti bonds. Ca 7 Ti 9 Trimer is an unprecedented POM species containing an alkaline-earth-metal cluster cation and is the first example of alkaline-earth-metal ions clustered around a titanium(IV)-substituted POM.

Optimizing measurements of cluster velocities and temperatures for CCAT-prime and future surveys

NASA Astrophysics Data System (ADS)

Mittal, Avirukt; de Bernardis, Francesco; Niemack, Michael D.

2018-02-01

Galaxy cluster velocity correlations and mass distributions are sensitive probes of cosmology and the growth of structure. Upcoming microwave surveys will enable extraction of velocities and temperatures from many individual clusters for the first time. We forecast constraints on peculiar velocities, electron temperatures, and optical depths of galaxy clusters obtainable with upcoming multi-frequency measurements of the kinematic, thermal, and relativistic Sunyaev-Zeldovich effects. The forecasted constraints are compared for different measurement configurations with frequency bands between 90 GHz and 1 THz, and for different survey strategies for the 6-meter CCAT-prime telescope. We study methods for improving cluster constraints by removing emission from dusty star forming galaxies, and by using X-ray temperature priors from eROSITA. Cluster constraints are forecast for several model cluster masses. A sensitivity optimization for seven frequency bands is presented for a CCAT-prime first light instrument and a next generation instrument that takes advantage of the large optical throughput of CCAT-prime. We find that CCAT-prime observations are expected to enable measurement and separation of the SZ effects to characterize the velocity, temperature, and optical depth of individual massive clusters (~1015 Msolar). Submillimeter measurements are shown to play an important role in separating these components from dusty galaxy contamination. Using a modular instrument configuration with similar optical throughput for each detector array, we develop a rule of thumb for the number of detector arrays desired at each frequency to optimize extraction of these signals. Our results are relevant for a future "Stage IV" cosmic microwave background survey, which could enable galaxy cluster measurements over a larger range of masses and redshifts than will be accessible by other experiments.

Shape analysis of H II regions - I. Statistical clustering

NASA Astrophysics Data System (ADS)

Campbell-White, Justyn; Froebrich, Dirk; Kume, Alfred

2018-07-01

We present here our shape analysis method for a sample of 76 Galactic H II regions from MAGPIS 1.4 GHz data. The main goal is to determine whether physical properties and initial conditions of massive star cluster formation are linked to the shape of the regions. We outline a systematic procedure for extracting region shapes and perform hierarchical clustering on the shape data. We identified six groups that categorize H II regions by common morphologies. We confirmed the validity of these groupings by bootstrap re-sampling and the ordinance technique multidimensional scaling. We then investigated associations between physical parameters and the assigned groups. Location is mostly independent of group, with a small preference for regions of similar longitudes to share common morphologies. The shapes are homogeneously distributed across Galactocentric distance and latitude. One group contains regions that are all younger than 0.5 Myr and ionized by low- to intermediate-mass sources. Those in another group are all driven by intermediate- to high-mass sources. One group was distinctly separated from the other five and contained regions at the surface brightness detection limit for the survey. We find that our hierarchical procedure is most sensitive to the spatial sampling resolution used, which is determined for each region from its distance. We discuss how these errors can be further quantified and reduced in future work by utilizing synthetic observations from numerical simulations of H II regions. We also outline how this shape analysis has further applications to other diffuse astronomical objects.

Shape Analysis of HII Regions - I. Statistical Clustering

NASA Astrophysics Data System (ADS)

Campbell-White, Justyn; Froebrich, Dirk; Kume, Alfred

2018-04-01

We present here our shape analysis method for a sample of 76 Galactic HII regions from MAGPIS 1.4 GHz data. The main goal is to determine whether physical properties and initial conditions of massive star cluster formation is linked to the shape of the regions. We outline a systematic procedure for extracting region shapes and perform hierarchical clustering on the shape data. We identified six groups that categorise HII regions by common morphologies. We confirmed the validity of these groupings by bootstrap re-sampling and the ordinance technique multidimensional scaling. We then investigated associations between physical parameters and the assigned groups. Location is mostly independent of group, with a small preference for regions of similar longitudes to share common morphologies. The shapes are homogeneously distributed across Galactocentric distance and latitude. One group contains regions that are all younger than 0.5 Myr and ionised by low- to intermediate-mass sources. Those in another group are all driven by intermediate- to high-mass sources. One group was distinctly separated from the other five and contained regions at the surface brightness detection limit for the survey. We find that our hierarchical procedure is most sensitive to the spatial sampling resolution used, which is determined for each region from its distance. We discuss how these errors can be further quantified and reduced in future work by utilising synthetic observations from numerical simulations of HII regions. We also outline how this shape analysis has further applications to other diffuse astronomical objects.

Assessing Many-Body Effects of Water Self-Ions. I: OH-(H2O) n Clusters.

PubMed

Egan, Colin K; Paesani, Francesco

2018-04-10

The importance of many-body effects in the hydration of the hydroxide ion (OH - ) is investigated through a systematic analysis of the many-body expansion of the interaction energy carried out at the CCSD(T) level of theory, extrapolated to the complete basis set limit, for the low-lying isomers of OH - (H 2 O) n clusters, with n = 1-5. This is accomplished by partitioning individual fragments extracted from the whole clusters into "groups" that are classified by both the number of OH - and water molecules and the hydrogen bonding connectivity within each fragment. With the aid of the absolutely localized molecular orbital energy decomposition analysis (ALMO-EDA) method, this structure-based partitioning is found to largely correlate with the character of different many-body interactions, such as cooperative and anticooperative hydrogen bonding, within each fragment. This analysis emphasizes the importance of a many-body representation of inductive electrostatics and charge transfer in modeling OH - hydration. Furthermore, the rapid convergence of the many-body expansion of the interaction energy also suggests a rigorous path for the development of analytical potential energy functions capable of describing individual OH - -water many-body terms, with chemical accuracy. Finally, a comparison between the reference CCSD(T) many-body interaction terms with the corresponding values obtained with various exchange-correlation functionals demonstrates that range-separated, dispersion-corrected, hybrid functionals exhibit the highest accuracy, while GGA functionals, with or without dispersion corrections, are inadequate to describe OH - -water interactions.

Analysis of Geographic and Pairwise Distances among Chinese Cashmere Goat Populations

PubMed Central

Liu, Jian-Bin; Wang, Fan; Lang, Xia; Zha, Xi; Sun, Xiao-Ping; Yue, Yao-Jing; Feng, Rui-Lin; Yang, Bo-Hui; Guo, Jian

2013-01-01

This study investigated the geographic and pairwise distances of nine Chinese local Cashmere goat populations through the analysis of 20 microsatellite DNA markers. Fluorescence PCR was used to identify the markers, which were selected based on their significance as identified by the Food and Agriculture Organization of the United Nations (FAO) and the International Society for Animal Genetics (ISAG). In total, 206 alleles were detected; the average allele number was 10.30; the polymorphism information content of loci ranged from 0.5213 to 0.7582; the number of effective alleles ranged from 4.0484 to 4.6178; the observed heterozygosity was from 0.5023 to 0.5602 for the practical sample; the expected heterozygosity ranged from 0.5783 to 0.6464; and Allelic richness ranged from 4.7551 to 8.0693. These results indicated that Chinese Cashmere goat populations exhibited rich genetic diversity. Further, the Wright’s F-statistics of subpopulation within total (FST) was 0.1184; the genetic differentiation coefficient (GST) was 0.0940; and the average gene flow (Nm) was 2.0415. All pairwise FST values among the populations were highly significant (p<0.01 or p<0.001), suggesting that the populations studied should all be considered to be separate breeds. Finally, the clustering analysis divided the Chinese Cashmere goat populations into at least four clusters, with the Hexi and Yashan goat populations alone in one cluster. These results have provided useful, practical, and important information for the future of Chinese Cashmere goat breeding. PMID:25049794

Worldwide clustering of the corruption perception

NASA Astrophysics Data System (ADS)

Paulus, Michal; Kristoufek, Ladislav

2015-06-01

We inspect a possible clustering structure of the corruption perception among 134 countries. Using the average linkage clustering, we uncover a well-defined hierarchy in the relationships among countries. Four main clusters are identified and they suggest that countries worldwide can be quite well separated according to their perception of corruption. Moreover, we find a strong connection between corruption levels and a stage of development inside the clusters. The ranking of countries according to their corruption perfectly copies the ranking according to the economic performance measured by the gross domestic product per capita of the member states. To the best of our knowledge, this study is the first one to present an application of hierarchical and clustering methods to the specific case of corruption.

Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer.

PubMed

Nurjuliana, M; Che Man, Y B; Mat Hashim, D; Mohamed, A K S

2011-08-01

The volatile compounds of pork, other meats and meat products were studied using an electronic nose and gas chromatography mass spectrometer with headspace analyzer (GCMS-HS) for halal verification. The zNose™ was successfully employed for identification and differentiation of pork and pork sausages from beef, mutton and chicken meats and sausages which were achieved using a visual odor pattern called VaporPrint™, derived from the frequency of the surface acoustic wave (SAW) detector of the electronic nose. GCMS-HS was employed to separate and analyze the headspace gasses from samples into peaks corresponding to individual compounds for the purpose of identification. Principal component analysis (PCA) was applied for data interpretation. Analysis by PCA was able to cluster and discriminate pork from other types of meats and sausages. It was shown that PCA could provide a good separation of the samples with 67% of the total variance accounted by PC1. Copyright © 2011 Elsevier Ltd. All rights reserved.

Use of UV Sources for Detection and Identification of Explosives

NASA Technical Reports Server (NTRS)

Hug, William; Reid, Ray; Bhartia, Rohit; Lane, Arthur

2009-01-01

Measurement of Raman and native fluorescence emission using ultraviolet (UV) sources (<400 nm) on targeted materials is suitable for both sensitive detection and accurate identification of explosive materials. When the UV emission data are analyzed using a combination of Principal Component Analysis (PCA) and cluster analysis, chemicals and biological samples can be differentiated based on the geometric arrangement of molecules, the number of repeating aromatic rings, associated functional groups (nitrogen, sulfur, hydroxyl, and methyl), microbial life cycles (spores vs. vegetative cells), and the number of conjugated bonds. Explosive materials can be separated from one another as well as from a range of possible background materials, which includes microbes, car doors, motor oil, and fingerprints on car doors, etc. Many explosives are comprised of similar atomic constituents found in potential background samples such as fingerprint oils/skin, motor oil, and soil. This technique is sensitive to chemical bonds between the elements that lead to the discriminating separability between backgrounds and explosive materials.

Compositional clustering in task structure learning

PubMed Central

Frank, Michael J.

2018-01-01

Humans are remarkably adept at generalizing knowledge between experiences in a way that can be difficult for computers. Often, this entails generalizing constituent pieces of experiences that do not fully overlap, but nonetheless share useful similarities with, previously acquired knowledge. However, it is often unclear how knowledge gained in one context should generalize to another. Previous computational models and data suggest that rather than learning about each individual context, humans build latent abstract structures and learn to link these structures to arbitrary contexts, facilitating generalization. In these models, task structures that are more popular across contexts are more likely to be revisited in new contexts. However, these models can only re-use policies as a whole and are unable to transfer knowledge about the transition structure of the environment even if only the goal has changed (or vice-versa). This contrasts with ecological settings, where some aspects of task structure, such as the transition function, will be shared between context separately from other aspects, such as the reward function. Here, we develop a novel non-parametric Bayesian agent that forms independent latent clusters for transition and reward functions, affording separable transfer of their constituent parts across contexts. We show that the relative performance of this agent compared to an agent that jointly clusters reward and transition functions depends environmental task statistics: the mutual information between transition and reward functions and the stochasticity of the observations. We formalize our analysis through an information theoretic account of the priors, and propose a meta learning agent that dynamically arbitrates between strategies across task domains to optimize a statistical tradeoff. PMID:29672581

A combined gene and cell therapy approach for restoration of conduction.

PubMed

Hofshi, Anat; Itzhaki, Ilanit; Gepstein, Amira; Arbel, Gil; Gross, Gil J; Gepstein, Lior

2011-01-01

Abnormal conduction underlies both bradyarrhythmias and re-entrant tachyarrhythmias. However, no practical way exists for restoring or improving conduction in areas of conduction slowing or block. This study sought to test the feasibility of a novel strategy for conduction repair using genetically engineered cells designed to form biological "conducting cables." An in vitro model of conduction block was established using spatially separated, spontaneously contracting, nonsynchronized human embryonic stem cell-derived cardiomyocytes clusters. Immunostaining, dye transfer, intracellular recordings, and multielectrode array (MEA) studies were performed to evaluate the ability of genetically engineered HEK293 cells, expressing the SCN5A-encoded Na(+) channel, to couple with cultured cardiomyocytes and to synchronize their electrical activity. Connexin-43 immunostaining and calcein dye-transfer experiments confirmed the formation of functional gap junctions between the engineered cells and neighboring cardiomyocytes. MEA and intracellular recordings were performed to assess the ability of the engineered cells to restore conduction in the co-cultures. Synchronization was defined by establishment of fixed local activation time differences between the cardiomyocytes clusters and convergence of their activation cycle lengths. Nontransfected control cells were able to induce synchronization between cardiomyocytes clusters separated by distances up to 300 μm (n = 21). In contrast, the Na(+) channel-expressing cells synchronized contractions between clusters separated by up to 1,050 μm, the longest distance studied (n = 23). Finally, engineered cells expressing the voltage-sensitive K(v)1.3 potassium channel prevented synchronization at any distance. Genetically engineered cells, transfected to express Na(+) channels, can form biological conducting cables bridging and coupling spatially separated cardiomyocytes. This novel cell therapy approach might be useful for the development of therapeutic strategies for both bradyarrhythmias and tachyarrhythmias. Copyright © 2011 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Deficit of Wide Binaries in the η Chamaeleontis Young Cluster

NASA Astrophysics Data System (ADS)

Brandeker, Alexis; Jayawardhana, Ray; Khavari, Parandis; Haisch, Karl E., Jr.; Mardones, Diego

2006-12-01

We have carried out a sensitive high-resolution imaging survey of stars in the young (6-8 Myr), nearby (97 pc) compact cluster around η Chamaeleontis to search for stellar and substellar companions. Our data were obtained using the NACO adaptive optics system on the ESO Very Large Telescope (VLT). Given its youth and proximity, any substellar companions are expected to be luminous, especially in the near-infrared, and thus easier to detect next to their parent stars. Here, we present VLT NACO adaptive optics imaging with companion detection limits for 17 η Cha cluster members, and follow-up VLT ISAAC near-infrared spectroscopy for companion candidates. The widest binary detected is ~0.2", corresponding to the projected separation 20 AU, despite our survey being sensitive down to substellar companions outside 0.3", and planetary-mass objects outside 0.5". This implies that the stellar companion probability outside 0.3" and the brown dwarf companion probability outside 0.5" are less than 0.16 with 95% confidence. We compare the wide binary frequency of η Cha to that of the similarly aged TW Hydrae association and estimate the statistical likelihood that the wide binary probability is equal in both groups to be less than 2×10-4. Even though the η Cha cluster is relatively dense, stellar encounters in its present configuration cannot account for the relative deficit of wide binaries. We thus conclude that the difference in wide binary probability in these two groups provides strong evidence for multiplicity properties being dependent on environment. In two appendices we derive the projected separation probability distribution for binaries, used to constrain physical separations from observed projected separations, and summarize statistical tools useful for multiplicity studies.

A robust multilevel simultaneous eigenvalue solver

NASA Technical Reports Server (NTRS)

Costiner, Sorin; Taasan, Shlomo

1993-01-01

Multilevel (ML) algorithms for eigenvalue problems are often faced with several types of difficulties such as: the mixing of approximated eigenvectors by the solution process, the approximation of incomplete clusters of eigenvectors, the poor representation of solution on coarse levels, and the existence of close or equal eigenvalues. Algorithms that do not treat appropriately these difficulties usually fail, or their performance degrades when facing them. These issues motivated the development of a robust adaptive ML algorithm which treats these difficulties, for the calculation of a few eigenvectors and their corresponding eigenvalues. The main techniques used in the new algorithm include: the adaptive completion and separation of the relevant clusters on different levels, the simultaneous treatment of solutions within each cluster, and the robustness tests which monitor the algorithm's efficiency and convergence. The eigenvectors' separation efficiency is based on a new ML projection technique generalizing the Rayleigh Ritz projection, combined with a technique, the backrotations. These separation techniques, when combined with an FMG formulation, in many cases lead to algorithms of O(qN) complexity, for q eigenvectors of size N on the finest level. Previously developed ML algorithms are less focused on the mentioned difficulties. Moreover, algorithms which employ fine level separation techniques are of O(q(sub 2)N) complexity and usually do not overcome all these difficulties. Computational examples are presented where Schrodinger type eigenvalue problems in 2-D and 3-D, having equal and closely clustered eigenvalues, are solved with the efficiency of the Poisson multigrid solver. A second order approximation is obtained in O(qN) work, where the total computational work is equivalent to only a few fine level relaxations per eigenvector.

Origin and evolution of the Perm Anomaly

NASA Astrophysics Data System (ADS)

Flament, N. E.; Williams, S.; Müller, D.; Gurnis, M.; Bower, D. J.

2016-12-01

Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs, 15000 km in diameter, 500-1000 km high) located under Africa and the Pacific Ocean. In addition, a single, much smaller ( 1000 km in diameter, 500 km high) deep mantle structure named the "Perm Anomaly" was recently identified through the analysis of seismic tomography models. This discovery challenges current reconstructions of the evolution of the plate-mantle system that invoke plumes rising from the edges of the two LLSVPs, assumed spatially fixed and non-deforming in time. Here, we present mantle flow models constrained by tectonic reconstructions that reproduce the present-day structure of the lower mantle, and show a Perm-like anomaly. In the dynamic models, spanning 230 Myr, subducting slabs deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour, mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify equally-spaced points on Earth's surface into two groups with similar variations in present-day temperature between 1000-2800 km depth, for each model case. The procedure reveals a high-temperature cluster and a low-temperature cluster with respect to ambient mantle temperature below 2400 km depth. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the LLSVPs and of the Perm Anomaly revealed by a similar cluster analysis of seven tomography models. Model success is quantified by computing the accuracy (between 0.56 and 0.76) of the temperature clusters in predicting the low-velocity cluster obtained from tomography, and qualified by the occurrence of a separate Perm-like anomaly. The anomaly formed in isolation prior to 150 Ma within a long-lived subduction network 22000 km in circumference composed of the Mongol-Okhotsk subduction along Eurasia to the west, northern Tethys subduction to the south, and east Asia subduction to the east, then migrated 2500 km westward at an average rate of 1.7 cm/yr, indicating a greater mobility of deep mantle structures than previously recognized. We infer that the mobile Perm Anomaly could be linked to the Emeishan volcanics, in contrast to the previously proposed Siberian Traps.